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Dental Age Estimation in Adults. An in-depth analysis of
secondary dentine deposition in different populations
and clinical conditions.
Talia Yolanda Marroquin Peñaloza DDS, MClinDent(Endodontist)
This thesis is presented for the degree of Doctor of Philosophy of The University of Western
Australia
School of Human Sciences
2017
1
THESIS DECLARATION
I, Talia Yolanda Marroquin Peñaloza, certify that:
This thesis has been substantially accomplished during enrolment in the degree.
This thesis does not contain material which has been accepted for the award of any other
degree or diploma in my name, in any university or other tertiary institution.
No part of this work will, in the future, be used in a submission in my name, for any other
degree or diploma in any university or other tertiary institution without the prior approval
of The University of Western Australia and where applicable, any partner institution
responsible for the joint-award of this degree.
This thesis does not contain any material previously published or written by another
person, except where due reference has been made in the text.
The work(s) are not in any way a violation or infringement of any copyright, trademark,
patent, or other rights whatsoever of any person.
The research involving human data reported in this thesis was assessed and approved by
The University of Western Australia Human Research Ethics Committee. Approval: (Ref:
RA/4/1/6797).
Written patient consent has been received and archived for the research involving
patient data reported in this thesis.
2
The work described in this thesis did not need funded of tertiary parties.
This thesis contains published work and/or work prepared for publication, some of which
has been co-authored.
Signature:
Date: 30th November, 2017.
3
SUMMARY
Dental age estimation has been an important issue for humanity since ancient times. In the
same way, different methods have been proposed through history for young individuals
and adults. Once forensic dentistry is an important branch of the forensic sciences, and
with the introduction of radiology in dentistry, it has been possible to propose non-invasive
methods for age estimation, based on the radiological analysis of the inverse relation of the
root canal size with age. Age estimation of adult individuals has always been a challenge,
as those methods based on the narrowing of the root canal, as a result of secondary
dentine production have shown wide variability in their results. This thesis analyses some
of the observed obstacles for dental age estimation in adults, and proposes new
approaches, aimed to overcome them.
The published papers presented in this thesis follow some of the previously proposed
methods for dental age estimation in adults, such as Kvaal et al’s method, and those
methods based on volume measurements of pulp and tooth, adapting, and testing them in
diverse groups of populations. Measurements have also been taken in individuals with
different dental characteristics, thereby challenging some of the established parameters for
dental age estimation as it is the exclusive analysis of totally sound teeth, in samples with a
unique ethnic background. Additionally, this thesis also includes what could be considered
to be the first literature review in forensic dentistry for dental age estimation in adults; a
study, with enormous contributions to this research field. This thesis also includes the
analysis of the possible factors that affect the accuracy of the tested methods.
4
CONTENTS
THESIS DECLARATION .................................................................................................................. 1
SUMMARY .................................................................................................................................... 3
CONTENTS .................................................................................................................................... 4
TABLE LIST .................................................................................................................................... 7
GRAPH LIST ................................................................................................................................... 9
ACKNOWLEDGEMENTS ............................................................................................................. 10
AUTHORSHIP DECLARATION. .................................................................................................... 12
GENERAL INTRODUCTION ......................................................................................................... 16
REFERENCES ............................................................................................................................... 25
SECTION ONE. Non-invasive methods for dental age estimation in adults: Systematic
Review. ....................................................................................................................................... 27
Preface ....................................................................................................................................... 27
1. Chapter 1. Age estimation in adults by dental imaging assessment systematic review28
SECTION TWO. Assessment of possible effect of orthodontic treatment on one of the
available methods for age estimation in adults: The Kvaal et al. method. ............................. 70
Preface ....................................................................................................................................... 70
2. Chapter 2. Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment .............................................................................................................. 76
3. Chapter 3. Orthodontic treatment: Real risk for dental age estimation in adults? ........ 95
SECTION THREE: New uses of the Kvaal et al method for age estimation in young
individuals and adults from different groups of population. ................................................ 111
5
Preface ..................................................................................................................................... 111
4. Chapter 4. Determining the effectiveness of adult measures of standardized age
estimation on juveniles in a Western Australian population. ............................................... 112
5. Chapter 5. Application of the Kvaal method for adult dental age estimation using Cone
Beam Computed Tomography (CBCT). ................................................................................... 132
SECTION FOUR: New technologies in dental age estimation. .............................................. 152
PREFACE ................................................................................................................................... 152
6. Chapter 6. Reliability and repeatability of pulp volumetric reconstruction through
three different volume calculations ....................................................................................... 153
7. Chapter 7. A new proposal to overtake population group differences for dental age
estimation in adults through pulp/tooth volume calculation. Pilot Study. .......................... 178
GENERAL DISCUSSION. ............................................................................................................ 196
GENERAL CONCLUSIONS ......................................................................................................... 204
APPENDIX 1. Age estimation in adults by dental imaging assessment systematic review. 209
APPENDIX 2. Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment ………………………………………………………………………………………………….. 219
APPENDIX 3. Orthodontic treatment: Real risk for dental age estimation in adults?.........226
APPENDIX 4. Determining the effectiveness of adult measures of standardized age
estimation on juveniles in a Western Australian population ……………………………..…………...231
APPENDIX 5. Application of the Kvaal method for adult dental age estimation using Cone
Beam Computed Tomography (CBCT)……………..…………………………………………………..………....242
APPENDIX 6. Reliability and repeatability of pulp volumetric reconstruction through three
different volume calculations………………………………………………………………………………………..…248
6
APPENDIX 7. A new proposal to overtake population group differences for dental age
estimation in adults through pulp/tooth volume calculation. Pilot Study. In press………….261
7
TABLE LIST
Table 1.1. Total studies reporting the use of the Cameriere et al. method. .......................... 38
Table 1.2. Total studies reporting the use of the Cameriere et al. method. ......................... 39
Table 1.3. Total studies reporting the use of volume calculation. ......................................... 40
Table 1.4. The Kvaal et al. method: Studies included in the quantitative analysis. .............. 41
Table 1.5. The Cameriere et al. method: Studies included in the quantitative analysis. ...... 42
Table 1.6. Volume calculation based methods. ...................................................................... 43
Table 2.1. Correlation coefficients before (1) and after orthodontic treatment (2). ................ 83
Table 2.2. Multiple regressions for estimation of chronological age (in years) for individual
maxillary and mandibular teeth in subjects before (1) and after (2) orthodontic treatment
.................................................................................................................................................... 84
Table 2.3. Multiple regressions for estimation of chronological age (in years) for the
combination of different teeth before orthodontic treatment .............................................. 85
Table 2.4. Multiple regressions for estimation of chronological age (in years) for the
combination of different teeth after orthodontic treatment ................................................. 86
Table 3.1. Contingency table to estimate if orthodontic treatment was a causal of
overestimation, when the Kvaal et al. method is used to age estimation. .......................... 102
Table 3.2. Comparison of over- and under-estimates obtained per tooth .......................... 103
Table 4.1. Correlation coefficients between chronological age and Kvaal dental
measurements and ratios, for individuals under 30 years of age. ........................................ 121
Table 4.2. Multiple regression for estimation of chronological age (in years) from individual
maxillary and mandibular teeth from individuals under 30 years of age. ............................ 122
8
Table 4.3. Multiple regressions for estimation of chronological age (in years) from the
combined maxillary and mandibular teeth. ........................................................................... 123
Table 5.1. Age and sex distribution for CBCT and i-CAT tomographs. .................................. 140
Table 5.2. Correlation coefficient measurements CBCT ........................................................ 140
Table 5.3. Linear regression analysis, linear regression formulae, correlation coefficient (r)
between age and the ratios of bucco-lingual and mesio-distal width measurements from
CBCT & i-CAT ............................................................................................................................ 141
Table 6.1. Volume results of using automatic segmentation (Vol 1), manual segmentation
using just the first and last slice (Vol 2), and manual segmentation each forth slice (Vol3), of
cone beam computer tomography from upper canines. (FDI 13, 23) .................................. 163
Table 6.2. Cone shape approach results using the tool polygon (Pol) and oval (Oval). Pulp
area (in mm2) at the CEJ level and volume (in mm3) calculation with the measured root
length (in mm). ........................................................................................................................ 164
Table 6.3. Setting parameter combinations used in part C. ................................................. 165
Table 7.1. Distribution of the individuals for age in years and country; Malaysia (Mal) and
Colombia (Col) used for the image segmentation and volume calculation in this study. ... 186
9
GRAPH LIST
Graph 1.1. Flow chart of the study selection for the Kvaal et al. method. ............................ 35
Graph 1.2. Flow chart of the study selection for the Cameriere et al. method .................... 36
Graph 1.3. Flow chart of the study selection for methods based on volume calculation. ... 37
Graph 4.1. Scatter plot showing a positive association between the estimated age in years
and the chronological age in years for the teeth 33/43 ........................................................ 122
Graph 6.1. Volumetric reconstructions, upper right canine using different methods. ..... 162
Graph 7.1. Scatter plot showing the correlation between age and the pulp/pulp+tooth
volume ratio. (P/PT ratio) R2=0.42 .......................................................................................... 186
10
ACKNOWLEDGEMENTS
This thesis is the result of an international collaboration between different eminences from
4 different countries: Australia, Colombia, Malaysia and Norway, from some of the most
prestigious institutions around the world. The National University of Malaysia, The National
University of Colombia, The University of Oslo, and The University of Western Australia. It
has been an honor to count upon their support through this journey, which started only as
an academic project, but that now is an incredible personal and professional achievement.
I want to thank my supervisors, Dr. Shalmira Karkhanis, Dr. Sigrid I. Kvaal, Dr. Estie Kruger,
Dr. Sivabalan Vasudavan, and Dr. Marc Tennant, who enlightened me with their diverse
knowledge, supported me in those difficult moments, inspired me with their different
goals, and leaded me in my professional growth. I thank Professor John McGeachie for his
collaboration with the final editing of this document. I also want to thank Dr. Nurul Firdaus,
Dr. Mohaed Shahida Mohd Said, Dr. Shalini Kanagasingam, Dr. Manuel Gonzalez, and Dr.
Claudia Garcia, who trusted on me and gave me access to their data bases. I want to thank
to Dr. Daniel Franklin and Dr. Ambika Flavel for their support through the Forensic Science
Center at The University of Western Australia. Also, I want to thank to all those
anonymized patients, who accepted that their records were used for the good of science.
I want to bring special recognition to Edwin Castelblanco, Marty Firth, and Alethea Rea,
who supported me in the statistical analysis of the data.
11
I also want to thank Colfuturo and Colciencias – Colombia, for having awarded me with the
international scholarship program, which helps Colombian students to continue with their
academic formation undertaking research degrees in the best universities around the
world. I hope, this thesis contributes to the academic and scientific development of our
country. Finally, I want to thank my friends and family who supported me during all these
studying years, this achievement would not have been possible without their support.
Talia Yolanda Marroquin Peñaloza
12
AUTHORSHIP DECLARATION.
This thesis contains work that has been published, accepted for publication, and submitted
for publication, and follows the format of my thesis by a series of papers, as stipulated by
The University of Western Australia for the Degree of Doctor of Philosophy,
In this thesis, all seven papers (7 primary) listed have undergone peer review, 6 have been
already published, and in all papers, the candidate was responsible for the work. The
candidate collected and analyzed the data.
The data were processed, and this information enabled the candidate to scrutinize existing
theories. With this knowledge, the candidate created new knowledge generated new
concepts, methodologies and understandings. With permission, the candidate was given
authority to submit the work for publication.
This thesis is comprised of a series of published papers in peer reviewed journals of which
all of them have been co-authored.
PhD Candidate, Talia Yolanda Marroquin Peñaloza. 30th , November, 2017.
Coordinating Supervisor, Winthrop Professor Marc Tennant. 30th November, 2017.
13
PUBLICATIONS ARISING FROM THIS THESIS
For all the papers of this thesis the contribution of the first author was estimated to be at
least 85% as co-author:
1. Chapter 1
Marroquin, T. Y., S. Karkhanis, S., Kvaal, S. I., Vasudavan, S., Kruger, E., & Tennant, M.
Age estimation in adults by dental imaging assessment systematic review. Forensic
Science International Journal. Accepted for publication. March 2017.
2. Chapter 2.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016) Changes in age estimation standards secondary to full fixed
edgewise orthodontic treatment. European Journal of Forensic Science, Accepted for
publication. June 2016.
3. Chapter 3.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Orthodontic Treatment: Real Risk for Dental Age Estimation in
Adults? Journal of Forensic Science. Accepted for publication. October 2016.
4. Chapter 4.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Determining the effectiveness of adult measures of standardised
14
age estimation on juveniles in a Western Australian population. Australian Journal of
Forensic Sciences. Accepted for publication. March 2016.
5. Chapter 5.
Marroquin, T.Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Nurul F., Kanagasingam S., D.
Franklin., E., Kruger, E., & Tennant, M. (2016) Application of the Kvaal method for adult
dental age estimation using Cone Beam Computed Tomography (CBCT). Journal of
Forensic and Legal Medicine, Accepted for publication. October 2016.
6. Chapter 6.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. Reliability and repeatability of pulp volumetric reconstruction through
three different volume calculations. Journal of Forensic Odontostomatology. Accepted
for publication. March 2017.
7. Chapter 7.
Marroquin, T.Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Nurul F., Kanagasingam S., D.
Franklin., E., Kruger, E., & Tennant, M. A new proposal to overtake population group
differences for dental age estimation in adults through pulp/tooth volume calculation.
Pilot Study. In press.
Student signature: Talia Yolanda Marroquin Peñaloza
15
The external supervisors, Shalmira Karkhanis, Sigrid Kvaal, and Sivabalan Vasudavan,
agreed with the contents and papers published in this thesis.
I, Marc Tennant certify that the student statements regarding their contribution to
each of the works listed above are correct
Coordinating supervisor signature: Estie Kruger
Date: 30th November, 2017.
16
GENERAL INTRODUCTION
Forensic science has been defined as the application of science to the law or legal
scenarios. In the same way, forensic dentistry refers to the application of dentistry to the
law to interpret dental and related evidence in criminalistics fields, having important value
for identification of individuals [1]. More, specifically, forensic dentistry is a specialized
branch of dentistry that uses specialised knowledge to collect, manage, interpret, evaluate
and present dental evidence for legal proceedings. This is applicable to dental
identification, sex determination, cheiloscopy and palatoscopy, molecular biomarkers, bite
mark analysis, human abuse and neglect, dental malpractice and negligence, dental
anthropology and archaeology, and the main scope of this thesis is concerned with age
estimation [2].
Age is one of the most important features to establish the identity of any individual, next to
sex, height, and ethnicity [3]. The need to confirm the age of different individuals has been
a crucial topic in anthropological, legal, and later in forensic scenarios. One forensic case
that has been stipulated as the first using dental age estimation with forensic purposes [1],
was narrated in the book “L’Art Dentaire en medicine legale” by Dr. Oscar Amoedo in 1898
[4], the father of forensic dentistry. This is related to the story of Louis-Charles Capet, or
Louis XVII of France, son of Louis XVI and Marie-Antoniette.
He passed away at the age of ten years two months, in prison, in 1795. However, the coffin
with his remains could not been found. It was believed that he had been substituted with
17
other boy his age, and that the prince was still alive; with this, a number of individuals
unsuccessfully claimed to be Louis XVII. In 1849, in the old cemetery of St Margarite a lead
coffin was found, with a skeleton, believed to belong to the young prince.
The first examinations, by Dr. Milcent, determined that these were the remains of Louis
XVII, but Dr. Recamier rejected this hypothesis, based on a dental exam, and claimed that
the individual was 15 to 16 years old. This little story, that could have been a fragment of a
fairy tale, is only one simple example that highlights the relevance of forensic dentistry and
the role of the forensic dentist to confirm the age and identity of different individuals.
Up to date, many methods have been proposed for age estimation, using different
indicators which vary somewhat, since the study of bone changes with maturation up to
more invasive techniques, based on chemical analysis of different tissue samples. All these
methods, have displayed a wide variability in their accuracy and reliability, which is even
more questionable when it comes to the analysis of individuals that have reached their
physical maturity.
Dentistry has contributed substantially to forensic sciences, in regards of age estimation,
having a relevant and positive impact, helping in the analysis and resolution of many cases
around the world. Among the different available methods for age estimation, those that
are minimally invasive are of interest owing to the major advantage of not requiring tooth
extraction, making them appropriate for the identification of unknown deceased
18
individuals, and also for the identification of living individuals with doubtful documents of
identification.
Teeth analysis for age estimation and identification of individuals has different advantages
over the analysis of osseous tissue, such the high resistance of teeth to decomposition and
taphonomic processes, which make them suitable for study long after the individual has
deceased [3]. Furthermore, age-related changes in teeth can be observed and studied on
dental radiographs, offering minimally invasive methods, which is not always possible with
bone analysis.
The genetically controlled process of tooth formation provides reliable data for the age
estimation of individuals, that have not completed tooth maturation. In this way, there are
different methods to estimate the age of individuals, from the 14th week of gestation, up to
the age of 21 years, where due to the analysis of third molars formation it is possible to
establish if they are over or under the age of 18 years [5].
Nevertheless, age estimation in individuals with their dentition, totally formed, is still a
challenge. Numerous methods have been proposed for dental age estimation in adults.
Although, in certain cases, the accuracy and reliability could be questionable, each one has
been an important step for the proposal of more modern, easier, and accurate methods.
In 1925, Bodecker [6] identified a dental change that is related with age and can be
observed once the root development has finished. This is the apposition of secondary
19
dentine, on the walls of the root canal. The formation of secondary dentine commences
once the tooth formation has finished, making the root canal or pulp chamber smaller [7].
In this way, a negative correlation between the age of the individual and the dimensions of
the root canal may be established [8].
In 1950, Gustafson [9] proposed a method that included the analysis of dental attrition,
periodontosis, cementum apposition, root resorption, root transparency, and the
formation of secondary dentine, which for his study, had to be observed on microscopic
sections. The methodology proposed a system of points depending on the status of the
different age indicators.
The sum of points and the relation with age was recorded; this revealed an increase of
points with age. With this, the author affirmed that it was possible to draw a regression
line for the relationship between age and points; however, this system was not applicable
for teeth in broken-down condition.
The author also recommended that those who chose to use this method had to create their
own standard curve. Since then, the statistical rigor of methods has noticeably increased,
as well as the number of participants in different studies. However, the use of linear
regression models has remained constant and is still an important method for the
development for age estimation in adults.
20
As the dimensions of the root canal can be measured in dental radiographs or dental
tomography, different methods have been proposed. In 1995 Kvaal et al. [8], published a
method based on linear measurements of tooth, root and pulp chamber length and the
measurement of the width of the tooth, and root canal at three different levels on the
roots. All these measures had to be taken from six different single rooted teeth in
periapical radiographs.
The original method demanded the use of Vernier calipers to measure the length, and a
stereomicroscope with a measuring eyepiece to the nearest 0.1mm with which to measure
the width of pulp and root. It was proposed that the calculation of pulp/tooth ratio
dimensions and the application of linear regression models were adequate to produce a
formula for age estimation in individuals older than 20 years.
Up until now, this method has been tested in at least 29 studies in 12 different countries;
some studies have modified or adapted the original method to the new emerging imaging
technology in dentistry. In this thesis, this method was tested in new scenarios and
adapted to new technologies.
Following the same principle of secondary dentine production with age and the negative
correlation between root canal size and age, Cameriere et al. [9], proposed a method based
on area measurements of root canal and tooth. As the available technology, at the time of
the elaboration of this method, was different, this method requires the use of digital
radiograph and the access to specific software.
21
This method has also been tested in at least 29 studies in 11 countries. It is also based on
the negative correlation of the pulp/tooth dimension ratio with age, but requires area
measurements. One of the last proposals, for age estimation in adults, is the calculation of
pulp and root canal volume from computed tomography (CT) or cone beam computed
tomography (CBCT).
This last method, is still under development. However, at least 16 studies from 7 countries
have been published using different techniques and software. In this thesis, some of the
published methodologies were analyzed, and a new method is proposed to estimate dental
age in adults. The above-mentioned methods, besides being based on the production of
secondary dentine with age, have another similar feature: the proposal of linear regression
models and equations to estimate the age of the individuals.
The use of the pulp/tooth ratio calculation, not only helps the researchers to observe how
the size of the root canal or pulp chamber changes with age, but also, as established by
Kvaal et al., it is useful to diminish the effects of image magnification [8], and probably sex.
On the other hand, the brief description of some of the different methods for dental age
estimation testifies to the strong relation between forensic dentistry and radiology. The
use of radiology in dentistry, and forensic dentistry dates back to 1895, when Wilhelm
Conrad Röntgen discovered the X-rays. One year later, in 1896, there were significant
advances for the application of radiology in dentistry.
22
Some of the most relevant contributors were Otto Walhoff, who obtained a radiograph of
his own maxillary sinuses, and a dental radiograph using dried human skulls. Furthermore,
Edmund Kells, who is recognized as a dental pioneer and scientific genius [10], introduced
radiology into dentistry, obtaining images from living patients.
Also in 1896, it was reported that one of the first uses of radiology for forensic applications
to confirm the presence of bullets inside the head of a woman, who had been attacked by
her husband [11]. For those days, to obtain a radiographic record, it was necessary to
expose the individual to X-radiation for up to 70 minutes [12]. During the following years,
the technology and new techniques in radiology have not only reduced the exposure times,
but also have provided forensic science with new and better techniques, to support the
resolution of different legal cases.
Now, in a digital era, plus the easy access to the Internet, to obtain, analyze, duplicate and
share images, it is faster than ever, promoting the proposal of new emergent methods for
identification and age estimation. This has allowed forensic teams, and academic
researchers to collaborate, using two and three-dimensional images. As it has been
described above, in forensic dentistry and age estimation, there have been major
developments since the time of the young prince, Louis XVII of France.
At this stage, it is important to clarify that those studies on dental age estimation for young
and older individuals have been based essentially, on the analysis of totally sound teeth,
and the vast majority of the published studies have obtained data from individuals who
23
belong to the same population. However, there are different challenges for dental age
estimation in adults that should be considered.
Firstly, there is no available systematic review that compares the accuracy of the above
mentioned three different methods for age estimation. This thesis presents the first
systematic review in forensic dentistry for age estimation in adults that follows the
parameters established by the Cochrane handbook for systematic reviews-methodology, in
the absence of guidelines for forensic sciences.
Secondly, it has been overlooked that the production of secondary dentine can be affected
by external factors, generating the production of tertiary dentine, the two of which are
undistinguishable in dental radiographs. Furthermore, it has been suggested that for
dental age estimation it is necessary to use only totally sound teeth, excluding those
individuals who have received orthodontic treatment, a dental procedure that is becoming
popular and that also alters pulp chamber size and tooth length, parameters used for the
application of the Kvaal et al. method.
Thirdly, tooth formation finishes, in general, at the age of 14 years. For age estimation of
older individuals (adolescents and sub-adults), the available methods are based on the
radiological analysis of third molar root formation. However, there is a problem with some
young individuals with agenesis of third molars.
Fourthly, despite the introduction of tomography in dentistry, there are no studies testing
the Kvaal et al. method on CBCT, an analysis that is useful to perform, as it could provide
24
more tools for dental age estimation in adults, performing linear measurements not only in
a coronal, but also a sagittal plane, inaccessible in routine dental radiographs.
Fifthly, although the introduction of tomography to dentistry and forensic dentistry has
promoted the proposal of different methods based on volume reconstruction, no study has
considered the different technological aspects, unique to each software and techniques
used to undertake the respective volume measurement.
Finally, there are distinct advantages of available imaging techniques, which allow
researchers to obtain volume measurements of any anatomic region, as well as the
advantages that telecommunication brings to share images and data.
The above factors, could be considered as challenges when different non-invasive methods
are used for dental age estimation in adults. The first aim of this thesis is to look for an
answer to these challenges. To this end, a series of 7 papers are presented and their
results are discussed in 4 different sections that this thesis encompasses.
25
REFERENCES
1. Senn DR. Forensic Dentistry. 2nd Ed. Boca Raton, FL: CRC; Press, 2009.
2. Rai B., & Kaur, J. Dental Age Estimation. In Evidence-Based Forensic Dentistry.
Springer Berlin Heidelberg; Press, 2012.
3. Franklin D. Forensic age estimation in human skeletal remains: Current concepts
and future directions. Leg Med. 2010;12:1-7.
4. Silva RF, Franco A. L'art dentaire en médecine legale. RBOL. 2016;3,1.
5. Senn DR, Weems RA. Manual of Forensic Odontology. 5th ed. Boca Raton, FL:
CRC; Press, 2013.
6. Bodecher CF. A consideration of some of the changes in the teeth from young to
old age. Dental Cosmos. 1925;67:543-9.
7. Panchbhai AS. Dental radiographic indicators, a key to age estimation.
Dentomaxillofacial Radiol. 2011;40:199-212.
8. Kvaal SI, Kolltveit KM, Thomsen IO, Solheim T. Age estimation of adults from
dental radiographs. Forensic Sci Int. 1995;74:175-85.
9. Cameriere R, Ferrante L, Cingolani M. Variations in pulp/tooth area ratio as an
indicator of age: a preliminary study. J Forensic Sci. 2004;49:317-19.
26
10. Jacobsohn P, Kantor M, Pihlstrom B. The X-ray in dentistry, and the legacy of C.
Edmund Kells A commentary on Kells CE. The X-ray in dental practice. J Natl
Dent Assoc 1920; 7:241-272. J Am Dent Assoc. 2013;144:15S-9S.
11. Thali MJ, Brogdon B, Viner MD. Forensic radiology, Second edition. CRC Press;
2002.
12. Chandrasekhar T, Vennila P. Role of Radiology in Forensic Dentistry. J Indian
Acad Oral Med Radiol. 2011;23:229-31.
27
SECTION ONE. Non-invasive methods for dental age estimation in adults: Systematic
Review.
Preface
Being one of the main issues in forensic and anthropological sciences, age estimation in
adults has been the target of researchers in the field. In the same way, the analysis of
dental age-related changes in adults has been widely explored, based on the clinical
observation of certain dental changes such as tooth attrition and periodontal recession,
which are not reliable age indicators.
The aim of this thesis is the analysis of non-invasive dental age estimation in adults, based
on the radiological measurement of the age-related dimensional change of the root canal,
due to secondary dentine production through life. To this end, a systematic review was
carried out, collecting all the available publications on linear measurements of tooth and
pulp width and length, area measurements of tooth and pulp, and also pulp/tooth volume
quantification from dental computed tomography.
The aim, methodological design and findings of this systematic review are presented in
Chapter 1. This systematic review is one notable achievement from this thesis as, to date,
there is no similar publication in forensic dentistry or in the anthropological science
literature.
28
1. Chapter 1. Age estimation in adults by dental imaging assessment systematic review
This chapter was published as:
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Kruger, E., & Tennant, M. Age
estimation in adults by dental imaging assessment. Systematic review. Forensic Science
International Journal. Accepted for publication, March 2017.
29
ABSTRACT
Importance: The need to rely on proper, simple, and accurate methods for age estimation
in adults is still a world-wide issue. It has been well documented that teeth are more
resistant than bones to the taphonomic processes, and that the use of methods for age
estimation based on dental imaging assessment are not only less invasive than those based
on osseous analysis, but also have shown similar or superior accuracy in adults.
Objectives: To summarise the results of some of the most recently cited methods for
dental age estimation in adults, based on odontometric dental imaging analysis, to
establish which methods are more accurate, accessible, and simple.
Evidence review: A literature search from several databases was conducted from January
1995 to July 2016 with previously defined inclusion criteria.
Conclusion: Based on the findings of this review, it could be possible to suggest pulp/tooth
area ratio calculation from first, upper canines and other single rooted teeth (lower
premolars, upper central incisors), and a specific statistical analysis that considers the non-
linear production of secondary dentine with age, as a reliable, easy, fast, and predictable
method for dental age estimation in adults. The second recommended method is the
pulp/tooth width-length ratio calculation. The use of specific population formulae would
be recommended, but to include data of individuals from different groups of populations in
the same analysis is not discouraged. A minimum sample size of at least 120 participants is
recommended to obtain more reliable results. Methods based on volume calculation are
time consuming and still need improvement.
Key words: Forensic dentistry, adults, age estimation, dental imaging, systematic review.
30
INTRODUCTION
Age is one of the most important characteristics used to establish the identity of any
individual in different legal, forensic, or anthropological research context [1]. To this end,
forensic teams depend on osseous analysis based methods, which have acceptable results
for young individuals or in their early adulthood [2], and dental development based
methods, which are highly reliable in individuals under 21 years of age [3].
However, these methods have some disadvantages: the poor resistance of bones to the
taphonomic process [4], and once the individual reaches the threshold of 21 years of age,
and third molars development concludes [3], the currently available dental development
based methods are not applicable. In individuals with the congenital absence of third
molar teeth, this threshold is not applicable for individuals older than 14 – 15 years of age.
To respond to the need of an aging population, and with the evident resistance of teeth to
the taphonomic process, alternative methods for dental age estimation in adults have been
proposed. Primarily, these are based on the formation of secondary dentine, studied since
1950 [5], and the subsequent narrowing of the pulp cavity, which can be observed in dental
radiographs, leading to the proposal of minimally invasive methods.
This systematic review focuses on three methods based on odontometric analysis of the
pulp cavity, performing length and width measurements [6], area measurements [7], and
lastly, volume calculation [8]. The objective of this review is to summarise the results of
31
these recently most cited methods for dental age estimation in adults, to establish which
method is more accurate, accessible, and simple.
Description of the problem
Different methods have been published for dental age estimation in adults, based on the
pulp/tooth dimensions’ ratios. Nevertheless, the results of the application of some of these
methods for dental age estimation, in adults from different population groups, exceeds the
accepted threshold in forensic sciences, which indicates that the standard deviation of a
method for adult’s age estimation should preferable be below a standard deviation (SD) of
years ±10 years [9].
Description of the methods being investigated
The methods for dental age estimation in adults, analysed in this paper, were selected
based on their minimally invasive nature, not a requirement for the extraction of teeth to
be performed, and pulp/tooth ratio calculation, which have been applied in individuals
from different populations. The Kvaal et al. [6] method is based on the analysis of linear
measurements of the pulp, tooth, and root length as well as root and pulp width
measurements at three different root levels, initially applied on periapical radiographs, and
later on panoramic radiographs and tomographs. The Cameriere et al. [7, 10] method is
based on the analysis of pulp and tooth area measurements on periapical, and panoramic
radiographs. Finally, different methods for dental age estimation in adults, based on
pulp/tooth volume ratio from cone beam computer tomography [8, 11-14], were included
in this systematic review.
32
How these methods might work
The methods in this study are based on a negative correlation between age and the pulp
chamber size, as well as on the tooth/pulp ratio calculation, regardless of the nature of the
measurements: length/width, area, or volume. In other words, all measurements evaluate
the association of one age related phenomenon, as it is the formation of secondary dentine
with the decrease of pulp chamber size with age. This has been accepted as an age
indicator that is observable and measurable with different dental imaging techniques.
Ideally, the accuracy of the methods should not exceed the threshold of a SD ±10 years [1,
4].
Why it is important to do this review
The relevance of this review is grounded on the need to recommend a method for dental
age estimation with the following characteristics: simple, fast, non-invasive, non-expensive,
and reproducible, and over all, accurate; that can be systematically used in different
academic and forensic scenarios. The objective is to aid the reconstruction of identity
profiles of unidentified deceased individuals or living individuals with doubtful identity
documents.
METHODS
Criteria for considering studies for this review
Qualitative analysis of the original human studies reporting the use of any of the listed
methods for dental age estimation, based on pulp/tooth ratio calculation (length/width,
33
area, volume) were included; in particular, those that preferably reported intra-inter
observer calibration, generating population specific formulae.
Studies with samples including individuals younger than 14 years of age were excluded, as
well as studies with small sample sizes (n<50), and those using extracted teeth. Also,
studies that did not report the use of specific population formulae were excluded for the
quantitative analysis.
Search methods for identification of studies
The information was searched though data-bases available at The University of Western
Australia, which included the collections of:
Directory of open access journals (DOAJ), Medline/PubMed (NLM), OneFile (GALE),
ProQuest, collection, (Web of Science), Science Direct Journals (Elsevier), Social Sciences
Citation Index (Web of Science), Scopus (Elsevier), Social Sciences Citation Index (Web of
Science), Wiley (Cross Referenced), Wiley Online Library. Also, Google Scholar, by papers
that referenced the original study performed by Kvaal et al., Cameriere et al., and those
methods for age estimation that referred to the use of CBCT and volume reconstruction of
pulp chambers and teeth.
The search key words were as follows: Kvaal and dental age estimation, Cameriere and
dental age estimation, age, and tooth volume. The literature search included publications
by these key authors after the publication of their original papers up until July 2016. The
34
search was conducted during the years 2014 to 2016. This systematic review follows the
Cochrane handbook for systematic reviews-methodology and, where possible, the RevMan
software recommended by the Cochrane handbook. (Graphs 1.1-1.3)
DATA COLLECTION AND ANALYSIS
Selection of studies
The initial selection was based on the title and abstract. Papers with titles that referred the
inclusion of minors only (children) were excluded. Studies reporting the use of third molars
or developing teeth were excluded. Studies that included the use of other methods for
dental age estimation in children were excluded (Demirjian), or any other invasive method
for dental age estimation were excluded. (Graphs 1.1-1.3, Tables 1.1-1.3)
Data extraction and management
The data were organized in an Excel spreadsheet as follows: Author, year, country, number
of participants (male and female), age, intra and inter-observer agreement assessment.
Also recorded were: the imaging technique, measuring instrument, best correlation
coefficient between age and the different age predictors, best result in terms of accuracy
per individual tooth or per set of teeth, when possible, as well as the highest error recorded
by a set of teeth or individual tooth (Table 1.4-1.6).
Assessment of risk of bias in included studies
To avoid bias in this systematic review, and to avoid false positive or false negative
35
Graph 1.1. Flow chart of the study selection for the Kvaal et al. method.
36
Graph 1.2. Flow chart of the study selection for the Cameriere et al. method
37
Graph 1.3. Flow chart of the study selection for methods based on volume calculation.
38
Table 1.1. Total studies reporting the use of the Cameriere et al. method.
Author Year Country Total* Age
Kvaal et al. [6] 1995 Norway 100 20-87
Kvaal et al. [16] 1999 Sweden 21 20-60
Willems et al. [9] 2002 Belgium 29 26-85
Soomer et al. [1] 2003 Caucasian 20 14-95
Bosmans et al. [20] 2005 Belgium 197 19-75
Paewinsky et al. [19] 2005 Germany 168 18-81
Meinl A. [31] 2007 Austria 44 13-24
Avendaño et al. [18] 2009 Colombia 107 21-50
Landa M. [32] 2009 Portugal 100 14-60
Shetty et al. [15] 2010 India 100 20-70
Sharma et al. [71] 2010 India 50 15-60
Saxena. [30] 2011 India 120 21-60
Saxena, Tiwari [40] 2011 India 160 21-60
Chandramala et al. [21] 2012 India 100 20-70
Kanchan et al. [35] 2012 India 100 25-77
N. Agarwal. [17] 2012 India 50 20-70
Erbudak et al. [29] 2012 Turkey 123 15-57
Thevissen et al. [33] 2012 Belgium 450 15-23
Limdiwala et al. [22] 2013 India 150 20-55
Parkin et al. [28] 2013 India 30 15-60
Kostenko. [72] 2013 Ukraine 64 ---
Karkhanis et al. [24] 2014 Australia 279 20-62
Misrlioglu et al. [25] 2014 Turkey 114 17-72
Patil et al. [69] 2014 India 200 20-50
Edward et al. [23] 2014 Sudan 99 15-30
Muszynska et al. [34] 2015 Poland 3 ---
Marroquin et al. [26] 2016 Australia 74 12-28
Mittal et al. [27] 2016 India 152 14-56
Rajpal et al. [70] 2016 India 50 15-57
29 papers 12 Countries 3254 12-95
*Number of individuals reported in each study. Sample size.
39
Table 1.2. Total studies reporting the use of the Cameriere et al. method.
Author Year Country Total Age
Cameriere et al. [7] 2004 Italy 100 18-72
Cameriere et al. [52] 2006 Italy 33 ---
Cameriere et al. [10] 2007 Italy 100 20-79
Cameriere et al. [36] 2007 Italy 100 20-79
Cattaneo et al. [64] 2008 Ethiopia 1 52
Cameriere et al. [37] 2009 Portugal and Italy 229 20-84
Singaraju et al. [38] 2009 India 200 18-72
Babshed. [4] 2010 India 178 20-70
De luca et al. [2] 2010 Spain – Italy 73 ---
Babshed et al [50] 2011 India 61 21-71
Cameriere et al [73] 2011 Italy 90 50-79
Jeevan et al. [39] 2011 India 228 16-72
Saxena [30] 2011 India 120 21-60
Vodanovic et al. [65] 2011 Croatia 192 ---
Zaher et al. [41] 2011 Egypt 144 12-60
De luca et al. [51] 2011 Mexico 85 18-60
Cameriere et al. [42] 2012 Spain 606 18-75
Cameriere et al. [46] 2013 Portugal 116 18-74
Charis et al. [43] 2013 India 120 20-70
Cameriere et al. [46] 2013 Portugal 116 18-74
AC Azevedo. [44] 2014 Italy 81 19-74
Misirlioglu et al. [25] 2014 Turkey 114 17-72
Azevedo et al. [44] 2015 Brazil 443 20-78
Ravindra et al. [47] 2015 India 308 9-68
Cameriere et al. [74] 2015 Italy 70 20-70
De Angelis et al. [67] 2015 --- 1 ---
Fabbri et al. [66] 2015 Italy 18 ---
Sakhdari et al. [48] 2015 Iran 120 >12
Torkian. [75] 2015 Iran 120 >12
29 papers 11 Countries 4167 12-79
*Number of individuals reported in each study: Sample size.
40
Table 1.3. Total studies reporting the use of volume calculation.
*Number of individuals reported in each study: Sample size.
Author Year Country Total* Age
Vandervoort et al. [8] 2004 Belgium 52 24-66
Yang F. et al. [11] 2006 Belgium 19 23-70
Someda et al. [12] 2009 Japan 155 12-79
Agematsu et al. [61] 2010 Japan 258 teeth 20-79
Aboshi et al. [13] 2010 Japan 50 20-78
Star et al. [55] 2011 Belgium 111 10-65
Tardivo et al. [56] 2011 France 58 14-74
Jagannathan et al. [14] 2011 India 188 10-70
Sakuma et al. [53] 2013 Japan 136 14-79
Tardivo et al. [57] 2014 France 210 15-85
Sasaki et al. [54] 2014 Japan 363 15-70
Mendonca et al. [60] 2015 Brazil 72 22-70
Ge et al. [62] 2015 China 403 12-69
De Angelis et al. [58] 2015 Italy 91 17-80
Pinchi et al. [59] 2015 Italy 148 10-80
Ge et al. [59] 2016 China 240 16-63
16 papers 7 Countries 2296 10-85
41
Table 1.4. The Kvaal et al. method: Studies included in the quantitative analysis.
Study Sample Measuring instrument SEE ± years per tooth or group of teeth (FDI)
6 teeth Upper Lower 11/21 12/22 15/25 32/42 33/43 34/44 11/21 32/42
13/23
Kvaal [6] 1995, Norway.
100 PER 20-87 years
Stereomicroscope and Vernier calipers.
8.6 8.9 9.4 9.5 10 11 10.5 11.5 11.5
Bosman [20] 2005, Belgium.
197 OPG 19-75 years
Adobe Photoshop software 9.5 9.2 9.9 9.7 9.8 9.3 11.6 8.2 8.1
Paewinsky [19] * 2005, Germany.
168 OPG 14-81 Years
Hipax program 5.6
6.4
Avendano [18] 2009, Colombia
107 PER 21-50 years
Scion Image software
7.1
Shetty [15] 2010, India.
100 PER 20-70 years
SV- 4 mini slide viewer, digital Vernier calipers, stereomicroscope
10.5 10.2 11.8 11.5 12.4 11.8 12.7 13.3 11.8
Erbudak [29] 2012, Turkey.
123 OPG 14-57years
Image J software 10 10.1 8.7 8.82
Saxena**[40] 2011, India.
120 OPG 21-60 years
Autocad2005 software 3.63
Kanchan [35] 2012, India.
Group A, 47 PER 25-75 years
Adobe Photoshop software
12 12 12.4 12.7 13.2 11.8 13.3
13.2
Group B, 43 PER 25-77 years
11.9 11.2 12.4 11.1 13.4 12.6 13.4 13.8 12.7
Limdawala [22] 2013, India.
Group A, 100 PER 25-50 years
Kodak Dental Imaging Software 8.3 8.2 9
Group B, 50 PER 25-50 years
9.4 9.5 9.8
Misirlioglu [25] 2014, Turkey.
144 OPG 17-72 years
Easy-Dent PC software
5.8
7.3 7.5 6.9
Patil [69] 2014, India.
200 PER 20-50 years
Image-Pro Plus II software
6.5
Karkhanis [24] 2015, Australia.
200 OPG 20-62 years
Image J software 8.9 9.6 8.3 9.3 9.6 9.5 10.2 10.9 10.5
Mittal [27] 2016, India. 152 OPG 14-60 years Vistascan DBSWIN software 7.9 8.5 7.5 8.1 8.5 7.8 8.8 7.9 7.5
Rajpal [70] 2016, India 50 PER 15-57 years Kodak Dental Imaging Software 6.4 7.3 7.8
*Error reported as standard deviation. **Error reported as the difference between the chronological age and the estimated. PER=Periapical radiographs. OPG=Panoramic radiographs. Tooth numeration FDI
42
Table 1.5. The Cameriere et al. method: Studies included in the quantitative analysis.
*Error reported as mean absolute error (MAE), **Error reported as the module of the differences between the chronological and estimated age, ***Error reported as mean error, PER=Periapical radiographs. OPG=Panoramic radiographs. Tooth numeration FDI (Federation Dentaire International)
Study Sample Measuring instrument SEE ± years per tooth (FDI)
32/42 11/21 12/22 31/41 32/42 33/43 34/44 35/45 13/23
Cameriere et al. [7]* 2004, Italy.
100 OPG 18-72 years
AutoCAD2000
3.27
Cameriere et al. [37] 2009, Portugal and Italy.
229 PER 20-84 years
Adobe Photoshop
4.33
4.24
Babshed. [4] 2010, India.
178 PER 20-70 years
Adobe Photoshop AutoCAD 2004
10
10
Babshed et al. [50] 2011, India.
61 PER 21-71 years
Adobe Photoshop AutoCAD 2004
12.22
12.28 13.08 12.45
Jeevan. [39]* 2011, India.
228 PER 16-72 years
Adobe Photoshop
6.39
4.28
Zaher et al. [41] 2011, Egypt.
144 PER 12-60 years
AutoCAD2008
2.63 1.94
Cameriere et al. [42] 2012, Spain.
606 OPG 18-75 years
Adobe Photoshop
6.38 5.75
Cameriere et al. [46] Portugal. 2013
116 PER 18-74 years
Adobe Photoshop
7.03 6.64 10.8 10.9
Charis et al [43]* 2013, India.
120 PER 20-70 years
Jenoptic ProgRess Version ss2.7.
5.4
AC Azevedo [44]** 2014, Italy.
81 PER 19-74 years
Jenoptic ProgRess Version ss2.7.
3.05
Misirlioglu et al. [25] 2014, Turkey.
114 PER 17-72 years
Adobe Photoshop
6.75
Azevedo et al. [44] 2015, Brazil.
443 PER 20-78 years
Adobe Photoshop
6.41
5.79
43
Table 1.6. Volume calculation based methods.
Author Sample Image segmentation method Measuring instrument
Accuracy pert tooth (FDI)
Star et al. [55] 2011, Belgium.
111 CBCT 10-65 years
automatic segmentation (threshold), and manual correction
Simplant® 11/21 SD=12.8 13/23 SD=13.1 15/25 SD=8.4
Tardivo et al. [57] 2014, France.
210 CT 15-85 years
Semiautomatic Mimics® 13/23 MAE=3.4 33/43 MAE=4.6
De Angelis et al. [58] 2015, Italy.
91 CBCT 17-80 years
Manual Osirix software prediction interval = ±28 years
Pinchi et al. [59] 2015, Italy.
148 CBCT 10-80 years
cone shape approximation Osirix® software SEE=±11.45
CBCT: Cone beam computed tomography. SD: Standard deviation. MAE: Mean absolute error. SEE: Standard error of estimation. Tooth numeration FDI (Federation Dentaire International)
44
conclusions, it was necessary to analyse the possibility of author bias. This was determined
by the participation of the same authors in repeated publications. To this end, the results
were analysed comparing individual papers, and then grouping them per author.
Additionally, in certain cases where there were doubts about the origin of the sample,
which means the likelihood of finding different studies by the same authors that had used
the same sample, the authors were contacted to confirm the origin of the sample. In case
that two studies had the same sample, the authors were asked to suggest which study
should be included in the meta-analysis. Likewise, to deal with missing data, the authors
were contacted for more information. There was another possible source of bias observed
in this study: the use of non-specific population regression models and equations, which
could generate the wrong assumption on the accuracy of the analysed methods. To
overcome this problem, only studies using specific population formulae were used in the
quantitative analysis. However, there is not enough evidence to state that the production
of secondary dentine varies among individuals of different population.
RESULTS.
Kvaal et al. [6] (29 papers, 3254 participants)
Qualitative analysis
The original paper on the Kvaal et al. [6] method was published in 1995. Since then, this
method has been applied to a global sample of 3254 individuals, from 12 different
45
countries (Graph 1.1, Table 1.1). The initial methodology suggested the use of periapical
radiographs from six different teeth, using Vernier calipers to measure the maximum tooth
length, pulp length and root length, and a stereomicroscope with a measuring eyepiece to
the nearest 0.1mm, to measure pulp and root width at three different levels previously
described by Kvaal et al. [6].
Only a few studies have followed the original methodology, with slight adaptations [1, 6, 9,
15-18]. In 2005, this method was applied to panoramic radiographs [20], which became
more popular [20-34]. The use of digital imaging in dentistry also introduced the use of
different software to perform the odontometric measurements.
The most commonly used software programs are: Adobe Photoshop (different versions
n=5), Image J (n=4) and Kodak dental imaging software (n=2). From those studies that
tested the effect of sex on the accuracy of the age estimated: three found that sex does not
affect the models [15, 19, 30]; and two that it does [18, 23]. In the original study, sex was
included as a factor for the mandibular lateral incisor, indicating that pulp cavity size
changes occurred faster in males, as females need another 6 years to get the same age as
males for this tooth [6].
Quantitative analysis
From the total sample, only 16 papers met the inclusion criteria for the quantitative
analysis. (Table 1.4). The most accurate result (SD=5.6, r=-0.95) was obtained from
panoramic radiographs using the Hipax program (version 3.01) software, 168 participants
46
(77 female and 91 male) in a Caucasian group [19]. The largest error reported error was
SEE >13 years r2=0.1 [15, 35] obtained from the lower canine, following original Kvaal et al.
methodology on periapical radiographs [35] and the Adobe Photoshop 6.0 software in
panoramic radiographs [15].
Kvaal et al. measurements have been reported to have a high degree of intra and inter-
observer agreement indicating the reproducibility of the measurements, even in those
studies that did not follow the original methodology. Only one study reported significant
differences in the root length and pulp width at the level B and root width at the level A
measurement, although this study reported a SEE=±13.8 (r2=0.38), the average error of age
estimation was ±18-21 years using periapical radiographs. [35]
Note: The studies that did not meet the inclusion criteria for the quantitative analysis also
reported high intra and inter-observer agreement [31-33]. One study reported that the
lower lateral incisor produced lower intra-observer correlation [32], and one affirmed that
the use of a stereomicroscope improved the accuracy of the age estimates [9].
Cameriere et al. [7] (29 papers, 4167 participants)
Qualitative analysis
The original paper documenting the Cameriere et al. method [7] was published in 2004. In
the present systematic review, 29 papers using this method were studied, having a global
sample of 4167 individuals from 11 countries (Graph 1.2, Table 1.2). This method was
47
initially applied to digital panoramic radiographs, using (AutoCAD2000, Install Shield3.0,
1997) and different versions of this software have been used in 11 studies. The most used
software, to perform the pulp/tooth area measurements, was Adobe Photoshop (13
studies).
This method was designed to be applied to single rooted teeth, especially canines, but it
has also been tested in premolars, central, and lateral incisors. From those studies that
assessed the effect of sex on the regression models, the vast majority reported that sex
does not affect the regression model [4, 7, 25, 30, 36-45]. Only 4 studies reported that sex
affects the regression model [46-49].
Quantitative analysis
Twelve studies met the inclusion criteria for the quantitative analysis (Table 1.5). The use
of this method has a standard error of estimation (SEE) from±1.2 [41] to ±12-13years
(r=0.2-0.4) [50]. From these studies, two reported a median error <±5 years [7, 37], six
reported an error from ±5 to ±8.5 years [25, 39, 41-43, 45], and three studies reported an
error from ±10 to ±13 years [4, 46, 50]. From the studies included in the qualitative
analysis, only one reported significant intra-observer differences in lateral incisors and first
premolars (p<0.05) [50].
Note: All the studies that did not meet the inclusion criteria for the qualitative analysis and
that included intra and inter-observer calibration, reported high intra/inter-observer
agreement [36, 48, 51, 52].
48
Volume (16 papers, 2444 participants)
Qualitative analysis
Owing to the relatively few studies doing pulp/tooth volume reconstruction, in the
qualitative analysis those studies using extracted teeth were included. The first study doing
pulp/tooth volume reconstruction reported the use of micro-focus X-ray in 2004 [8]. In this
current systematic review, 16 studies used the pulp/tooth volume reconstruction, by
means of micro-focus computer tomography, CT scan or CBCT, and the use of different
software to do manual or semiautomatic volume reconstruction, such as Tri/3D Bon,
Mimics®, ITK-SNAP 2.4, Osirix, Amira among others, in a global sample of 2444 individuals
from 7 countries (Graph 1.3, Table 1.3).
However, the methodology used by some studies, required the use of extracted teeth [8,
12, 13, 53, 54]. With regard to the effect of sex on the regression models, nine studies
reported that sex has no effect [8, 14, 25, 53, 55-59]. Three reported that the models are
more accurate in females than in males, having a higher determination coefficient for
women than for men [12, 60, 61]. The comparative data are as follows: r2=0.6 for males
and r2=0.7 for females [12], or r2=0.29 for males and r2=0.15 for males [60], and r2=0.67 for
males and r2=0.75 for females when the mandibular central incisor is used, or r2=0.56 for
males and r2=0.58 for females when the second premolar is used.
Two studies, which reconstructed only the pulp cavity volume, also reported significant
differences between tooth type and sex [62, 63]. One of them found a significant
49
difference in the pulpal volume between both genders (p=0.028 <0.05), and a stronger
relation between pulp chamber and age for females (r2=0.6) than for males (r2=0.5) [62].
The other one reported a signifficant difference in volume between the two genders for 12
types of teeth (p=0.000) [63].
Quantitative analysis
Four studies meet the inclusion criteria for the quantitative analysis. The error of these
studies varies between ±3.47 years [57] to ±28 years [58]. A high intra-observer agreement
was reported [59]. Among those studies that did not meet the inclusion criteria for the
quantitative analysis, seven also reported high intra- and inter-observer agreement [8, 11-
14, 56, 62, 63].
DISCUSSION
Age estimation in adults is a challenge in all forensic investigations, especially in cases that
require the use of non-invasive methods. The formation of secondary dentine and the
resultant non-linear narrowing of the root canal with age [11], is one age predictor
measurable in dental radiographs and tomographs, leading to the proposal of different
methods for age estimation in adults as an alternative to more invasive methods, and as a
complement to osseous analysis [2, 16, 34, 64-67].
In the same way, many methods have been suggested for dental age estimation in adults.
Nevertheless, there are few available studies that compare their accuracy [68].
50
In the lack of a consensus on a uniformly applicable method for age estimation in adults,
the need to perform a systematic review was timely. This systematic review summarizes
and compares the results of some of the most used methods for dental age estimation in
adults.
In terms of the qualitative analysis, it has been reported that there are no significant
differences between right or left teeth [14, 56]. Another aspect to test among the different
papers was the effect of sex of the different methods. Although not all the included studies
assessed the effect of sex on age estimation, those that did (n=38), 71% (n=27) affirm that
sex has no statistically significant effect on age estimation, when pulp/tooth ratio is
calculated. However, if only pulp volume is measured and used as age indicator, there is a
significant difference between the accuracy for males and females [62, 63].
In the light of the above evidence one could suggest that ratio calculation not only
diminishes the effects of tooth magnification in dental radiographs, as reported by Kvaal [6]
et al., but also reduces the effect of sexual dimorphism related to tooth size. The age of
the participants is also another relevant aspect to include.
In this systematic review, those studies including participants under 14 years of age were
excluded for two main reasons. Firstly, there are other methods more reliable for aging
teenagers and infants, and secondly, before 14 years of age, not all the teeth have
completed the apex closure, which by definition, is a requirement for the formation of the
secondary dentine [76].
51
For the qualitative analysis, characteristics related to sample size and inclusion criteria
established in different studies were compared. As compared to previous efforts, no
significant correlation between sample size and the accuracy of the method was found,
when all the data were analysed together (r2=0.1, p-value <0.05, sample size of the
analysed studies n=50 to 604) or when the data were analysed individually for each
method.
It is necessary to highlight that from the studies included in this current analysis (n=30) only
4 (13.3%) had a sample smaller than 100 individuals (n=50 to 91 individuals), which may
suggest that in any study for age estimation the minimum sample should include data from
at least 100 participants, or over 100 teeth from different individuals in those studies using
only one tooth type. Some of the excluded studies, for the quantitative analysis, fail in this
aspect [55, 56, 60, 61], including data from several teeth of the same individual and
counting them as different samples, which may affect the reported results.
A previous study recommended a minimum of 120 participants in order to achieve 80% of
power and 5% of significance [30]. One almost universal inclusion criterion was the use of
only totally sound teeth. Only two studies did not follow this parameter, using teeth with
lesions to do volume calculations [54], or using panoramic radiographs that did not meet
the inclusion criteria suggested by Kvaal et al. [22]. Both studies found no significant effect
of these situations on the accuracy of the results.
52
Another aspect to consider is the description of the different methods, in terms of the
procedure to measure the different pulp/tooth dimensions, as well as the statistical
processing of the data. In certain cases, it was necessary to re-read the papers several
times to understand the proposed methodology and how the accuracy was reported.
In the quantitative analysis two main characteristics were compared among the studies:
repeatability of the measurements, in terms of intra and inter-observer agreement; and
their accuracy, reported as standard error of estimation (SEE), mean absolute error (MAE)
or standard deviation (SD). Due to this variation in the approach to evaluate and to report
the obtained accuracy, it was not possible to perform a deeper statistical analysis, as a
meta-analysis to confirm that one method was superior to another. However, in this
review the studies using pulp/tooth area ratio reported a lower error (table 1.4, 1.5 and
1.6).
All the studies reported significant intra- and inter-observer agreement, regardless of the
method and the measuring instrument, which suggests that after adequate training any of
these methods is reproducible. However, with regard to the simplicity of the technique,
and the access to the required tool to measure and calculate the respective pulp/tooth
ratio dimensions, Kvaal et al., and Cameriere et al. are more convenient.
By using periapical radiographs or panoramic radiographs, as the radiological technique
does not affect the accuracy of the measurements, as long as the quality of the image
53
allows the observer to clearly observe the boundaries of the root canal and tooth surface
[22].
The volumetric reconstruction of anatomic structures involves more technical and time-
consuming training as well as the use of more complex software. These factors could be
considered as obstacles for the larger scale application of some of these methods.
Likewise, the user spends more time doing the volumetric reconstruction per tooth, which
varies from 4 hours [8] to 15 minutes [60], when reported.
Another important aspect, with regard to the accuracy of the method, is the use of specific
population formulae, which has been believed to improve the results of the age estimates,
independently of the used method [14, 29, 41, 45, 63, 69]. As in those studies, using non-
specific population formulae the reported error was notably larger (error > ±20 years) [31,
32]. But the most recent findings about age mimicry, explained in Chapter 7, could reveal
that this assumtion is called into question [77].
The use of data from different populations in the same statistical analysis, to generate a
unique age estimation equation, is achievable [2, 20, 46]. Furthermore, it has been
reported that the pulp chamber size variation can be detected only each 10 years, which
opens a question about the reliability of those methods reporting a lower error.
In the specific analysis by the Kvaal et al. method, although requiring the inclusion of six
different single rooted teeth per idividual, the use of only one tooth [18], only upper
54
central incisor [69], canines [25], mandibular teeth [32], or different combinations of teeth
to apply the odontometric analysis described by Kvaal et al [24, 26], has also been
reported, with acceptable results (SEE < ±10 years).
It has also been reported that its accuracy depends on the quality of the image and on the
precision of the measurements [22]. Several studies reported that tooth length is not
strongly correlated with age [15, 17, 19, 22], as tooth length would depend on tooth wear,
bruxism, and food habits, rather than a physiological aging related process [15].
In regard to the Cameriere et al method, it only requires the use of one tooth, and the
majority of the studies report the use of canines. However, one study using three different
lower teeth (lateral incisor, canines, first premolars) found that lower canines had the
poorest correlation coefficient with age (r2=-0.2) [50]. Another study found more accurate
estimations from upper lateral incisors, claiming that the narrowing velocity in the pulp
chamber of this tooth is twice as fast as in lower incisors [46].
The Cameriere et al. method reported the lowest error (total average ±5.6 years), and a
sample of at least 120 individuals was reported as being adequate to obtain more accurate
age estimates [30].
The combined use of the Kvaal et al. width ratios and Cameriere area ratios has been
reported on canines measured from digital panoramic radiographs. More accurate age
estimates were achieved when the pulp/tooth width ratio at the mid-root level (i.e. half-
55
way between the enamel-cementum junction, and the apex of the root level) and
pulp/tooth area ratio were used together [30], or when the area ratio calculation from
canines is used individually [25].
In this systematic review the following advantages about the use of pulp/tooth area
calculation over other methods were noted: area measurements on digital radiographs
with different software are faster; and the most recent study using this method proposes
software for the automatic selection of pulp and tooth borders. These steps minimize the
time taken to obtain the area of tooth and pulp chamber, and reduce the error associated
with the observer, when performing the area selection [74].
Linear measurements can also be performed on digital radiographs, but, the observer
needs to take nine measurements per tooth, in six teeth, and calculate several ratios. In
the method using pulp/tooth area measurements, only one ratio needs to be calculated
and allows the researcher to develop the respective statistical regression model. In the
same way, the use of canines, especially upper canines, to calculate pulp/tooth area ratio
has certain advantages, as facilitated by their longer survival, less wear, and the larger size
of the pulp chamber in comparison with other teeth [58]. Also, as observed in table 1.5,
there are not only more studies reporting the use of upper canines for pulp/tooth area
calculations but also, these studies present acceptable accuracy.
This is in contrast to what was reported by Kvaal et al when doing pulp/tooth length/with
ratio calculations; they observed that upper canines had the lowest correlation with age,
56
when using dental radiographs of extracted teeth [76], which was an exclusion criterion, in
this current systematic review.
Finally, although the use of pulp/tooth volume ratio calculations from non-extracted teeth
still requires more research. The initial results of the analysis of pulp volume from
individuals of different age groups provide important and detailed information to
understand the formation of secondary dentine.
It has been reported that, the pulp/tooth volume ratios in the cervical area, were more
correlated with age, and that this correlation decreased towards the tooth apex [13]. Also,
that the most marked reduction in volume ratio was observed between the second and the
fifth decades of life in lower first and second premolars, and between the second and the
third decades of life in lower first premolars [13]. These clear findings may enlighten the
prospect of future and more accurate methods for age estimation in adults.
CONCLUSION
Narrowing of the root canal caused by the formation of secondary dentine is a well-
accepted age indicator in adults. This systematic review observed that age estimation
methods based on pulp/tooth area ratio calculation provided more accurate results, even
when one tooth is analysed per individual. However certain conditions need to be fulfilled:
a sample of minimum 120 individuals; older than 14 years of age; assessment of the
57
accuracy of the observer. The inclusion of data of individuals from different populations in
the same analysis is not discouraged.
Future studies for dental age estimation in adults, must consider the non-linear deposition
of secondary dentine through life in their statistical analysis, and also that the use of linear
regression models would generate the over-estimation of age in young individuals and the
under-estimation of age in older individuals [78]. This systematic review also recommends
the use of dental age estimation methods: firstly pulp/tooth area ratio calculation of single
rooted teeth: upper canines and other teeth (lower premolars, upper central incisors); and
secondly pulp/tooth length/with ratio calculation, following the methodology proposed by
Kvaal et al.
These factors need to be considered in combination with other methods that include
diverse age indicators to produce more reliable age estimates. The author of this
systematic review also recommends future studies to report their results in terms of
standard deviation, mean absolute error and standard error of estimation simultaneously.
Such a display of data will facilitate more meaningful meta-analyses in future reviews.
58
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SECTION TWO. Assessment of possible effect of orthodontic treatment on one of the
available methods for age estimation in adults: The Kvaal et al. method.
Preface
Section two answers one of the main aims of this thesis: the effect of external factors on
the accuracy of the Kvaal et al. method. This section presents two studies that tested this
method in individuals who had received orthodontic treatment. For chapter 2, the Kvaal et
al. method was tested on two different data sets: the first, collected from individuals that
had not received orthodontic treatment; and the second from individuals in whom
orthodontic treatment was completed.
Two sets of formulae to estimate the age of individuals were proposed: one for individuals
who did not receive orthodontic treatment; and the second for those who had received
orthodontic treatment; comparisons of the results were performed. It is necessary to
highlight that this is the first study that applies one age estimation method for adults, in
individuals whose dental conditions have been altered. This is in contrast to previous
studies that used data from individuals with sound teeth or who had not been exposed to
other dental procedures.
In Chapter 3, the statistical approach for the analysis of the data is innovative, as it follows
the design of epidemiological studies to assess risk factors. As in the study presented in
Chapter 2, it was observed that there was no statistically significant difference for the age
71
estimation from individuals with and without orthodontic treatment. Chapter 3 presents a
detailed analysis, at the tooth level, of the effect of orthodontic treatment on the accuracy
of the Kvaal et al. method testing formulae that were previously published for dental age
estimation in adults.
The chapters presented in this section share the methodological design with regards to the
inclusion and exclusion criteria of the participants: analyzed teeth, use of panoramic
radiographs, and measurements collection as follows:
Inclusion criteria
All subjects who had a recorded panoramic radiograph of high quality with respect to
factors of image brightness, contrast, and sharpness. In addition, all teeth included in the
analysis were clinically sound, with completed root formation, and at the occlusal plane
level.
Exclusion criteria
Any radiographs that did not meet the inclusion criteria, or had observable failings (Eg.
image distortion, poor contrast, overlap or superposition of tooth structure, or improper
positioning) were excluded. Teeth with rotations, incomplete root formation, dilacerations,
pulpal pathologies and endodontic treatment, and/or restorations were excluded. Teeth
with developmental abnormalities in size, shape and tooth structure, as well as previous
pulpal and periodontal pathologies, and endodontic treatment were excluded. Teeth with
72
large areas of enamel overlap between neighboring teeth were excluded in the studies that
are included in this section.
Teeth Selection
In accordance to Kvaal et al. [1], three single rooted upper teeth (with Federation Dentaire
International (FDI) notation 11/21, 12/22. 15/35) and three single rooted lower teeth (FDI
32/42, 33/43, 34/44) were measured. Kvaal et al. [1] reported that there no significant
differences between teeth from the left or the right side of the arch.
Consequently, in the absence of one of the teeth, the contralateral tooth was used, as long
as it met the inclusion criteria. In accordance with Karkhanis et al [2], panoramic
radiographs that presented any combination of the required teeth were included. Both
studies also shared the procedures to perform the measurements on digital panoramic
radiographs, the calibration of the observer, and the methods to test the measurement
precision as described below:
Measurements
All the panoramic radiographs were obtained in digital format, the measurements were
performed using Image J software (version 1.48 19 April 2014 - National Institute of Health,
USA). Following the methodology used by Kvaal et al. [1], the following measurements
were recorded: tooth, pulp and root length, as well as the pulp and tooth width at three
different levels: A (cemento-enamel junction in the mesial surface of the roots); B
(midpoint between the points A and C); and C (midpoint between the cemento-enamel
73
junction and root apex). After the collection of the figures in an Excel (2013) spreadsheet, a
series of ratios was calculated: (T) tooth/root lengths; (R) pulp/tooth length, (P) pulp/root
length, and root width/ pulp width ratio at levels A, B and C.
The ratio calculation and use, was proposed by Kvaal et al. [1] with the aim to reduce the
effect of magnification and angulation inherent in most radiographs [1, 3]. The different
mean values calculated with these ratios provided the age estimation predictors. M: mean
value all ratios, W: mean value width ratios B and C, L: mean value ratios P and R, W-L:
difference between W-L).
In Chapter 2, the predictors M and W-L were later used to formulate the age estimation
models by means of multiple regression analysis. In Chapter 3, the predictors M and W-L
were later used to estimate the age of all the participants, as established by Kvaal et al. [1].
The measurements were completed by a single observer (TYM). All data were collected
using Excel (version 2013 Microsoft Redmont, USA) and statistical analyses were completed
using the program R Core Team version 3.1.3 (2015). (R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL
http://www.R-project.org/).
Calibration
Intra and inter-observer calibration was estimated using five randomly selected panoramic
radiographs from the final study sample. These panoramic radiographs were measured on
five different days with at least one-day interval. With the aim to avoid the recall of the
measurements and landmarks, five new panoramic radiographs were also measured on
74
each occasion. Data were recorded using the software Image J by TYM and SK. To
determine intra-observer precision, three estimates of precision were calculated: the
technical error of measurement (TEM <1.0), relative technical error of measurement (rTEM
<5%) and coefficient of reliability was calculated to quantify the inter- and intra-observer
measurement error [4].
Measurement precision
After the estimation of intra- and inter-observer error, the obtained values were as follows:
intra-observer error: TEM <1.0 (0.92), rTEM<5% (2.99%) and R>0.75 (0.95). Inter-observer
error (between SK and TYM) was: TEM<1.0 (0.80), rTEM<5 (2.37) and R>0.75 (0.98)
showing comparable intra and inter-observer measurement precision; within acceptable
standards for all the measurements.
75
REFERENCES
1. Kvaal SI, Kolltveit KM, Thomsen IO, Solheim T. Age estimation of adults from
dental radiographs. Forensic Sci Int. 1995; 74:175-85.
2. Karkhanis S, Mack P, Franklin D. Age estimation standards for a Western
Australian population using the dental age estimation technique developed by
Kvaal et al. Forensic Sci Int. 2014;235:104.e1-.e6.
3. Kanchan-Talreja P, Acharya AB, Naikmasur VG. An assessment of the versatility
of Kvaal's method of adult dental age estimation in Indians. Arch Oral Biol.
2012;57:277-84.
4. Weinberg SM, Scott NM, Neiswanger K, Marazita ML. Intraobserver error
associated with measurements of the hand. Am J Hum Biol. 2005;17:368-71.
76
2. Chapter 2. Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment
This chapter was published as:
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment. European Journal of Forensic Science, Accepted for publication.
June 2016.
77
ABSTRACT
Objective: The aim of this cohort study was to evaluate if the side effects of orthodontic
treatment have any significant impact when the Kvaal et al. method is used for dental age
estimation. The objective was to observe the potential effects of orthodontic treatment on
the accuracy of the age estimation, as performed by using the Kvaal et al. standards when it
was applied on individuals before and after orthodontic treatment.
Methods: Following the methodological approach of Kvaal et al., odontometric
measurements were acquired and the data were statistically analyzed to develop age
estimation regression models. The total number of radiographs analyzed was 182 (64%,
n=58) female and 36% (n=33) male. The ages ranged from 12 to 50 years for females
(mean age 22 years), and 12 to 52 for males (mean age 22 years), before starting the
treatment. The average length of the treatment was 2.2 years for both females and males.
Results: The standard error of estimate (SEE) for the regression models did not change
dramatically for the pre- and post-treatment data.
Conclusions: It is recommended that similar analyses be performed for other methods of
dental age estimation, for example methods based on cone beam computer-tomography
or micro-focus computer tomography. These novel approaches, although more accurate,
are also potentially more sensitive to dental changes caused by orthodontic treatment.
Key words: Forensic sciences, dental age estimation, secondary dentine formation, adults,
orthodontic treatment, root resorption.
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INTRODUCTION
Kvaal et al. [1] developed a non-invasive method for the estimation of age in adults with
measurement of dimensions of the pulp chamber and tooth length to formulate regression
models for the estimation of age. Originally, this method was proposed to be used on
periapical radiographs. However, more recent work has focused on the use of the Kvaal et
al. [1] method in panoramic radiographs [2-4]. During tooth development, secondary
dentine deposition commences once the root formation is complete, and the tooth erupts
to the level of the occlusal plane [5].
Annually, the rate of secondary dentine formation has been documented to be 6.5 μm/year
for the crown, and 10 μm/year for the root [6]. The rate of secondary dentine formation, is
influenced by external stimuli such as occlusal forces, trauma and caries [7]. These external
factors also generate the production of tertiary dentine [5], which is indistinguishable from
secondary dentine on dental radiographs [8].
The estimation of dental age has been a valid tool in forensic and anthropological research
[1, 9, 10]. For younger persons, including newborns, infants and adolescents, there are
dental age estimation methods, generally based on tooth maturation, which are considered
the most accurate to estimate of chronological age in sub-adults [3, 11-13].
In adults, and once the root formation is deemed complete, methods for dental age
estimation are broadly based on the analysis of secondary dentine deposition and the
79
subsequent narrowing of the pulp chamber [1, 6, 14]. A potential confounding factor in the
estimation of dental age is the high incidence of orthodontic treatment in developed
countries [15]. The judicious application of forces is central to successful orthodontic
treatment and is well known to induce biological changes in dental hard tissues, including
the formation of secondary dentine [7] and root shortening [16]. The corollary being a
change in the dental morphological features analysed in the estimation of dental age in
adults [7, 17].
Given the potential of the development of tooth structure in adolescents and adult patients
to be influenced by the application of orthodontic forces, and these structures being the
foundation of age estimation methods, it is important to recognise and quantify such
influences. The first aim of this study was to evaluate if the side effects of orthodontic
treatment had any significant impact on dental age estimation when using the Kvaal et al.
[1] method. The objective of this study was also to observe the potential effects of
orthodontic treatment on the accuracy of age estimation, as performed by using the Kvaal
et al. [1] standards when applied to individuals before and after orthodontic treatment.
MATERIALS AND METHODS
Ethics approval was obtained from the Human Research Ethics Committee of The
University of Western Australia (Ref: RA/4/1/6797) prior to commencement. The design of
the study, data collection and analysis has been performed in accordance with the ethical
standards laid down in the 1964 Declaration of Helsinki.
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Sample
This cohort study consisted of a series of subjects who consecutively presented for
orthodontic treatment at a private specialist orthodontic clinic (SV). All panoramic
radiographs were acquired from the same machine and in digital format, with the informed
consent of the participants. All of the panoramic radiographs were unidentified, and the
only information known was the sex and age of the participants at the starting and finishing
time of the orthodontic treatment.
Sample population
This study analyzed a total of 182 pre-, and post-orthodontic treatment panoramic
radiographs from 91 participants, 64% (n=58) female and 36% (n=33) male, from a Western
Australian population. All participants presented for orthodontic treatment that, after
diagnosis and treatment planning, was completed with fixed appliances. The ages ranged
from 12 to 50 years for females (mean age 22) and 12 to 52 for males (mean age 22) before
starting the treatment. The average length of treatment was 2.2 years for both females
and males. Digital panoramic radiographs were taken as part of routine clinical orthodontic
treatment to evaluate the initial condition of the participants and the final treatment
results.
Statistical analysis
The strength of linear association between chronological age and the Kvaal et al. [1] dental
ratios was determined by Pearson correlation coefficient (r2). Following this stage,
regression analysis was applied to evaluate the relationship between the ratios and the
81
chronological age. The final results were later used to generate the statistical models for
age estimation. To quantify the predictive accuracy of the models, the standard error of
estimation (SEE) was used in the cross-validation sample. Multivariable linear regression
analyses were used to examine the association between the independent and outcome
variables. The outcome variables included chronological age (dependent variable), and the
predictors M and W-L (independent variables). Different equations were generated to
estimate the chronological age, by individual teeth and by groups of teeth, as follows:
Three maxillary teeth with M and W-L values (6 predictors) individually calculated for each
tooth, and the average of M and W-L for the same teeth (2 predictors).
Three mandibular teeth with M and W-L values (6 predictors) individually calculated for
each tooth, and the average of M and W-L for the same teeth (2 predictors). All six teeth,
with M and W-L values (12 predictors) individually calculated for each tooth, and the
average of M and W-L for the same teeth (2 predictors). All regression models were built
using the ordinary least squares approach. R-square values were computed to examine the
amount of variance explained by the predictor variables. The formula proposed by
Preoteasa et al. [18] was used to calculate the percentages of teeth with root shortening.
RESULTS
Age distribution
The age distribution before orthodontic treatment for females was: 12-19 years (62%,
n=36), 20-39 years (28%, n=16), >40 years (10%, n=6), and after treatment it was: 15-19
82
years (57%, n=33), 20-39 years (33%, n=19), >40 years (10%, n=6). For males, before
orthodontic treatment was: 12-19 years (52%, n=17), 20-39 years (42%, n=14), and >40
years (6%, n=2), and after orthodontic treatment it was: 13-19 years (48%, n=16), 20 to 39
years (45%, n=15) and >40 years (6%, n=2).
The correlation coefficient between chronological age and the dental ratios was calculated
for the data before and after orthodontic intervention (Table 2.1). In both cases, the
correlation coefficient related with the width ratios (A, B and C) were more significant than
those related with length (P, T, R and L). As established by Kvaal et al. [1], the predictors M
and W-L are required to be included in the final equation for dental age estimation. Based
on the Pearson correlation coefficients, it could be observed that after orthodontic
treatment, the significance of the values for the predictor W-L decreased.
Individual tooth regression models, and multiple teeth regression models, were proposed
for individuals that had not received orthodontic treatment (Tables 2.2 and 2.3
respectively), and for individuals after finishing the treatment (Table 2.3 and 2.4). In regard
to the models for age estimation using individual teeth, the SEE tends to increase after
orthodontic treatment, especially for the mandibular canine, where the increase was ±2
years. Furthermore, while the results for the SEE provided by the mandibular canine
showed a lower SEE (± 8.26 years) in the data analysis before treatment, the same tooth
showed the greatest value of SEE (±10.23 years) for individual tooth analysis, after
orthodontic treatment
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Table 2.1. Correlation coefficients before (1) and after orthodontic treatment (2).
Correlation coefficients between chronological age before(1) and after(2) starting orthodontic treatment and the Kvaal et al. [1] dental ratios (P: pulp length/root length, T: tooth length/root length, R: Pulp length/tooth length, A: pulp width/root width at level A, B: pulp width/root width at level B, C: pulp width/root width at level C) and predictors (M: mean value all ratios, W: mean value width ratios B and C, L: mean value ratios P and R, W-L: difference between W-L). p< 0.05* p<0.01** NS non-significant
ratio
Tooth number (FDI tooth numeration)
11/21 12/22 15/25 32/42 33/43 34/44
P1 0.15 0.07 -0.08 0.08 -0.08 0.2
P2 -0.26 -0.13 -0.06 -0.02 -0.22 -0.12
T1 0.03 0.03 -0.13 -0.18 -0.23 -0.11
T2 -0.16 -0.12 -0.14 -0.09 -0.08 -0.15
R1 0.16 0.04 0.07 0.32* 0.17 0.38**
R2 -0.09 -0.01 0.13 0.07 -0.14 0.03
A1 -0.44** -0.41** -0.42** -0.41** -0.32** -0.16
A2 -0.31* -0.38** -0.47** -0.17 -0.21 -0.19
B1 -0.43** -0.41** 0.02 -0.21* -0.62** -0.59**
B2 -0.44** -0.49** -0.44** -0.22* -0.48** -0.52**
C1 -0.34** -0.34* -0.32* -0.18 -0.51** -0.45**
C2 -0.34** -0.43** -0.36* -0.32* -0.33* -0.43**
M1 -0.13 -0.33* -0.28* -0.19 -0.56** -0.37**
M2 -0.31* -0.40** -0.41** -0.22* -0.38 -0.44**
W1 -0.44** -0.41** -0.14 -0.23* -0.52** -0.57**
W2 -0.45** -0.51** -0.46** -0.29* -0.43** -0.52**
L1 0.18 0.07 -0.13 0.19 0.01 0.33
L2 -0.22* -0.11 -0.14 0.01 -0.21 -0.07
W-L1 -0.36 -0.32 0.02 -0.32* -0.48** -0.57**
W-L2 -0.01 -0.23* -0.05 -0.22* -0.26* -0.41**
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Table 2.2. Multiple regressions for estimation of chronological age (in years) for
individual maxillary and mandibular teeth in subjects before (1) and after (2)
orthodontic treatment
Teeth FDI n R R2 Equation SEE ± years
11/21(1) 83 0.22 0.21 Age= 39.87-76.79(M) -51.75(W-L) 8.57
11/21(2) 83 0.14 0.12 Age= 54.50-73.67(M)-30.64(W-L) 9.06
12/22(1) 81 0.18 0.16 Age= 68.21-99.54(M) -33.52 (W-L) 8.92
12/22(2) 81 0.25 0.23 Age= 83.07-128.42(M)-42.68(W-L) 8.48
15/25(1) 58 0.08 0.04 Age= 79.8105-81.5881(M)-0.5444(W-L) 9.99
15/25(2) 58 0.21 0.18 Age= 90.22-129.66(M)-18.62(W-L) 9.29
32/42(1) 87 0.12 0.10 Age= 15.40-37.51(M)-43.05(W-L) 9.73
32/42(2) 87 0.09 0.74 Age= 49.10-77.55(M)-37.65(W-L) 9.89
33/43(1) 63 0.47 0.45 Age= 111.80-238.35(M)-132.7(W-L) 8.26
33/43(2) 63 0.19 0.16 Age= 76.60-159.75(M)-105.79(W-L) 10.26
34/44(1) 68 0.35 0.33 Age= 21.67-69.84(M)-69.59(W-L) 8.40
34/44(2) 68 0.31 0.29 73.52-137.96(M)-64.43(W-L) 8.71
R2, coefficient of determination. Standard error of estimation (SEE) in years. M: mean value all ratios, W: mean value width ratios B and C, L: mean value ratios P and R, W-L: difference between W-L.
85
Table 2.3. Multiple regressions for estimation of chronological age (in years) for the combination of different teeth before orthodon tic
treatment
Teeth N R R2 Equation (FDI tooth numeration) SEE ± years
3 max 2 pds 50 0.27 0.24 Age= 80.40- 145.51(M) -47.69 (W-L) 7.78
3 max 6 pds 50 0.31 0.21 Age= 63.704 - 6.412 (11/21M) - 17.216 (11/21W-L) - 32.812 (12/22M)-19.332 (12/22W-L) - 77.969 (15/25M) + 10.594 (15/25W-L)
7.93
3 mdb 2 pds 46 0.4 0.37 Age= 13.11-36.64 (M) - 19.83 (W-L) 9.12
3 mdb 6 pds 46 0.6 0.54 Age= 124.528 + 81.230 (32/42M) - 7.784 (32/42W-L) - 328.184 (33/43M) - 121.021 (33/43W-L) - 37.503 (34/44M) - 9.855(34/44W-L)
7.8
6 teeth 2 pds 36 0.45 0.41 Age = 133.86 - 238.98 (M) - 67.88 (W-L) 7.6
6 teeth 12 pds 36 0.72 0.58 Age = 130.727 + 15.058 (11/21M) + 23.906 (11/21W-L) + 61.249 (12/22M) - 29.091 (12/22W-L) - 100.481 (15/25M) - 2.441 (15/25W-L) + 54.517 (32/42M) + 3.089 (32/42W-L) - 268.438 (33/43M) - 89.805 (33/43W-L) - 41.009 (34/44M) - 25.32 (34/44W-L)
6.3
R2, coefficient of determination. Standard error of estimation (SEE) in years. M: mean value all ratios, W: mean value width ratios B and C, L: mean value ratios P and R, W-L: difference between W-L. Age predictors (pds). Maxillary teeth (max). Mandibular teeth (mdb).
86
Table 2.4. Multiple regressions for estimation of chronological age (in years) for the combination of different teeth after orthodontic
treatment
Teeth n R R2 Equation (FDI tooth numeration) SEE ± years
3 max 2 pds 50 0.38 0.36 Age= 102.46 -102.16(M) -63.13(W-L) 7.21
3 max 6 pds 50 0.42 0.34 Age= 114.631 - 0.876 (11/21M) + 2.218 (11/21 W-L) + -115.748 (12/22M) - 38.699 (12/22W-L) - 91.406 (15/25M) -20.963(15/25W-L)
7.31
3 mdb 2 pds 46 0.33 0.30 Age=98.68-213.10 (M) - 105.05 (W-L) 9.63
3 mdb 6 pds 46 0.44 0.36 Age= 42.761 + 81.109 (32/42M) + 1.905 (32/42W-L) - 111.346 (33/43M) - 173.252(33/43W-L) - 151.769 (34/44M) - 43.162 (34/44W-L)
9.23
6 teeth 2 pds 36 0.49 0.46 Age = 174.12 -288.42 (M) -59.22 (W-L) 7.37
6 teeth 12 pds 36 0.6 0.39 Age= 154.569+9.383(11/21M) + 19.718 (11/21W-L)-70.675 (12/22M)-39.284(12/22W-L)-39.932(15/25M) - 4.881 (15/25W-L)+47.114 (32/42M)-17.071 (32/42W-L)-58.568 (33/43M) -29.183 (33/43W-L) -149.635(34/44M)-0.842 (34/44W-L)
7.8
R2, coefficient of determination. Standard error of estimation (SEE) in years. M: mean value all ratios, W: mean value width ratios B and C, L: mean value ratios P and R, W-L: difference between W-L. Age predictors (pds). Maxillary teeth (max). Mandibular teeth (mdb).
87
When multiple regression models were formulated using different combinations of teeth, it
is also noticeable that in a few cases the SEE decreased after orthodontic treatment:
maxillary lateral incisor (±0.437), maxillary first premolar (±0.698), the multiple tooth
regression models using three maxillary teeth with two (±0.574) and six (±0.613)
predictors, and in the multiple regression models using six teeth and two predictors
(±0.237): In both circumstances, the multiple regression models using the different teeth
combinations improved the accuracy of estimation of chronological age, consistent with
previous studies [2].
Root shortening was detected in in 62% of the upper central incisors, 53% of upper lateral
incisors, 48% of upper second premolars, 48% of lower lateral incisors, 50% of lower canine
and 51% of lower second premolars, with a formula previously proposed [18].
DISCUSSION
This is the first study specifically designed to apply the Kvaal et al. [1] method to a group of
orthodontically treated subjects. Also, the first study evaluating the impact of the side
effects of orthodontic treatment on one of the proposed methods for dental age
estimation in adults based on the formation of secondary dentine and the pulp/tooth
dimension ratios.
Previous investigations failed to disclose whether subjects had previously received
orthodontic treatment. There are well known biological changes that occur secondarily to
88
the application of orthodontic forces, including apical root resorption and secondary
dentine formation.
External root resorption is one unavoidable, unpredictable, and undesirable sequela [19-
21] of orthodontic treatment. The reported frequency of external root resorption is about
100% when it is examined under microscopy. When it is quantified on periapical or
panoramic radiographs, the frequency falls to 70%, with a mean reported value of root
shortening of 1.42 ±0.44mm, and 1% to 5% of the cases with a loss of 4mm or one third of
root length [18].
In addition, maxillary teeth are more sensitive than mandibular teeth to root resorption.
The most frequently affected teeth, according to severity, are the maxillary laterals,
maxillary centrals, mandibular incisors, the distal root of mandibular first molars, second
premolars, and maxillary second premolars [20, 22], and all these teeth have been used in
different methods for dental age estimation in adults [1, 2, 23]. In this study, a higher
percentage of root resorption for upper teeth was also observed.
Confirming the findings of Karkhanis et al. [2], the length ratios (P, T, R, and L ratios) in this
study have a non-significant correlation coefficient with age, (p>0.05). Furthermore, the
percentage of negative correlation coefficients (Table 2.1), closer to -1, is higher in the
observed values after orthodontic treatment (23% before vs 66% after).
89
As the Kvaal et al. [1] method is based on the negative correlation between age and the
above-mentioned ratios, it is possible to observe that after orthodontic treatment this
negative correlation is more evident, but not statistically significant. In this study, there
were no significant variations in the correlation coefficients of the calculated length ratios
with age among the different teeth. Furthermore, as the Kvaal et al. [1] method is based
on length ratio calculations, not the linear measurements per se, it is possible that the
effect of root shortening on the estimated ages had been diminished when the ratios are
calculated.
In terms of secondary dentine formation due to orthodontic treatment (a phenomenon
that has not been as widely investigated as root resorption), there are reports of complete
obliteration of the canals in maxillary incisors [24]. In one study analysing the tooth
changes in terms of root length and pulp chamber within maxillary central incisors (tooth
11 and 21), statistically significant changes in the width of the pulp chamber at the
midpoint of the dental root [25] were found, equivalent to the point C in the Kvaal et al. [1]
method.
Another study, using cone beam computer tomography in maxillary teeth, found a
statistically significant difference between the volumes before and after orthodontic
treatment, with the highest mean volume loss observed in the upper left lateral incisor
(3.86 mm3), and the least for the upper right central incisor (3.04 mm3) [7].
90
In this study, the correlation coefficients of the pulp/root width ratios (A, B, C, and W)
maintained their negative correlation with age before and after the treatment, without
showing the same variation observed for the length ratios. It would still be necessary to
assess if the root shortening after orthodontic treatment, displaced the location of the
reference points B and C towards the crown (where the pulp chamber is wider), and its
relationship with the observed variation of the SEE before and after orthodontic treatment,
which in both cases is acceptable in forensic terms (SEE=± 10 years).
CONCLUSION
This current investigation demonstrated an alteration in tooth and pulp chamber
morphology and dimensions following orthodontic treatment. However, these changes did
not serve to significantly influence the validity and accuracy (SEE) of the Kvaal et al. [1]
method when applied in the assessment of panoramic radiographs to estimate
chronological age. Furthermore, it is not possible to affirm that the instrument used, the
dental panoramic is sensitive enough to detect such small changes in the pulp chamber
dimensions. It is recommended that further analysis of other methods for dental age
estimation in adults based on the formation of secondary dentine, such as developed by
Cameriere et al. [3], or the more recently proposed methods based on volumetric
reconstructions of the tooth and pulp chamber in CBCT [26, 27], which could be more
susceptible to be affected by orthodontic treatment sequels.
91
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intrusive and extrusive orthodontic forces. J Oral Sci. 2009;51(1):109-15.
18. Preoteasa CT, Ionescu E, Preoteasa E, Tenreiro Machado JA, Baleanu MC,
Baleanu D. Multidimensional Scaling for Orthodontic Root Resorption. Math
Probl Eng. 2013;2013;1-6.
19. Ponder SN, Benavides E, Kapila S, Hatch NE. Quantification of external root
resorption by low- vs high-resolution cone-beam computed tomography and
periapical radiography: A volumetric and linear analysis. Am J Orthod
Dentofacial Orthop. 2013;143(1):77-91.
20. Campos MJ, Silva KS, Gravina MA, Fraga MR, Vitral RWF. Apical root resorption:
The dark side of the root. Am J Orthod Dentofacial Orthop. 2013;143(4):492-8.
21. Harris DA, Jones AS, Darendeliler MA. Physical properties of root cementum:
Part 8. Volumetric analysis of root resorption craters after application of
controlled intrusive light and heavy orthodontic forces: A microcomputed
tomography scan study. Am J Orthod Dentofacial Orthop. 2006;130(5):639-47.
22. Brezniak N, Wasserstein A. Root resorption after orthodontic treatment: Part 2.
Literature review. Am J Orthod Dentofacial Orthop. 1993;103(2):138-46.
23. Mathew DG, Rajesh S, Koshi E, Priya LE, Nair AS, Mohan A. Adult forensic age
estimation using mandibular first molar radiographs: A novel technique. J
Forensic Dent Sci. 2013;5(1):56-9.
94
24. Delivanis HP, Sauer GJR. Incidence of canal calcification in the orthodontic
patient. Am J Orthod. 1982;82(1):58-61.
25. Tobón D, Aristizabal D, Álvarez C, Urrea J. Cambios radiculares en pacientes
tratados ortodoncicamente. (Spanish). Root changes in patients treated
orthodontically (English). CES Odontol. 2014;27(2):37-46.
26. Ge ZP, Ma Rh, Li G, Zhang JZ, Ma XC. Age estimation based on pulp chamber
volume of first molars from cone-beam computed tomography images. Forensic
Sci Int. 2015;253:133.e1-7.
27. Sakuma A, Saitoh H, Suzuki Y, Makino Y, Inokuchi G, Hayakawa M, et al. Age
Estimation Based on Pulp Cavity to Tooth Volume Ratio Using Postmortem
Computed Tomography Images. J Forensic Sci. 2013;58(6):1531-5.
95
3. Chapter 3. Orthodontic treatment: Real risk for dental age estimation in adults?
This chapter was published as:
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Orthodontic Treatment: Real Risk for Dental Age Estimation in Adults?
Journal of Forensic Science. Accepted for publication. October 2016.
96
ABSTRACT
Dental age estimation becomes a challenge once the root formation has finished. In living
adults, the most commonly used methods are based on the formation of secondary
dentine. One of the side effects of orthodontic treatment is the formation of secondary
dentine and root shortening.
The aim of this study was to establish if the secondary effects of orthodontic treatment
generate a statistically significant difference in dental age estimations. The study sample
included 34 pairs of pre- and post-orthodontic treatment panoramic radiographs, from
different individuals with exactly the same age and sex distribution. Females (n=22, 65%)
age range 15-50 years old, median 17.5, and males (n=12, 35%) age range 16-37 years old,
median 22.5 were included.
After data collection, dental age was estimated per tooth using formulae previously
published. The risk of obtaining over-estimation of age was calculated (RR=1.007). The
changes caused by orthodontic treatment do not have any significant effect on age
estimation when the Kvaal et al method is applied on panoramic radiographs.
Key words: Forensic science, dental age estimation, secondary dentine formation, adults,
orthodontic treatment, root resorption.
97
INTRODUCTION
The analysis of teeth for age estimation has been scientifically reported since the early
1800s [1]. Methods based on tooth formation in juveniles have shown high reliability [2-4].
Once the root formation has finished, (generally at the age of 14 years) [5], dental age
estimation becomes a challenge, partly as a result of third molar formation variability [6].
The most reported non-invasive methods for dental age estimation are based on the
formation of secondary dentine and the decrease of pulp chamber dimensions.
These features are measurable in periapical radiographs [7, 8], panoramic radiographs [9,
10], micro-focus computed tomography [11], computed tomography [12], and cone beam
computed tomography [13]. These methods proposed different formulae to be used in
specific populations. An important characteristic of these studies is that in their analysis,
they included only totally sound teeth.
It is well known that orthodontic forces generate irreversible changes on tooth structure,
such as root shortening [14], and secondary dentine formation [15]. These two biological
changes in tooth structure may directly affect the features used for dental age estimation
in adults, especially the method proposed by Kvaal et al. [7].
This method is based on the measurement of tooth/pulp length, root canal and root width
at different levels, followed by ratio calculations and linear regression analysis for dental
age estimation. It would be expected that with the mentioned changes, secondary to
98
orthodontic treatment, age estimation in participants post orthodontic treatment, would
show a higher estimation error and higher overestimation, compared to that of non-
treated participants. If that were to be the case, it would be necessary to develop specific
standards for orthodontically treated participants, not only for the Kvaal et al. [7] method,
but for any method based on secondary dentine formation and the variation of pulp/tooth
dimensions with age.
In the event of the results being different to the expected, it would mean that the Kvaal et
al. method could be used despite the evidence of anatomic changes related to orthodontic
treatment. The aim of this study was to establish if orthodontic treatment could generate
changes in dental age estimations at the tooth level when the Kvaal et al. [7] method is
applied per individual tooth.
MATERIALS AND METHODS
Ethics approval was obtained from the Human Research Ethics Committee of The
University of Western Australia (Ref: RA/4/1/6797) prior to commencement.
Panoramic radiographs, orthodontics, and dental age estimation
Initially, the Kvaal et al. [7] method was proposed to be used on periapical radiographs.
However, recent studies have also applied this method on panoramic radiographs [9, 10].
Panoramic radiographs have more image distortion than periapical radiographs, but it has
been reported that when root resorption associated with orthodontic treatment is
99
measured on panoramic radiographs, it is significantly higher than when measured on
periapical radiographs [16].
This is the first study to see the effect of orthodontic related changes on age estimation
therefore, no power calculation was achievable. However, based on the size of previous
research assessing pulpal changes associated to orthodontic treatment [17], a sample size
in a similar range was deemed appropriate.
Sample Selection
The study cohort consisted of a series of participants who consecutively presented for
orthodontic treatment at a private specialist orthodontic clinic (SV). The initial sample for
this study was 91 participants, who had a pre, and post-treatment panoramic radiographs
from a Western Australia population. From the initial sample, a total of 34 pre-, and 34
post-orthodontic treatment panoramic radiographs, were selected, resulting in a final
sample of 34 pairs of panoramic radiographs (n=68).
Sample size reduction corresponded to the need of age and sex matching between the
different individuals in each pair, one of them without orthodontic treatment and the other
one with a concluded treatment. Females 65% (n=22, for both groups), age range 15-50
years old, median 17.5. Males 35% (n=12, for both groups) age range 16-37 years old,
median 22.5. The minimum length treatment was 1.2 years, the maximum 3.6 years,
median 2.1 years.
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Special characteristics of this study
The purpose of this study was to assess the biologic variation effects of orthodontic
treatment at the tooth level. Therefore, the tooth-by-tooth formulae for the Kvaal method
were applied. [10, 18]. Measurements were taken before categorizing the sample into two
groups: pre for panoramic radiographs obtained from non-treated participants, and post
for treated participants, in order to avoid observation bias.
Statistical analysis
After the completion of the measurements, dental age estimation was calculated using the
age estimation equations from individual teeth. In participants 30 years or older the
equations used were those reported by Karkhanis et al. [10]. And for participants 29 years
or younger, the equations used were obtained from a different group of non-treated
participants (n=74 aged 12-28 years). Both set of equations were obtained from a Western
Australian population. Then, the respective analysis for risk assessment was performed.
RESULTS.
After age estimation per individual tooth, there was a total of 189 age estimates for group
pre, and 196 estimates for group post. The age estimates obtained were then compared
between participants with exactly the same age and sex in group pre, and group post. In
this way 183 pairs of age estimates were obtained and compared 1 to 1. For 79% (n=145)
of the total observations, the fluctuation of the data was the same, regardless if there was
101
over or under estimation of the age. In terms of over-estimation, in 47% of these
observations, the over estimation was higher after the orthodontic treatment.
Although the fluctuation of the data was the same in groups, pre-and post, there was a
clear difference between the ages. Before the age of 25, the large majority of results
showed a slight over estimation of age which did not exceed the reported SEE. In contrast,
the majority of age estimation data obtained from older participants showed under
estimation of the age that notably exceeded the reported SEE.
A contingency table (Table 3.1) was developed to test if the secondary effects of
orthodontic treatment were a real risk to produce over-estimation of the age when the
Kvaal et al. method is applied. The relative risk calculated was RR=1.0071 (Low risk).
The fluctuation of the data in regard to the chronological current age of the individual was
analyzed per individual tooth (Table 3.2), showing that there was not a significant
difference in the percentages of over estimation and under estimation between both
groups (Pearson correlation coefficient=0.78).
Although the fluctuation of the data was the same in groups, pre-and post, there was a
clear difference between the ages. Before the age of 25, the large majority of results
showed a slight over estimation of age which did not exceed the reported SEE. In contrast,
the majority of age estimation data obtained from older participants showed under
estimation of the age that notably exceeded the reported SEE.
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Table 3.1. Contingency table to estimate if orthodontic treatment was a causal of
overestimation, when the Kvaal et al. method is used to age estimation.
Orthodontic treatment Over-estimation Under-estimation TOTAL
YES
Post-treatment
48%
n=94
52%
n=102 n=196
No
Pre-treatment
48%
n=184
52%
n=99 n=189
TOTAL n=184 n=201 n=385
Incidence over-estimation group A=47.9%. Incidence under-estimation group B=47.6%. Relative risk of presenting overestimation owed to orthodontic treatment secondary effects when Kvaal et al. method is used for dental age estimation: RR=1.0071 (No or low risk).
103
Table 3.2. Comparison of over- and under-estimates obtained per tooth
TOOTH (FDI) 11/21 12/22 15/25 32/42 33/43 34/44 O
VER
ES
TIM
ATI
ON
Pre-treatment 39%
(n=13)
50%
(n=)16
52%
(n=17)
47%
(n=16)
54%
(n=13)
47%
(n=15)
Post-treatment 38%
(n=13)
45%
(n=15)
48%
(n=16)
44%
(n=15)
61%
(n=20)
52%
(n=15)
UN
DER
ES
TIM
ATI
ON
Pre-treatment 61%
(n=20)
50%
(n=16)
48%
(n=16)
53%
(n=18)
46%
(n=11)
53%
(n=17)
Post-treatment 62%
(n=21)
55%
(n=18)
52%
(n=17)
56%
(n=19)
39%
(n=13)
48%
(n=14)
SEE ± years (<30 years) 4.3 4.2 4.5 4.4 3.7 3.7
SEE ± years (> 30 years) 9.3 9.6 9.5 10.2 10.9 10.5
Reported standard estimation error (SEE) per individual tooth, before and after orthodontic treatment, for participants younger than 30 years (<30 years) and over 30 years of age (> 30 years).
104
DISCUSSION
The reliability of dental age estimation in adults, based on the formation of secondary
dentine, have shown superior accuracy to other methods, based on the analysis of other
age related dental or osseous changes [8, 10]. However, teeth are subjected to different
changes through life, related with pathology, biological, chemical, or mechanical trauma or
dental procedures.
It has been reported that orthodontic treatment causes mechanical trauma to the
periodontal ligament and induces pulpal reactions [20]. The most frequently reported side
effect is external root resorption, a process characterized by the destruction of root
structure [20], with the subsequent diminution of root length (mean reported value of 1.42
±0.44mm) [21].
Another side effect is the reduction of pulp chamber dimensions, owed to secondary
dentine formation [15]. With these changes, it was expected to obtain significant
differences between group pre, and post, with higher percentages of over estimates of age
in treated participants.
Analysis of the obtained data facilitated the calculation of the potential risk of having over
estimation in participants after finishing the orthodontic treatment (Table 3.1). After
calculating the incidence of overestimation in groups pre, and post, there was no evidence
of association between over-estimation of age and orthodontic treatment (RR=1.0071).
105
However, it is necessary to mention that in this study none of the tested teeth showed
signs of severe apical root resorption.
Previous studies have found that, maxillary teeth are more affected by root shortening due
to orthodontic treatment, especially, lateral and central incisors [22, 23]. In this study, they
also presented the higher percentage of underestimates of age for both groups, followed
by the mandibular lateral incisor. In the case of under estimation, it was observed in a
higher percentage in lower canines for group pre, and group post, 54% and 61%
respectively.
Previous studies using the Kvaal et al. method and their proposed formulae, reported a
constant under-estimation of age, from 18 to 20 years [19] up to 47.10 years [24]. These
studies did not use population specific formulae. In this study, the formulae used were
obtained from the same Western Australian population. There was a clear cutline (24 years
for both groups) where the estimates would notably exceed the reported SEE (1 to 5
years), having statistically significant under estimates.
It is necessary to determine in future studies if this finding could be related to the fact that
the apposition of secondary dentine does not occur in a linear manner through life [24],
causing a larger decrease of pulp dimensions between 20 to 40 years of age, than between
40 to 60 years of age [25]. A limiting factor to clearly examine this relation in the current
study was the lack of individual over 40 years of age.
106
As the main objective of this study was to establish if orthodontic treatment would
generate changes in dental age estimation, and as different teeth are affected with
different severity degrees, in this study previously published formulae were used for dental
age estimation for individual teeth rather than per set of teeth or per individual.
The use of the Kvaal et al [7] individual teeth formulae to estimate dental age has been
reported on extracted teeth [26]. In the same way, there are other methods based on the
assessment of a single tooth per individual to generate dental age estimation models with
acceptable results in a forensic framework [5, 7, 13].
CONCLUSION.
In this current study, orthodontic treatment did not affect the final results when the Kvaal
et al. method was used for dental age estimation. Although it has been previously
established that, to use the pulp complex as a biomarker for general ageing, the analysed
teeth have to fulfil the requirements of being in normal and functional occlusion, totally
sound and free from dental procedures [7], the real effect of different dental conditions on
methods based on the formation of secondary dentine, for dental age estimation, has not
been tested. The results of this current study allow forensic dentists to use the Kvaal et al
method in participants who have had previous orthodontic treatment, when there are no
signs of severe apical root resorption.
107
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11. Vandevoort FM, Bergmans L, Van Cleynenbreugel J, Bielen DJ, Lambrechts P,
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14. Baumrind S, Korn EL, Boyd RL. Apical root resorption in orthodontically treated
adults. Am J Orthod Dentofacial Orthop. 1996;110(3):311-20.
15. Venkatesh S, Ajmera S, Ganeshkar SV. Volumetric Pulp Changes after
Orthodontic Treatment Determined by Cone-beam Computed Tomography. J
Endod. 2014;40(11):1758-63.
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16. Sameshima G. Asgarifar K. Assessment of root resorption and root shape:
periapical vs panoramic films. Angle Orthod. 2001;71(3):185-189
17. Lazzaretti, Bortoluzzi, Torres Fernandes, Rodriguez, Grehs, and Martins
Hartmann. Histologic Evaluation of Human Pulp Tissue after Orthodontic
Intrusion. J Endod.2014;40(10):1537-540.
18. Marroquin TY, Karkhanis S, Kvaal SI, Vasudavan S, Castelblanco E, Kruger E,
Tennant M. Determining the effectiveness of adult measures of standardised
age estimation on juveniles in a Western Australian population. Aust J Forensic
S. 2016 May 22:1-9.
19. Kanchan-Talreja P, Acharya AB, Naikmasur VG. An assessment of the versatility
of Kvaal's method of adult dental age estimation in Indians. Arch Oral Biol.
2012;57(3):277-84.
20. Krishnan V, Davidovitch Ze. Cellular, molecular, and tissue-level reactions to
orthodontic force. Am J Orthod Dentofacial Orthop. 2006;129(4):469.e1-.e32.
21. Preoteasa CT, Ionescu E, Preoteasa E, Tenreiro Machado JA, Baleanu MC,
Baleanu D. Multidimensional Scaling for Orthodontic Root Resorption. Math
Prob Eng. 2013;2013.
22. Brezniak N, Wasserstein A. Root resorption after orthodontic treatment: Part 2.
Literature review. Am J Orthod Dentofacial Orthop. 1993;103(2):138-46.
110
23. Silva Campos MJ, Silva KS, Gravina MA, Fraga MR, Vitral RWF. Apical root
resorption: The dark side of the root. Am J Orthod Dentofacial Orthop.
2013;143(4):492-8.
24. Meinl A, Tangl S, Pernicka E, Fenes C, Watzek G. On the applicability of
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Forensic Sci. 2007;52(2):438-41.
25. Oi T, Saka H, Ide Y. Three-dimensional observation of pulp cavities in the
maxillary first premolar tooth using micro-CT. Int Endod J. 2004;37(1):46-51.
26. Willems G, Moulin-Romsee C, Solheim T. Non-destructive dental-age calculation
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126:221-226
111
SECTION THREE: New uses of the Kvaal et al method for age estimation in young individuals
and adults from different groups of population.
Preface
The studies presented in this section explore the use of the Kvaal et al method in two new
scenarios. In Chapter 4, this method is applied on a sample that contains data from
panoramic radiographs of young individuals (14 to 30 years of age) from a Western
Australian Population. The objective was to address one of the issues faced by forensic
dentists: individuals that present agenesis of third molars, which limits the use of methods
based on tooth formation.
Chapter 5 presents a new proposal to implement the Kvaal et al method on computed
tomography (CT) and cone beam computer tomography (CBCT). It also explores the
pulp/tooth width ratio calculation not only in the coronal view of the tooth, observable in
dental radiographs, but also in the sagittal view, which is only observable with this last
imaging techniques. Simultaneously, in this chapter, one of the controversies, or previously
stated principles of dental age estimation (that only sound teeth should be used), was
tested by the use of teeth with a variety of different conditions.
112
4. Chapter 4. Determining the effectiveness of adult measures of standardized age
estimation on juveniles in a Western Australian population.
This chapter was published as:
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Determining the effectiveness of adult measures of standardised age
estimation on juveniles in a Western Australian population. Australian Journal of Forensic
Sciences. Accepted for publication. March 2016.
113
ABSTRACT
The estimation of chronological age through assessment of dental radiographs is well-
established and a useful method to assist in the identification of persons in forensic and
anthropological scenarios.
The objective of this investigation was twofold: i) to validate the Kvaal et al. age-estimation
method on a sample of Western Australian subjects, and ii) to increase the range of
chronological ages to which the Kvaal et al. method can be applied. The sample size
included panoramic radiographs from 74 subjects (aged 12-28 years).
A set of ratios was calculated and then used to apply different statistical models of linear
regression, to generate a final formula to estimate age. The most accurate estimations
were obtained from the models generated by the mandibular canine measurement (SEE
±3.708 years), and for the 3 mandibular teeth (SEE ±3.388 years). The results indicate that
inclusion of juveniles did not affect the final results, and the method still produced
estimates acceptable in a forensic framework.
Keywords: Forensic dentistry, dental age estimation, secondary dentine formation, young
adults.
114
INTRODUCTION
The accurate approximation of chronological age, secondary to sex determination, is an
integral factor in constructing a biological profile for forensic [1] and anthropological
purposes, including the confirmation of identification at times of mass disasters, crimes,
accidents and of unknown remains [2-4]. Further, the estimation of the chronological age
in the living is also needed in situations such as immigration and refugee [4]. Saunders
originally proposed the estimation of chronological age based on different stages of tooth
eruption [5], since then several more methods have been suggested to estimate dental age
in children.
Amongst these various methods, those that are based on the radiological examination of
permanent teeth development, are the most accurate [6, 7]. The Demirjian et al. [8, 9]
classification is reported as the best method for dental age estimation in children and
adolescents, thanks to its high observer agreement and correlation between the defined
stages and age [10]. The Demirjian et al. method has been adapted to different
populations, showing a mean difference between the chronological age and the dental age
of around one year in different studies [6, 9, 11].
The completion of tooth development is marked with the closure of the root apex, with the
third molar being the last tooth to complete its eruption and root development at
approximately 17-21 years of age. Following this stage, the accurate estimation of
chronological age based on dental formation becomes challenging [12], leading to the
115
development of alternative methods in adults. Bodecker [13] identified the relation of the
continued apposition of secondary dentine and the subsequent change in the morphology
of the pulp chamber, with chronological age. Accordingly, several dental age estimation
methods have been developed, based on the relation between secondary dentine
formation, and the subsequent narrowing and change in pulp chamber dimensions and
shape with age [1, 2, 14, 15].
Dental analysis using radiographs for the purpose of age estimation presents numerous
advantages over other histological and biochemical methods; it is relatively simple, non-
invasive, and economically viable [16]. The method developed by Kvaal et al. [1] is a
relatively non-invasive method and has been validated in diverse populations [17, 20].
Karkhanis et al. [17] applied the Kvaal et al. [1] method in a Western Australian population
to develop age estimation standards with acceptable results in a forensic framework (±10
years) [2].
Originally, the Kvaal et al. [1] method was proposed to be applied in an adult population.
More recently, the method has been applied in younger populations with varying degrees
of success. The level of error in estimates of ages remains high in younger populations with
Landa et al. reporting a standard deviation approaching 15 years [20].
The aim of the present study was to validate the applicability of the Kvaal et al. [1] method
in a younger population (Western Australia sample) and to provide further refinement of
the level of variation in younger people. This also assessed the potential of this method as
116
an additional tool for dental age estimation in juveniles, where methods based on the
analysis of tooth development cannot be used.
MATERIALS AND METHODS
This study received ethics approval from the Human Research Ethics Committee of The
University of Western Australia (Ref: RA/4/1/6797).
Sample Selection
The study cohort consisted of a series of subjects who consecutively presented for
orthodontic treatment at a private specialist orthodontic office. From the initial sample, 74
Western Australians were aged less than 30 years, of those 63.5% (n=47) were female and
36.5% (n=27) were male, with a median age of 16 years for both genders. All panoramic
radiographs were acquired from the same machine in digital format.
Analyses were completed with Image J software (version 1.48 19 April 2014 - National
Institute of Health, USA) and the measurements were completed by a single observer (TM).
All data were collated using Excel (version 2013 Microsoft Redmont, USA), and statistical
analysis was completed using R Core Team version 3.1.3 (2015). (R: A language and
environment for statistical computing. R Foundation for Statistical Computing, Vienna,
Austria. URL http://www.R-project.org/). All subjects with a panoramic radiograph of high
quality with respect to factors of image brightness, contrast and sharpness were included.
117
Any radiographs that did not meet this requirement or had observable failings (eg. image
distortion, poor contrast, superposition of tooth structure, or improper positioning) were
excluded. All teeth included in the analysis were clinically sound with completed root
formation and at occlusal plane level. Teeth with rotations, incomplete root formation,
dilacerations, pulpal pathologies, and endodontic treatment, and/or restorations were
excluded. Finally, teeth with large areas of enamel overlap between neighboring teeth
were excluded in this study.
Teeth analysed
Following the parameters as provided by Kvaal et al. [1], the teeth analysed were the
maxillary central incisors (with Federation Dentaire International (FDI) notation 11 and 21)
lateral incisors (FDI notation 12 and 22), second premolars (FDI notation 15 and 25),
mandibular lateral incisors (FDI notation 32 and 42), mandibular canines (FDI notation 33,
and 43) and first mandibular premolars (FDI notation 34 and 44). In the original study,
Kvaal et al. [1] analysed only those periapical radiographs from individuals where all the six
teeth were present and suitable for examination.
In the present study, panoramic radiographs with any combination of the required teeth
available for measurement were included. Previous research [1, 17, 19] has demonstrated
the absence of bilateral asymmetry in the deposition of secondary dentine. Consequently,
teeth from either side that fulfilled the inclusion criteria were analysed for the purpose of
developing age estimation standards.
118
Measurements
Odontometric data were acquired following the methodological approach of Kvaal et al. [1].
In this way, the data were obtained from measuring: maximum tooth length (from the
incisal border or cusp tip to the root apex), maximum pulp length (from the pulp chamber
roof to the root apex), and maximum root length (from the cemento-enamel junction (CEJ)
on the mesial surface of each tooth to the root apex). The pulp chamber and root width
measurements were collected at the points A (CEJ), B (mid-point between the points A and
C) and C (mid-point between the CEJ and root apex).
Measurement precision
A pilot set of 30 panoramic radiographs, which were not included in the final analysis, was
used to perform an initial training and benchmarking to an expert in the field (SK). Six of
the 30 radiographs were measured on 6 different days, in addition to 4 randomly selected
panoramic radiographs, thus resulting in the analysis of 10 panoramic radiographs per day.
Based on this, intra- and inter-observer error calculations were performed [17].
The measurements were acquired from all the panoramic radiographs with a minimum of
one day between each session to minimize the possibility of memorizing reference points
and/or measurements in each observer. A second intra- and inter-observer calibration was
performed using 5 randomly selected panoramic radiographs from the final study sample,
and recording the measurements on 5 different days, also using 4 additional panoramic
radiographs per day, to avoid measurements memorizing, with at least one day between
each evaluation.
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Statistical Analysis
Simple descriptive statistics (mean, standard deviation, and frequency distributions) were
used to summarize the data. Initial tests for normality (assessment for skewness, kurtosis
and Shapiro-Wilk) were performed to determine, where appropriate, parametric and non-
parametric univariate analysis testing for the continuous variables (Table 4.1). Pearson’s
correlation coefficient (r) was calculated to assess the strength of correlation between age
and dental ratios based on the Kvaal et al. [1] method (Table 4.1).
The correlation coefficients calculated (using the width ratios) presented significant
correlation values. The most representative were observed for the ratio calculated
between pulp and root width at the B point of the root, and for the predictor W-L. The
mandibular canines showed the highest correlation coefficient for the predictors B (-0.570)
and W-L (-0.625).
To examine the association of several factors with chronological age, multivariable linear
regression analyses were used to look at the association between the independent and
outcome variables. The outcome variables included chronological age. The predictor
variable M and W-L were used as the independent variables. Age estimation models were
developed individually for each tooth (Table 4.2), and the following tooth combinations
(Table 4.3): Three maxillary teeth with the predictors M and W-L individually introduced for
each tooth, (6 predictors), and the average of M and W-L (2 predictors).
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Three mandibular teeth with the predictors M and W-L individually introduced for each
tooth, having 6 predictors in the equation, and the average of M and W-L resulting in 2
predictors. And mandibular and maxillary teeth M and W-L predictors, introduced
individually in the equation (12 predictors) and the average of M and W-L (2 predictors). All
regression models were built using the ordinary least squares approach. R-square values
were computed to examine the amount of variance explained by the predictor variables.
All statistical tests were two-sided and a p- value of less than 0.01 was considered to be
statistically significant. Corrections were made for multiplicity using a modified Bonferonni
method to reduce the likelihood of Type I errors; an alpha threshold for statistical
significance for all comparisons was set at 0.01. Univariate analyses and multivariable
linear regression analyses were performed using R Core Team version 3.1.3 (2015). (R: A
language and environment for statistical computing. R Foundation for Statistical
Computing, Vienna, Austria. URL http://www.R-project.org/).
RESULTS
Measurement precision
The technical error of measurement (TEM), relative technical error of measurement (rTEM)
and coefficient of reliability were within acceptable standards for the intra- and inter-
observer measurement precision (TEM<1.0, rTEM<5%, R>0.75). These values were 0.92,
2.99% and 0.95 respectively for intra-observer precision analysis. Similarly, the inter-
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Table 4.1. Correlation coefficients between chronological age and Kvaal dental
measurements and ratios, for individuals under 30 years of age.
TOOTH NUMBER (FDI numbering system)
RATIO 11/21 12/22 15/25 32/42 33/43 34/44
P 0.13NS 0.23 NS 0.13 NS 0.16 NS 0.45* 0.15 NS
T 0.04 NS -0.07 NS -0.002 NS -0.13 NS 0.17 NS -0.12 NS
R 0.29* 0.29* 0.15 NS 0.33* 0.28* 0.39**
A -0.13 NS -0.28* -0.004 NS -0.26* -0.25 NS -0.14 NS
B -0.38* -0.30* -0.28* -0.35* -0.57** -0.38*
C -0.34* -0.38* 0.01 NS -0.09 NS -0.61** -0.5**
M -0.05 NS -0.2 NS 0.0001 NS -0.12 NS -0.11 NS -0.26*
W -0.41** -0.39** -0.15 NS -0.23* -0.12 NS -0.49**
L 0.15 NS 0.29* -0.002 NS 0.25* 0.47** 0.29*
W-L -0.31* -0.42** -0.05 NS -0.36* -0.62** -0.54**
*= p<0.05 **=p<0.01 NS= Not significant
Abbreviations: P, ratio between length of pulp and root; T, ratio between length of tooth and root; R, ratio between length of pulp and root; A , ratio between width of pulp and root at CEJ (Level A); B, ratio between width of the pulp and root at mid-point between level C and A (level B); C, ratio between width of pulp and root at mid-root level (level C); M, mean value of all ratios (first predictor); W, mean value of width ratios from levels B and C; L mean value of the length ratios P and R; W-L, difference between W and L (second predictor)(1).
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Graph 4.1. Scatter plot showing a positive association between the estimated age in
years and the chronological age in years for the teeth 33/43
Table 4.2. Multiple regression for estimation of chronological age (in years) from
individual maxillary and mandibular teeth from individuals under 30 years of age .
Tooth (FDI) n R R2 Equation SEE ± years
11/21 69 0.15 0.12 Age= 22.915-28.78 (M) -22.376 (W-L) 4.3
12/22 67 0.19 0.17 Age= 19.724-25.935 (M) – 23.631(W-L) 4.2
15/25 68 0.003 -0.27 Age= 17.78-3.962(M)-2.204(W-L) 4.5
32/42 71 0.13 0.10 Age= 4.644-5.363(M)-22.558(W-L) 4.4
33/43 48 0.41 0.39 Age= 11.26-41.33(M)-86.06(W-L) 3.7
34/44 71 0.32 0.31 Age= 10.513-27.075(M)-38.176(W-L) 3.7
Note. *R2, coefficient of determination. SEE, standard error of estimation in years. See table 4.1. for abbreviations.
12
3
Table 4.3. Multiple regressions for estimation of chronological age (in years) from the combined maxillary and mandibular teeth.
Teeth (FDI) n R R2 Equation SEE ± years
3mx (2pds) 60 0.15 0.12 Age= 28.702-46.338(M) - 24.233(W-L) 4.1
3mx(6pds) 60 0.23 0.15 Age=24.394-30.751 (11/21M) -12.090 (11/21W-L) - 29.2257 (12/22M)- 12.894 (12/22W-L) + 2.611 (15/25M) - 0.631 (15/25 W-L)
4.1
3mdb(2pds) 45 0.41 0.38 Age= -27.44 + 10.48(M) – 63.82 (W-L) 3.6
3 mdb (6pds) 45 0.53 0.46 Age= 1.894 + 13.428 (32/42M) -5.931 (32/42W-L) - 51.067 (33/43M) -66.495 (33/43W-L) - 5.114 (34/44M) -16.806 (34/44W-L)
3.3
6 teeth (2 pds) 40 0.25 0.21 Age= 31.91 - 63.34 (M) - 63.34 (W-L) 4.1
6 teeth (12 pds) 30 0.54 0.33 Age= 2.627 -58.42 (11/21 M) + 4.526 (11/21 W-L) + 32.169 (12/22 M) - 12.913 (12/22 W-L) + 25.460 (15/25M) + 1.098 (15/25 W-L) + 5.270 (32/42 M) + 0.096 (32/42 W-L) - 28.692 (33/43 M) + 1.686 (33/43 W-L) - 13.857 (34/44 M) - 49.336 (34/44 W-L)
3.7
*R2, coefficient of determination. SEE, standard error of estimation in years. See table 4.1 for abbreviations.
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observer calibration (between TM and SK) showed comparable precision [21] (TEM 0.80,
rTEM 2.37 and R 0.98). In this way, individual (Table 4.2) and multiple (Table 4.3) tooth
regression models were obtained. The accuracy to predict the age was quantified by the
standard error of estimation (SEE ±years). The most accurate age estimation model based
on the analysis of individual tooth was for mandibular canines (SEE ±3.708 years) (Graph
4.1). Prediction accuracy improved with the combined analysis of teeth; it was highest for
the model developed with the three mandibular teeth (6 predictors, SEE ± 3.388 years).
DISCUSSION
The estimation of chronological age has been a very relevant topic of discussion through
human history. For this reason, diverse skeletal and dental methods have been developed,
showing variable levels of reliability in different populations. Those methods, based on
dental changes, are well accepted and have shown their potential for forensic and
anthropological applications [22].
Once root formation has been completed, progressive dental changes such as secondary
dentine formation can be radiographically assessed based on the narrowing on the pulp
chamber. Odontometric and morphometric measurements can thus be acquired to
quantify secondary dentine deposition, and are the foundation for non-invasive adult age
estimation methods such as Kvaal et al. [1], and Cameriere et al. [23].
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The Kvaal et al. [1] method has been widely validated in different populations, because of
numerous benefits such as its relatively non-invasive approach, applicability in live
individuals, and low cost, among others. Previous research has applied this method to a
Western Australian population [17], and showed significant results that are valid under
forensic standards. Although the Kvaal et al. method [1] was initially developed to estimate
age in individuals over 20 years old, previous studies have tested this method in younger
populations [19].
The present study applied the Kvaal et al. method [1] in Western Australian participants
under 30 years of age. The primary aim was to assess the applicability of this method in a
younger population to broaden the age range that the method can be applied to, without
compromising the age estimation accuracy.
To this end, regression models were developed based on the data acquired from individual
teeth (Table 4.2) and a combination of teeth (Table 4.3). The accuracy to predict age was
quantified by the standard error of estimation (SEE ±years). The most accurate model for
individual teeth was for the mandibular canines (±3.708 years), in contrast to the study of
Karkhanis et al. [17], where the same tooth presented the highest SEE (±10.903 years).
Prediction accuracy improved when multiple teeth were included in the regression models
(Table 4.3). In this study, the highest level of accuracy was obtained when the equation
included 3 mandibular teeth and 6 predictors, (SEE ±3.388 years), in comparison with the
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study of Karkhanis et al. [17], where the most accurate model was for the combined
analysis of the 6 teeth and 12 predictors (SEE ±7.963).
Age estimation in individuals older than 14 years is difficult, as all permanent teeth, except
the third molars (when present), have completed their development [19]. Some examples
of previous studies amongst people under 30 years of age, using the Kvaal et al. method [1]
on panoramic radiographs, are: Erbudak et al. [24] in a Turkish population, including in their
sample 75 participants between 14 to 35 years of age, obtaining a SEE= ± 8.73 years at
best, using the regression formulas of Paewinsky et al. [25] and Kvaal et al. [1].
Further such studies were published by: Landa et al. [20] in a Spanish population with an
age range of 14 to 60 (n=100,) from which 40 idividuals were aged younger than 31 years
of age, and with an underestimation of age when using the regression formulae of Kvaal et
al. [1], and Paewinsky et al. [25], and a standard deviation of 12.53 at best, when the Kvaal
et al [1]. regression equation was used.
The last example is the study of Meinl et al. [19], which was conducted in an Austrian
population (n=44) with an age range of 13 to 24 years, and resulted in a mean
underestimation of 31.44 years when the Kvaal et al. [1] regression models were applied,
or a mean overestimation of 20.88 years when Paewinsky et al. [25] formula was applied.
In contrast, the present study (n=74) shows that the Kvaal et al. [1] method provides
acceptable results [2] in a sample composed of sub-adults and young adults.
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Further research is warranted, in other populations with similar age ranges and using larger
samples. It is also insightful to compare the results of this study with other methods based
on third molar development as an estimator of chronological age. One of the most
remarkable studies is the research performed by Lewis and Senn [10]. They reported a
standard deviation of no more than 3 years, when different methods are applied in a
North-American population. Another method based on third molars is the examination of
the periodontal membrane in lower third molars in a German population [26], which found
a standard deviation of between 1.9 to 4.8 years. However, third molar agenesis has been
reported to be between 14% up to 51% in different studies [27]. The Kvaal et al. [1]
method can be considered as an alternative in these cases.
CONCLUSION
Panoramic radiographs are a unique diagnostic tool, but also provide useful information,
valid for forensic purposes. It has been well established that dental records are a highly
precise instrument for determining an individual’s identity. The use of the Kvaal et al. [1]
method was initially purposed on periapical radiographs, obtained from adults, but lately
this method was applied using panoramic radiographs, and included juvenile participants.
The validation of the Kvaal et al. [1] method for age estimation, using panoramic
radiographs obtained from a population including juvenile individuals, enlarges the range of
ages where the ratio between secondary dentine production and decrease of pulp
chamber can be applied. This also presents the opportunity to examine the application of
this method in other juvenile population groups.
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17. Karkhanis S, Mack P, Franklin D. Age estimation standards for a Western Australian
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5. Chapter 5. Application of the Kvaal method for adult dental age estimation using
Cone Beam Computed Tomography (CBCT).
This chapter was published as:
Marroquin, T.Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Nurul F., Kanagasingam S., D.
Franklin., E., Kruger, E., & Tennant, M. (2016) Application of the Kvaal method for adult
dental age estimation using Cone Beam Computed Tomography (CBCT). Journal of Forensic
and Legal Medicine, Accepted for publication. October 2016.
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ABSTRACT
Different non-invasive methods have been proposed for dental age estimation in adults,
with the Kvaal et al. method as one of the more frequently tested in different populations.
The purpose of this study was to apply the Kvaal et al. method for dental age estimation on
modern volumetric data from 3D digital systems. To this end, 101 CBCT images from a
Malaysian population were used. Fifty-five per cent were female (n=55), and forty-five
percent were male (n=46), with a median age of 31 years for both sexes. As tomography
allows the observer to obtain a sagittal and coronal view of the teeth, the Kvaal pulp/root
width measurements and ratios were calculated in the bucco-lingual and mesio-distal
aspects of the tooth.
From these data, different linear regression models and formulae were built. The most
accurate models for estimating age were obtained from a diverse combination of
measurements (SEE ±10.58 years), and for the mesio-distal measurements of the central
incisor at level A (SEE ±12.84 years). This accuracy, however is outside an acceptable range
for forensic application (SEE ±10 years), and is also more time consuming than the original
approach based on dental radiographs.
Key words: Adults, age estimation, tomography, Kvaal method.
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INTRODUCTION
Currently, the need for developing more accurate and non-invasive methods for age
estimation, as part of the identification of adult individuals in situations of forensic
scenarios is increasing globally [1]. Gustafson first proposed a method for dental age
estimation in adults, [2] since then, the analysis of dental changes in adults relative to
chronological age has continued. The adult dentition is relatively resistant to
environmental and chemical influences, and methods based on the assessment of teeth are
considered advantageous for this reason [3, 4].
Furthermore, methods based on odontometric measurement of pulp and tooth structures
from dental radiographs or tomographs are non-invasive/non-destructive and can be
applied to both living or deceased individuals [5]. Kvaal et al, proposed a method for age
estimation in adults which has been tested in different populations around the world since
1995, but all reported a high standard error (±8.5 to ±13 years) [1, 5, 6]. The basis of this
method is the analysis of the narrowing of the pulp chamber with age, which is observable
and measurable in dental radiographs. However, there is scope for improvement in the
accuracy of the age estimations.
With the emergence of computer tomography (CT) and cone beam computer tomography
(CBCT), new methods based on volumetric reconstruction of tooth and pulp volume and
ratio calculations, have been proposed for dental age estimation in adults [7, 8]. However,
those techniques have not provided better accuracy relative to the previously described
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Kvaal et al. method, using dental radiographs. Moreover, pulp/tooth volume calculation is
labor intensive, [9] and can require the use of complex, and often costly computer software
[10]. Clearly, these more technical multi-dimensional systems provide considerably more
data, at a substantially more detailed level, and with a reduction in many of the
complications of simple plane film images.
The method described by Kvaal et al. [5] was initially proposed, with measuring dimensions
on periapical radiographs with a microscope and a pair of calligraphers. The applications of
this method have been expanded to include panoramic radiographs using different
analytical software [6, 11]. The purpose of the present study is to apply the Kvaal et al. [5]
method for dental age estimation using modern computer tomographic data from 3D
digital systems. The null hypothesis is that the substantially increased quantity (and
quality) of the data from these systems will provide greater accuracy of dental age
estimation in adults.
MATERIALS AND METHODS
Sample
The study sample included a total of 101 tomographs obtained as part of normal treatment
from the radiology department of the University of Keibangsaan Malaysia. Almost half (n=
47) were obtained with a Kodak device, reference K9000-3D (exposure parameters:
scanning time: 10.8 s, 3-15 mA, 60-85kVp, field of view FOV: 5.2 cm x 5.2cm to 5.5cm to
5.5cm, 180° rotation, slice thickness 0.076-0.2 mm), and 54 were obtained with an i-CAT
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device (Dental Imaging Technologies Corporation. i-CAT® FLXTM) (exposure parameters:
scanning time 4s, 5 mA, 120 kVp, FOV: 16cm x 16cm, Slice thickness 0.3 mm to 0.4 mm). Of
these tomographs, 55% were from female (n=55), and 45% were from male (n=46)
patients, with a median age of 31 years for both sexes (Table 5.1).
All images were received in DICOM format, and analysed using the Osirix® software
package (OnDemand 3D software CyberMed Inc, Seoul, South Korea). The study sample
included teeth with very small coronal restorations, as long as they did not compromise the
pulp chamber and secondary caries was not present. Teeth with shape abnormalities,
active caries, root canal treatment, prosthetic restorations, signs of pulp or periapical
pathologies, or open root apex, were duly excluded from the sample. Multi-rooted upper
second premolars were also excluded.
Teeth analysed
Initially, Kvaal et al. [5] proposed a set of linear measurements, including the length of the
tooth, pulp, and root, in addition to the width of the root and pulp chamber at different
levels, in six different teeth: upper central and lateral incisors, and the second premolar;
and the lower lateral incisor, canine and first premolar. In the present study, due to the
unclear definition of the pulp chamber and tooth boundaries for the lower teeth (most
likely related to their small dimensions) only upper teeth were included: central incisor,
lateral incisor, canine, and second upper premolar (when possible). As the dental images
are tomographs, it is possible to assess the teeth in sagittal and coronal views; accordingly,
the root length, and pulp/tooth width measurements proposed by Kvaal et al. [5] were
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acquired in the mesio-distal and bucco-lingual aspects of the teeth (see below). Significant
differences between teeth of the left and right side of the maxilla have not been reported
previously, [5] and therefore in this study, teeth from either the left or right side were
measured.
Measurements
As proposed by Kvaal et al., [5] the mesio-distal measurements of the teeth (coronal view)
were performed as follows: first, the level A, was located at the CEJ (cemento-enamel
junction) on the mesial side of the tooth, then level C was located halfway between point A
and the root apex, and finally point B was located halfway between point A and C.
As this is the first study applying the Kvaal et al. method exclusively using tomographs,
bucco-lingual measurements were also acquired (sagittal view). Point A was located at the
vestibular CEJ, point C halfway between the vestibular CEJ and the root apex, and point B,
halfway between point A and point C. In this way, there were six pulp/tooth width
measurements per tooth. All measurements were recorded by one observer (TYM) using
the Osirix® software.
Statistical analysis
Intra-observer error was tested, four tomographs were randomly selected (two Kodak and
two i-CAT) and all the measurements were recorded by one observer (TYM). Upper
central, lateral and canine were measured on four separate occasions, with a minimum of
one day between repetitions ensuring that the observer did not remember the previously
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recorded measurements. Measurement error was assessed by calculating the technical
error of measurement (TEM), coefficient of reliability (R) and relative technical error of
measurement (rTEM) [12].
All data were collected in an Excel spreadsheet, Excel (version 2013 Microsoft, Redmont,
USA), and statistical analysis was completed using R Core Team version 3.1.3 (2015). (R: A
language and environment for statistical computing. R Foundation for Statistical
Computing, Vienna, Austria. URL http://www.R-project.org/). Descriptive statistics were
used to summarise the data (mean, standard deviation, and frequency distributions).
Normality was also tested (skewness, kurtosis and Shapiro-Wilk) to establish whether
parametric or non-parametric analysis was required.
Pearson correlation coefficient (r) was calculated to assess the relationship between the
dental ratios and age, for data obtained from the Kodak CBCT and for data obtained from i-
CAT CBCT individually, and also when both data sets were combined. This was done with
the aim of testing if the difference between the resolutions of both devices could cause any
statistically significant differences (Table 5.2).
Linear regression models were built with age designated as the dependent variable.
Different age estimation equations were then formulated using different groupings of age
predictors: 1) the tooth/pulp ratios at the levels A, B or C individually; 2) calculating the
average of the pulp/tooth ratios of all the teeth at the different levels (A, B or C) obtaining a
formula for each level; 3) calculating the average of the pulp/tooth ratios of the lateral (Lat)
139
and central (Cent) upper incisor at the different levels (A, B and C); 4). Averages of the
pulp/tooth ratios from all the teeth at the levels A, B and C in the same formula (A+B+C);
and 5) same as 4, but excluding the ratios obtained from the canines (Cent-Lat). A total of
17 linear regression models were thus generated per data-set: sagittal (s) view (bucco-
lingual measurements); coronal (c) view; and the average of both (sc). The accuracy of the
models is reported as the standard error of estimation (SEE) [11, 13].
RESULTS
Intra-observer error results were considered to be within acceptable range. (TEM <1.0 and
the coefficient of reliability R>0.80%), regardless the source of the tomograph (Kodak or i-
CAT) or whether the measurements were recorded in the bucco-lingual or mesio-distal
view of the teeth. In terms of the relative technical error of measurement (rTEM), 72% of
the observations scored <5% and 28% had an rTEM < 10%. It was also observed that the
accuracy of the observer was better for the bucco-lingual measurements (sagittal view of
the teeth) regardless the source of the tomography.
Pearson correlation coefficient test (r) demonstrated a stronger correlation between the
pulp/tooth ratios and age for the bucco-lingual measurements (sagittal (s)) than for the
mesio-distal measurements (coronal view (c)) (Table 5.2). Although there were differences
between the correlation coefficients from the Kodak and i-CAT CBCT’s, scatter-plots
including the results of both sources do not show outliers associated with the specific use.
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There was a clear and significant negative correlation between age and pulp/tooth ratios in
all the data sets.
Table 5.1. Age and sex distribution for CBCT and i-CAT tomographs.
Table 5.2. Correlation coefficient measurements CBCT
CBCT i-CAT CBCT & i-CAT
Tooth number Coronal Sagittal Coronal Sagittal Coronal Sagittal
11/21 A -0.05 NS -0.36* -0.634** -0.65** -0.45** -0.61**
11/21 B -0.26 NS -0.37* -0.421** -0.59** -0.32* -0.5**
11/21 C -0.29 NS -0.45** -0.288* -0.36* -0.23* -0.41**
12/22 A -0.53** -0.08 NS -0.326* -0.62** -0.31* -0.41**
12/22 B -0.35* -0.5** -0.3* -0.60** -0.22* -0.46**
12/22 C -0.24 NS -0.57** -0.013 NS -0.41** -0.05 NS -0.41**
13/23 A -0.25 NS -0.13 NS -0.153 NS -0.50** -0.04 NS -0.17 NS
13/23 B -0.59** -0.56** -0.329* -0.41* -0.28** -0.39**
13/23 C -0.52** -0.34** -0.348* -0.24 NS -0.28** -0.21*
*p< 0.05, ** p< 0.01, NS= non-significant
SEX FEMALE MALE TOTAL
AGE RANGE (YEARS) CBCT (n=23) i-CAT (n=32) CBCT (n=24) i-CAT (n=22)
15-20 2 1 7 2 12
20-29 12 9 5 8 34
30-39 3 5 2 2 12
40-49 4 6 8 5 23
50-59 2 6 2 0 10
60-75 0 5 0 5 10
TOTAL 55 46 101
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Table 5.3. Linear regression analysis, linear regression formulae, correlation coefficient
(r) between age and the ratios of bucco-lingual and mesio-distal width measurements
from CBCT & i-CAT
Abbreviations: Tooth number (11/21, 12/22 and 13/23) with Asc, Bsc or Csc= pulp/tooth ratio at the levels A, B or C in the sagittal and coronal view (sc) calculated per tooth. Asc, Bsc or Csc: average of the pulp/tooth ratio at the respective level, from all the teeth. Asc, Bsc or Csc with Lat/Cent: average of the pulp/tooth ratio only from central and lateral incisors. Asc+Bsc+Csc=average from the pulp/tooth ratio from all the teeth at the respective level. Asc+Bsc+Csc=average from the pulp/tooth ratio from all the teeth at the respective level including only lateral and central teeth.
Sagittal and coronal
Age predictors n Linear regression formulae r r2 s
11/21 A sc 86 Age=99.74-72.07(11Ac)-161.63(11As) 0.4 0.4 12.2
11/21 B sc 86 Age=81.82-35.031(11Bc)-147.14(11As) 0.26 0.24 14
11/21 C sc 86 Age=71.92-29.16(11Cc)-134.69(11Cs) 0.17 0.15 14.9
12/22 A sc 89 Age=87.43-68.05(12Ac)-129.37(12As) 0.21 0.19 14.5
12/22 B sc 89 Age=73.98-24.34(12Cb)-127.46(12Bs) 0.21 0.19 14.5
12/22 C sc 89 Age=57.56+37.84(12Cc)-148.22(12cs) 0.18 0.17 14.7
13/23 A sc 95 Age=51.14-5.4(13Ac)-47.192(13As) 0.03 0.01 15.4
13/23 B sc 95 Age=69.51-47.15(13Bc)-70.44(13Bs) 0.17 0.15 14.2
13/23 C sc 95 Age=60.81-78.34(13Cc)-34.37(13Sc) 0.09 0.08 14.9
A sc 78 Age=100.41-33.11(Ac)-206.40(As) 0.34 0.33 13.5
B sc 78 Age=89.22-20.54(Bc)-178.29(Bs) 0.31 0.29 13.9
C sc 78 Age=69.46+16.4(Cc)-174.42(Cs) 0.17 0.15 15.2
A sc Cent/Lat 83 Age=105.42-72.96(Ac1/2)-187.22(As1/2) 0.4 0.38 12.8
B sc Cent/Lat 83 Age=86.31-19.86(Bc1/2)-180.19(Bs1/2) 0.29 0.27 13.9
C sc Cent/Lat 83 Age=70.41+42.09(Cc1/2)-206.7(Cs1/2) 0.23 0.21 14.4
Asc+Bsc+Csc 74 Age= 104.09 -17.65 (Ac)-135.48 (AS)-38.18(Bc) -105.54(Bs)+40.87(Cc)+10.93 (Cs)
0.4 0.35 13.3
Asc+Bsc+Csc Lat/Cent
82 Age=106.25-180.14(Asc1/2)-135.83(Bsc1/2)+51.73(Ccs1/2)
0.4 0.39 12.7
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Correlation coefficients were calculated as follows: i) for the measurements obtained from
the Kodak tomographs; ii) for the measurements recorded from the i-CAT tomographs; and
iii) for the combination of both. The i-CAT tomographs showed the strongest correlation to
age, especially for the upper central incisor (r= -0.65), followed by the combination of the
Kodak & i-CAT data sets (r=-0.61). The correlation coefficients obtained from the Kodak
tomographs, although statistically significant, were lower than those obtained from the i-
CAT and combined Kodak & i-CAT images (Table 5.2).
In relation to the accuracy of the different linear regression models, all estimates were over
the threshold generally accepted for forensic application (SEE ±10 years) [14]. However,
the SEE is reduced when both data-sets are combined into a linear regression model (Table
5.3). There was only one equation with an acceptable level of predictive accuracy (SEE
10.58 years (n=72, r=0.59, r2=0.56)):
Age= 101.46 + 734.74 (Ac) -374. 81 (Ac(Cent-Lat)) – 1075.18 (C sc) + 327.07 (Bc) + 310 (Cc(Cent-
Lat)) – 159.25 (11/21 As)
Abbreviations: Ac: average of the pulp/tooth ratio in the coronal view at level A from the
three teeth. Ac(Cent-Lat): average of the pulp/tooth ratios from the lateral and central
incisors. Csc: average of the pulp/tooth ratio at level C from the sagittal and coronal views
(sc) from all teeth. Bc: average of the pulp tooth ratio at the level B from all the teeth in the
coronal view. (Cc(Cent-Lat)): average of the pulp/tooth ratios at the level C from the lateral
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and central incisors in the coronal view. 11/21 As: pulp/tooth ratio at the level A from the
central incisor in the sagittal view.
The most accurate linear regression models obtained from the individual analysis of the
bucco-lingual measurements were as follows: the central incisor at level A (Age= 84.059 –
191.003 (11/21 As), r2=0.37, SEE=±12.84), the average of the bucco-lingual measurements
from the central incisor and lateral incisor at the level A, B and C (Age= 102.08-157.94 (As) -
73.0 (Bs) -36.81 (Cs), r2=0.39, SEE=±12.73 years).
When both data-sets were combined (Table 5.3) the highest accuracy was achieved from:
the average of the bucco-lingual (s) plus the average of the mesio-distal (c) measurements
at level A, (SEE ±12.17 years); the average of the bucco-lingual and mesio-distal
measurements at level A from the central and lateral incisors, (SEE ±12.76); and the
average of the bucco-lingual and mesio-distal measurements from the central and lateral
incisors at level A, plus level B, plus level C, (SEE ±12.7). The linear regression models
generated by the inclusion from only the mesio-distal (c) measurements did not result in an
SEE lower than ±14 years, and therefore these results are not included.
DISCUSSION
This is the first study testing the Kvaal et al. method exclusively in tomographs, and also the
first one applying Kvaal et al’s. pulp/tooth width ratio calculations in the bucco-lingual
aspect of the teeth. Computer tomography is increasingly being used in dental practice
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and provides three-dimensional information about any area of interest, in a relatively quick
and cost-effective manner [15].
In this study, it was expected that application of the Kvaal et al. method using CBCT
diagnostic images would increase the array of methods available for the forensic profiling
of living and deceased individuals.
Until now, there has been only one other study proposing a similar method for adult dental
age estimation, based on the assessment of the pulp/tooth bucco-lingual dimensions (area)
in canines [16]. Although the results of the latter study were satisfactory (Mean prediction
error, ME ±2.8 years at best), this method required extracted teeth, and thus has restricted
application in a forensic context. The use of tomographs overcomes issues related to the
requirement for tooth extraction, and also permits the analysis of multiple teeth with less
radiation exposure.
Although, in this study, the number of individuals was small in certain age intervals, there
are well documented biological age-related changes in the human dentition, which have
allowed forensic dentists to propose and use different methods for dental age estimation
[17].
In previous publications applying the Kvaal et al. [5] method for dental age estimation in
adults, one of the principal limitations is the absence of a clear limit between the dentine
and the pulp camber, [11] which is observed as a grey zone instead of a distinct line [6].
145
This affects the accuracy of the measurements and intra/inter-observer agreement.
In the present study, neither Kodak nor i-CAT tomographs were exempt from this issue. In
certain cases, the border between the pulp chamber and dentine, or tooth and bone are
also more blurred than in periapical radiographs.
It is noteworthy that dental Kodak tomographs may have higher resolution than i-CAT
tomographs. However, in the present study the data obtained from the i-CAT had a higher
correlation to age compared to the Kodak scans (Table 5.2). Similarly, the bucco-lingual
width ratios had a higher correlation to age than the mesio-distal width ratios (with the
latter measurable in periapical radiographs).
It has previously been reported that Kvaal et al. length measurements are both: difficult to
register, and do not provide significant information to the final equation [5, 18]. It is
important to note that in the tomographs analysed in the present study, it was even more
difficult to observe the root apex compared to periapical radiographs.
The only length measurement registered was the root length from the CEJ towards the
apex to locate points A, B, and C. In this way, only pulp/tooth width, and ratios were used
as the only age predictors. The exclusive use of pulp/tooth ratios proposed by Kvaal et al.
[5] has previously been documented [18] on panoramic radiographs, showing more
accurate results (SEE=±10.02 years) than those obtained in this study. (SEE=±10.58 years at
best).
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In a previous study that analysed the odontometric age-related changes in different teeth,
the rate of secondary dentine formation varied depending on tooth type: in canines, the
increase of coronal dentinal thickness was not as high as for the incisor, and premolars [19].
In the present study, it was similarly observed that although the correlation coefficient
between pulp/tooth ratios and age were significant, the exclusion of canine ratios when the
linear regression models were generated, improved their accuracy.
On the other hand, this is also the first study documenting the inclusion of teeth with small
crown fillings in the sample to generate linear regression formulae, in contrast to previous
publications using the Kvaal et al. method, [5] where one of the inclusion criteria was to use
only totally clinically sound teeth. There were no statistically significant differences caused
by inclusion of these teeth. This may relate to the nature of the formation of tertiary
dentine or reactionary dentine to external threats. Tertiary dentine formation is highly
dependent on the stimulus, and that caries mediators induce a focal dentine production,
[19-21] with a rate formation of about 3µm per day [22].
Regression analysis, has been chosen for age estimation due to its simplicity [23].
Nevertheless, it is necessary to note the limitations of the use of linear regression models
for dental age estimation; for example, the questionable believe that higher standard
deviations when the original formulae of Kvaal et al. are applied in populations of different
ethnic backgrounds [24], are related to the population or origin of the individual rather
than to the intrinsic characteristics of the sample. Also, it assumes that formation of
secondary dentine is a linear process, when it is more similar to a curve [25]. Additionally,
147
although using tomography resulted in obtaining more odontometric data from the same
teeth (mesio-distal and bucco-lingual measurements), this apparent advantage over the
use of dental radiographs, did not improve the final outcome. Also, the need to properly
align the teeth in the sagittal and coronal plane demands more time than the traditional
Kvaal et al. approach in dental radiographs.
Finally, it is necessary to mention that CBCT is not exempt from artefacts intrinsic to the
process of image acquisition [26]. This could explain, not only the high SEE obtained in this
study, but also the poor accuracy of those methods based on pulp/tooth volume
calculation, [9,10] when compared with more simple approaches such as the measurement
of pulp/tooth area on dental radiographs (Cameriere et al method, with a SEE=±3.27 years)
[16].
CONCLUSION
Radiological assessment of dental age-related changes is a valid tool for age estimation. It
is the case that new diagnostic technologies provide practitioners and forensic researchers
new opportunities to use and propose new methods for dental age estimation. However,
the use of tomographs in this study, applying the Kvaal et al method, did not improve the
results. It is recommended to also include teeth with small fillings in studies based on
pulp/tooth dimension ratios, as long as the pulp chamber is not compromised. The aim of
this is to further investigate the application of these different methods on those individuals
who do not have totally sound dentitions.
148
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SECTION FOUR: New technologies in dental age estimation.
PREFACE
The main contribution of this section to the thesis is the study of those methods for age
estimation based on volume reconstruction from dental CBCT. These methods do not
surpass the results obtained from the analysis of dental radiographs, which means that
although there are more advanced imaging techniques, they deserve to be deeply explored
and studied for their application in forensic dentistry for dental age estimation in adults.
Chapter 6 presents a study on three previously proposed methods for volume
reconstruction in dental age estimation and the possible technological and methodological
causes of variation on their results.
Chapter 7 presents an ingenious proposal for age estimation in adults using CBCT from
individuals native to different countries. Such individuals had very different ancestry, and
ethnic backgrounds, thereby challenging one of the established requirements for the
creation of methods for dental age estimation that demand the use and elaboration of
specific population studies and formulae.
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6. Chapter 6. Reliability and repeatability of pulp volumetric reconstruction through
three different volume calculations
This chapter was published as:
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. Reliability and repeatability of pulp volumetric reconstruction through three
different volume calculations. Journal of Forensic Odontostomatology. Accepted for
publication. March 2017.
154
ABSTRACT
Dental age estimation by means of the analysis of dental regressive changes is still a valid
tool in the forensic field. The latest methods are based on the analysis of CBCT and
volumetric reduction of dental pulp with advancing age in adults. These methods do not
show superior accuracy to those based on the analysis of conventional dental radiographs.
Objective: To test the variability of the volume measurements when different
segmentation methods are applied in pulp volume reconstruction.
Materials and methods: Osirix® and ITK-SNAP software were used. Different segmentation
methods (Part A) and volume approaches (Part B) were tested in a sample of 21 dental
CBCTs from upper canines. Different combinations of the data set were also tested on one
lower molar and one upper canine (Part C) to determine the variability of the results when
automatic segmentation is performed.
Results: Although the results show correlation among them (r>0.75), there is no evidence
that these methods are sensitive enough to detect small volumetric changes in structures
such as the dental pulp canal (Part A and Part B). Automatic segmentation is highly
susceptible to small variations in the setting parameters (Part C).
Conclusion: Although the volumetric reconstruction and pulp/tooth volume ratio has not
shown better results than methods based on dental radiographs, it is advisable to
persevere with the research in this area with new developments in imaging techniques.
Key words: Age estimation, pulp volume calculation, image segmentation.
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INTRODUCTION
Since 1950 different methods have been proposed to estimate dental age in adults [1].
Most of them are based on the formation of secondary dentine and the decrease of the
pulp chamber size with age [2, 3]. Methods that have an invasive approach, (for example
aspartic acid racemization and cementum annulation), are not of preference, as they often
require the physical damage of the sample [4]. With the evolution of different diagnostic
imaging techniques, non-invasive methods for dental age estimation have become the
preferred methods [5], starting with the use of periapical dental radiographs, [2, 3] then
panoramic radiographs [6], and more recently cone beam computed tomography (CBCT)
[7].
Micro-Computer Tomography (µCT) was introduced in the early 20th century [8] to
determine age related three-dimensional changes in pulp cavities, from maxillary first
premolar teeth. Consistent with early histological research, µCT findings indicate that a
decrease in pulp volume is not linear. It demonstrates a quicker reduction between 20 and
40 years, and then it slows down thereafter. Further research correlating the ratio
between pulp and tooth volume with the chronological age, using µCT and linear regression
models to estimate dental age in adults, revealed promising outcomes [8].
However, in light of the high radiation doses associated with µCT, only extracted teeth can
be measured in this way [9]. More recently, CBCT has been used for dental age estimation
calculating the volumes from tooth and pulp chamber. Since then, volumetric
156
reconstruction from CBCT with different software has been reported in various studies for
dental age estimation in adults [10-13]. The most recent studies document the use of CBCT
from single- [5, 13] and multi-rooted teeth. [14]
These new methods have not shown superior accuracy to the methods based on dental
radiographs [2, 15]. It is evident that within each type of software there are sensitivity
settings that influence the mathematical approach to measure the baseline volumetric
data. These settings clearly have consequences for the outcome and may well be in part
the cause of the substantial variation. The primary aim of this study was to test the
variability of the volume measurements when different segmentation methods were
applied to pulp volume reconstruction. This study is designed to ensure that the
underpinning assumptions of a commonly used age estimation approach, based on pulp
volume calculation, are as accurate as possible.
MATERIALS AND METHODS
Ethics approval for this study was obtained from the Human Research Ethics Committee of
the University of Western Australia (Ref: RA/4/1/6797). This study has been performed in
accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.
Study sample
A total of 22 anonymized dental CBCTs were used in this study. All were recorded with
therapeutic purposes, with the consent of the participants, and there was no unnecessary
157
or repeated radiation exposure. All images were previously unidentified, and age and sex
of each individual was the only known information. From these, 57% (n=12) were female,
age range 17-63 years, mean age 33.7, and 43% (n=9) were male, age range=15-52 years,
mean age 36.7.
The CBCTs were obtained from the Radiology Department of the University of Kebangsaan,
Malaysia, and the research group INVIENDO from the National University of Colombia. In
both cases, the images were obtained using the 9000 3D Extra-oral Imaging System
(Carestream Dental, Atlanta, GA, USA) which had a 180˚ rotation and a field of view (FOV)
of 50 mm by 37 mm. The radiation exposure parameters were 8-10 mA, 70 Kv, with a slice
thickness of 0.076mm. Images were saved in DICOM format.
The selected tooth to apply the different segmentation approaches was the upper right
canine, or the left when the right was absent (with Federation Dentaire International (FDI)
notation 13 and 23) reconstructing one tooth per subject. Only sound teeth, free of any
restorations with completed apex formation were included. The measurement software
packages used were: ITK-SNAP version 3.4 (open source software, www.itksnap.org) and
Osirix® (OnDemand 3D software CyberMed Inc, Seoul, South Korea).
All segmentations were completed by a single observer (TYM). All data were collated using
Excel (version 2013 Microsoft Redmont, USA) and statistical analysis was completed using R
Core Team version 3.1.3 (2015). (R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.)
158
Description of the method
This study tested the comparative outcome of three different ways of estimating the pulp
volume, dental age indicator used in adults [5, 13, 14]. The tests were carried out on the
root pulp chamber of upper canines (n=21), to calculate the correlation between automatic
[14], and manual segmentation [5] (Part A) (Table 6.1) and cone shape approach volume
calculation [13] (Part B) (Table 6.2). The final part of the study (Part C) (Table 6.3) tested
the variability of the results obtained with different setting parameter values combinations
for automatic segmentation of the pulp canal of one multi-rooted tooth, as previously
reported in the literature [14] and one single rooted tooth. (Graph 6.1)
Part A. Automatic and manual segmentation.
Automatic segmentation was performed using the software ITK-SNAP. (Graph 6.1. A).
Manual segmentation used software Osirix® and its 2D viewer, (Graph 6.1. B), which allows
the observer to go slice by slice and manually select the boundaries of the space to
reconstruct, using the tool polygon. The automatic segmentation process in ITK-SNAP is
called “seed region-growing”. To apply it, the observer sets up a “seed” inside the
structure to reconstruct, in this case, the pulp chamber. This seed grows, and a volume is
finally obtained.
Automatic segmentation of the pulp was generated using the same combination of setting
parameters through the entire sample: Scale of Gaussian blurring: 3.0, edge transformation
contrast: 0.2, edge transformation exponent: 4.0, expansion (balloon) force: 1.0, smoothing
(curvature) force: 0.2, edge attraction (advection) force 2.0. In three cases, the edge
159
transformation exponent needed to be adjusted to 0.05. Regression models were run to
establish which of the setting parameters would have the most significant influence on the
final results. Little changes in the Scale of Gaussian generated the bigger changes in the
final values (p< 0.01).
With manual segmentation two approaches were used. Firstly, every fourth slice was
analysed as for the published method. Secondly, the first and last slices were used as
samples. To analyse the same length of root in the automatic and manual approaches, a
length defined in the automatic approach was set for the manual approach.
Part B. Cone shape geometric approximation
The geometric approximation of the root canal to cone is a simple conservative method,
and has been used for dental age estimation in adults. Using Osirix®, ovals of best fit were
formed in the root canal at the cemento-enamel junction (CEJ) level, following the reported
method [13]. Secondly, instead of best fit ovals, the boundaries of the pulp canal were
drawn using the tool polygon (Graph 6.1, C). The root length was measured from the CEJ
to the apex, (Graph 6.1, D), and finally two different volumes of cones were calculated per
tooth with a mathematical formula.
Part C. Automatic segmentation and different setting parameters combinations
As observed in part A, it is not possible to apply the same combination of setting
parameters values to all teeth with automatic segmentation. Considering the advantage of
this automatic process, [16] twenty combinations of different values for all the setting
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parameters (Table 6.3) were used to reconstruct the pulp chamber of one lower first molar
(FDI 36, Male 23-year-old Malaysian origin, slice thickness 0.2mm) and an upper canine
(FDI 23, Male 31-year-old Colombian origin). The volumetric reconstruction with each
combination was completed twice per tooth. The variation among the volume from the
same tooth was calculated.
Statistical analysis
Shapiro Wilk normality test, mean, standard deviation (SD), paired t-Test and Pearson
correlation coefficient, were calculated to compare the results obtained using the different
segmentation methods (Part A), cone shape volume approach (Part B), and the obtained
results when different parameters are used to do the automatic segmentation of the same
tooth (Part C).
RESULTS
When automatic and manual segmentation using each fourth slice were compared, the
Pearson’s correlation coefficient (r2=0.83), shows a greater correlation between them, than
between automatic and manual segmentation using only the first and the last slices
(r2=0.75) or between the two manual segmentation methods (r2=0.79).
However, this does not mean that manual segmentation using every fourth slice and
automatic segmentation produces comparable results. The paired t test shows that there
is a statistically significant difference between the means of the results of both manual
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segmentations and automatic segmentation (p<0.01).
When comparing the volumes, the manual segmentation produced volumes are larger than
those obtained with automatic segmentation. To facilitate the understanding of this
difference, a simple mathematical analysis was used, taking the obtained volume with
automatic segmentation as 100% of the volume. Then the difference between the volumes
obtained with automatic segmentation and both manual segmentation, were used in a rule
of three to calculate the percentage this difference represents.
Part A. Automatic and manual segmentation
Three data-sets were obtained from the volumetric reconstruction of the root canal of the
canines using the different methods (Table 6.1). The results of this calculation showed that
the volumes obtained using every fourth slice are on average 25% (1% to 53%) larger than
those obtained with automatic segmentation.
Also, using the first and the last slices are on average 57% (12% to 210%) larger than those
obtained with automatic segmentation. The average of the volumes from both manual
segmentation methods is in general 41% larger than automatic segmentation. The volumes
obtained doing manual segmentation of each fourth slice were on average 28% larger than
those obtained using only the first and the last slice. However, some of them were on
average 16% smaller (p>0.05). The mathematical analysis was like the previously
described, but in this case, the volume obtained with manual segmentation using only the
first and last slice was taken as 100% in the rule of three.
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Graph 6.1. Volumetric reconstructions, upper right canine using different methods.
Volumetric reconstruction of tooth 13 from a female individual, 36 years old, using the different methodologies mentioned in this paper. A. Semiautomatic recontruction using ITK-SNAP software. B. Manual segmentation using Osirix ® software. C and D. Cone-shape geometric approximation, following the methodology reported by the author doing area measurement of the root canal at the level of the CEJ (D) and length measurement of the root from the CEJ up to the root apex (C), using Osirix ® software.
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Table 6.1. Volume results of using automatic segmentation (Vol 1), manual
segmentation using just the first and last slice (Vol 2), and manual segmentation each
forth slice (Vol3), of cone beam computer tomography from upper canines. (FDI 13, 23)
Individual Vol 1 (mm3) Vol 2 (mm3) Vol 3 (mm3)
1 10.87 10.6 13.2
2 16.03 17 19.7
3 16.4 20.9 19.8
4 9.309 12.9 14.8
5 5.478 7.1385 8.04
6 11.25 12.5 12.6
7 13.26 25.9 16.3
8 16.72 17 23.2
9 37.01 32.6 41.9
10 16.98 23.4 28.9
11 11.77 19.2 17.7
12 5.857 8.7131 11.7
13 9.107 13.3 28.3
14 17.24 33 29.8
15 12.76 27.5 21.1
16 15.87 16.1 27
17 13.2 19.7 22.6
18 11.61 19.7 16.5
19 24.52 35.3 40
20 15.51 22.1 22.1
21 17.6 29.3 35.5
Mean 14.68 20.18 22.41
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Table 6.2. Cone shape approach results using the tool polygon (Pol) and oval (Oval).
Pulp area (in mm2) at the CEJ level and volume (in mm3) calculation with the measured
root length (in mm).
area Area Pol Area Oval Root length Vol Pol Vol Oval
1 22 20 1.55 11.2 10.2
2 29 30.5 1.46 14.1 14.8
3 28 24.5 1.46 13.6 11.9
4 20 9.85 1.51 10.0 4.9
5 21 16 1.04 7.3 5.5
6 16 13.5 1.56 8.3 7.0
7 46 29 1.86 28.6 18.0
8 37 20.5 1.64 20.3 11.2
9 52 41 1.38 24.0 18.9
10 32 26.5 1.63 17.4 14.4
11 30 17 1.28 12.8 7.2
12 34 16 1.38 15.8 7.4
13 32 22 2.10 22.4 15.4
14 28 14 1.71 16.1 8.0
15 42 28.5 1.79 24.9 16.9
16 27 16 1.71 15.4 9.1
17 25 17.5 1.96 16.2 11.3
18 35 25.5 1.47 17.2 12.5
19 58 44.5 1.73 33.9 26.0
20 39 26.5 1.52 19.8 13.4
21 46 24.5 2.17 33.3 17.7
SD 8.7 10.86 7.45 5.2
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Table 6.3. Setting parameter combinations used in part C.
Repetition
Scale of Gaussian
Edge contrast
Edge transformation exponent.
Smoothing force
Average molar volume mm3
Average canine volume mm3
1 2.14 0.09 4 0.2 38.415 36.58
2 3 0.05 3 0.2 45.775 49.7
3 2.05 0.05 3 0.2 34.525 49.7
4 2.5 0.05 3 0.2 46.075 41.81
5 2.5 0.1 2.5 0.2 49.38 48.87
6 2.5 0.2 2.05 0.2 53.74 48.94
7 2 0.1 2.5 0.2 43.55 39.27
8 2.15 0.09 4 0.2 36.53 40.26
9 2.15 0.09 4 0.3 38.94 39.76
10 2.15 0.09 4 0.35 42 39.38
11 3 0.05 3 0.3 47.29 50.89
12 3 0.05 3 0.35 43.55 48.92
13 3 0.05 3 0.4 44.69 48.9
14 2.05 0.05 3 0.3 38.69 35.98
15 2.05 0.05 3 0.35 38.79 35.89
16 2.05 0.05 3 0.4 38.46 36.04
17 1.5 0.05 2.51 0.2 34.3 31.92
18 1.5 0.05 2.5 0.2 34.95 30.08
19 1 0.1 3 0.2 31.73 29.83
20 2 0.05 4 0.2 36.40 35.10
SD 0.53 0.03 0.59 0.07 5.74 7.12 Variance 0.28 0.01 0.35 0.005 32.94 50.75
Note: There are 3 parameters available in ITK-SNAP software that are not listed, as they were constant for all the reconstructions: Edge attraction force (=2) and step size (=1) and smoothing force which was changed from 1 to 0.5 only for the 18th combination.
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Part B. Cone shape geometric approximation
It was expected to obtain similar area and volume values when using ovals of best fit and
the tool polygon following the outline of the pulp chamber. Unexpectedly, with the tool
polygon the areas and volumes were noticeably larger (50%) than with the ovals (table 6.2).
However, there is a strong correlation coefficient between both measured areas using the
tools oval and polygon (r=0.84) at the CEJ and the volumes (r=0.88).
Repeatability of the automatic segmentation for the first and the second repetition for
both teeth was evaluated with the paired t test (r2=0.7, p=0.99), showing that there is no
statistically difference between both repetitions with a 95% level of confidence. The
average between the obtained volumes in both repetitions was calculated.
The volumes for the molar pulp chamber (FDI 36), ranged from 31.7mm3 to 53.74mm3,
with a SD of 5.7and a variance of 33. For the volumetric reconstruction of the canine (FDI
23), the volume value ranged between 29.8 mm3 to 50.8 mm3, SD=7.12 and variance of
50.75. The SD for the different parameters was not larger than 0.6 and the sample
variance was not greater than 0.3.
Part C. Automatic segmentation and different setting parameters combinations
When the areas using the two different tools are compared the data show a larger
variability and a high SD; this effect is diminished once the volume is calculated. In this
way, the length of the root is what really determines the final volume.
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DISCUSSION
With the introduction of computer vision techniques for medical imaging and their
application in dentistry and forensic sciences, the possibilities to propose methods for age
and sex estimation are almost unlimited. Owing to the apposition of secondary dentine,
the anthropometric assessment of the variation in the ratio between size of the pulp
chamber and size of the tooth is still an acceptable dental age predictor [14].
The aim of this study was to test the variability of the volume measurements when
different segmentation methods are applied in pulp volume reconstruction. This is because
although it would be expected that with volume measurements the results for age
estimation were more reliable, the literature shows the opposite. To find out an
explanation to the lower accuracy of the methods based on volume reconstruction, in this
study, we tested three different methods doing only pulp volume reconstruction.
The methods employed in this thesis, using CBCT, do not seem to be more accurate than
those based on radiographs for dental age estimation in adults, based on the analysis of the
available literature. This is regardless of the sample size of the study, which ranges from 19
individuals, analysing only 12 canines [7] to 403 individuals analysing only the pulp chamber
of first molars [14]. This is clear when the reported accuracy of the different methods is
compared. The mean absolute error using automatic segmentation of the first molar’s pulp
chamber is 6.26 years at best [14]. The cone shape geometric approach of pulp and tooth
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has a standard error of estimation of ± 11.45 years, [13] and finally, manual segmentation
of pulp and tooth, has a prediction interval of ± 12 years [5].
Other methods also using automatic segmentation of canines reported a prediction interval
of 3.47 years at best [17]. When these results are compared with some of the most
commonly used adult age estimation methods using dental radiographs, such as Cameriere
et al. [3] (with reported mean predictor errors of 2.37 years [18] to 11.01 years [19]
(tooth/pulp area ratio)), or the method developed by Kvaal et al. [2] (pulp/tooth-linear
measurements ratios with reported standard estimation errors of ±9.367 years [20]), it is
possible to observe that the use of CBCT and dental structures volume reconstruction, do
not improve the final results for adult age estimation. The relation between the lack of the
accuracy of the above mentioned methods for age estimation [5, 13, 14], and the different
methods for volume reconstruction are presented as follows:
Part A. Manual and automatic segmentation may produce similar results, as observed in
this study (r2=0.83). Manual segmentation is time consuming, difficult to perform and
prone to be influenced by the subjectivity of the observer, and personnel trained in this
aspect is necessary [21]. Additionally, it is not accurate enough to estimate the variation of
the volume in small anatomic structures, such as the root canal, as observed in this study.
Although there are different methods for automatic image segmentation, the first problem
faced in the bio-medical area, is the exclusive dependence on gradient or intensity analysis
without using anatomical information [21]. In the case of automatic segmentation, with
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ITK-SNAP software, although the software chooses which pixels will be included in the
segmentation, the observer finally decides how to adjust the parameters to control the
algorithms in the segmentation. This makes this method prone to a certain degree of
subjectivity from the observers. These parameters may also change from one CBCT to
another.
Unfortunately, in the previous study using this software, the values of the setting
parameters were not mentioned [14]. In this study, it was also observed that although all
the CBCTs were obtained from machines with the same reference, and under similar
exposure conditions (slice thickness, Kv, mA, and time of exposure) and the same
parameters for automatic segmentation, the interaction of the seed region-growing with
the boundaries of the structure to reconstruct may also differ from one CBCT to another.
For this reason, it is not possible to follow the recommendations of the ITK-SNAP
manufacturer, who recommends keeping the same parameters among different CBCT, and
it is neither possible to warrantee the uniformity of the segmentations obtained [14].
In this study, it was also observed that small changes in the values of the setting
parameters can generate significant variation in the final volumes with automatic
segmentation, even though the segmentation was made on the same CBCT, same tooth,
and same anatomic region. The significance of this is that the final volume will be always
the same under the same parameters, in the same CBCT, and anatomic region, but these
parameters generally need to be modified from one CBCT to another, and in the same way,
small changes in the parameters alter the final volume.
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Part B. With the aim of simplifying the measurement of the tooth structure volume, a cone
shape geometric approach was proposed (Part B) [13]. The developers of this method
were aware of the main disadvantages of this proposal: measurements inaccuracy and
subjectivity. They also reported that this method tends to underestimate the real volume
of the tooth structures (56% to 67%), which in theory would not affect the final results
after pulp/tooth ratio that was calculated to estimate the age.
To test this method, the current study used two differ approaches for doing the volume
calculation. The first, following the published methodology [13] displaying ovals at the CEJ,
and a second, selecting manually the outline of the root canal at the CEJ, using the tool
polygon. As observed in the results section, despite the difference between both area
measurements, at the CEJ, once the volume is calculated the difference decreases.
None of these approaches is recommended to do pulp volume measurements, firstly,
because of the subjectivity of the observer, who only counts with the naked eye to display
one or another, and secondly because both bring a distorted representation of the root
canal, ignoring the different variations in its internal shape.
Part C. In this study, there are different parameters that affect the final volumetric
reconstruction of any anatomical region. The scale of Gaussian, or blurrier factor [22] was
the most relevant when doing automatic segmentation. To increase the value of the
Gaussian scale, allows the observer to eliminate certain noises in the image, which affect
the “growing of the seed”. However, the bigger the value the Gaussian scale is, the more
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principal structures, and details will be lost [23]. This would mean that the initial volume of
the pulp chamber will be magnified [16].
Although automatic segmentation is less prone to the subjectivity of the observer than
manual segmentation, in this study it was observed that it is not possible to keep the same
volume reconstruction parameters for all the CBCT, and that minimum changes may
produce significant variations, even though they are done on the same tooth. The volume
obtained with this tool must be understood as an approximation to the real volume of the
structure to measure.
Taking into consideration the reported rate of secondary dentine formation is 6.5 μm/year
for the crown, and 10 μm/year for the root [24], the methods in this study are not sensitive
enough to detect such small dimension changes, generating a big variation of the
measurements, which could explain the greater error of pulp/tooth volume based methods
for age estimation when compared with simpler methods based on linear [2] or area
measurements [3] on dental radiographs.
Previous research in the biomedical area has highlighted the problems related to
semiautomatic segmentation, and specifically, to the process that the software uses to
select which pixels or voxels to be included in the final volume reconstruction. To
overcome this problem, the probabilistic anatomic atlas has been elaborated, which
facilitates the segmentation of an organ of interest [21]. When doing the semiautomatic
segmentation of teeth, and pulp chambers, different obstacles were observed.
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Firstly, owing to the similar density of dentine and bone, and the irregularity of the
periodontal ligament, it was not possible to obtain a volumetric reconstruction of the tooth
as it is for the pulp chamber. This is the reason why the automatic tooth volume
reconstruction was not analysed. Secondly, owing to the large variety in the pulp chamber
shapes in the apical third of the tooth, there was always a leak of the seed region -growing
in to the dentine.
To create a probabilistic atlas for dentistry could help to overcome these issues, and help
the dentist, and forensic dentist to implement more accurate, and easier methods for
automatic segmentation, and volume reconstruction. Thirdly, although the automatic
reconstruction of the pulp chamber of molars may be understood as a simple process, it
may be more reliable to use other methods for age estimation when using molars.
CONCLUSIONS
Based on the results of this study, it is possible to affirm that the volume measurements
with any segmentation method must be understood as an approximation of the measured
structure, and not as the real volume. In the same way, manual segmentation could
produce volume values that are even more inaccurate, and should be avoided in future
studies.
Although the volumetric reconstruction and P/T volume ratio has not shown better results
than methods based on dental radiographs, it is worth to persevere with the research in
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this area with an interdisciplinary team to build software that can reliably reconstruct pulp,
and tooth volumes for forensic purposes.
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ABSTRACT
Objectives: The formation of secondary dentine on the walls of the root canal has been
used as an age indicator in adults. The aims of this study are: firstly, to propose a method
for dental age estimation in adults, regardless of their nationality or ethnicity; and secondly
to test if by volume reconstruction of only a fraction of the tooth it is possible to obtain
linear regression models and a unique equation for dental age estimation.
Materials and Method: Eighty-one anonymized cone beam computed tomography images
obtained from two different population groups were used. Only sex and age information
were kept. One group had a Latin-American background (Colombian individuals aged 23 to
71 years), and the other had an Asian background (Malaysian individuals aged 15 to 58
years). The tooth analyzed was the upper canine. The software used was ITK-SNAP version
3.4 (open source software, www.itksnap.org), to do automatic volume reconstruction of
the cervical third of root canal, and root. The images were shared via online under the
strictest security parameters to guarantee the integrity and safety of the data.
Results: The correlation coefficient between pulp/pulp+tooth volume ratio increased when
data from individuals of both populations were included in the same statistical analysis
(r2=0.42). It is possible to propose a formula for age estimation regardless the origin of the
individual: Age=67.104+(-434.741 x p/pt) (Standard error of estimation=±11.4 years).
Conclusion: It has been established that methods for age estimation must be population
specific. In this study is has been demonstrated that meaningful data may be obtained
from individuals that are ethnically different and widely separated geographically.
Key words: Computed tomography, secondary dentine, age estimation, ethnic variation.
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INTRODUCTION
Much has been said in biological sciences about race and ethnicity since 1775, when
Johann Friedric Blumenbach defined five different races: Caucasians (whites), Mongolians
(East Asians) Malayans (South Asians), Negroids (Black Africans), and Americans (First
Nations) [1]. Since then, different studies followed this structure to analyze, interpret data,
and present results; a phenomenon that has been named “scientific racism” [2].
However, owing to the different nomadic and migration processes that humanity has
experienced across history, this racial classification is less accurate and practical [2].
Nevertheless, in forensic sciences it is still stipulated that the ethnic background of an
individual is of paramount relevance, to formulate a biological profile and to clarify the
identity of living or deceased individuals, next to sex, stature, and age [3].
In terms of age estimation, many methods have been proposed for individuals of different
ages, based on bone and tooth formation or deterioration with age [4]. Methods based on
the radiological analysis of dental development, have high accuracy, due to the genetically
controlled process of tooth formation, which seem to be similar for individuals from the
same group of population [5].
However, the most recent findings suggest that their results may be incurring on a
selection bias called “age mimicry”, [6, 7], which has caused the erroneous need to
generate specific population formulae for age estimation.
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Simultaneously, age estimation in adults, by means of non-invasive analysis, is still a
challenge for scientists of different areas, especially, those who are involved in forensic
investigations. Although different methods have been proposed, there is no consensus
about a unique method to be applied to individuals from different countries, and it has
been claimed that methods for age estimation must be population specific [8] whouthout
testing the use of mixed samples. Additionally, the few changes that bones and teeth have
after-body maturation, are a setback for the accuracy of the existing methods.
One of the first methods for dental age estimation in adults established that the formation
of secondary dentine on the wall of the root canal could be considered an age predictor in
adults [9]. Based on the negative correlation of pulp/tooth ratio size with age, different
non-invasive methods were proposed: linear measurements [10]; area measurements; in
dental radiographs [11]; and lastly volume measurements from dental tomography [12].
The aims of this study are: firstly, to propose a method for dental age estimation in adults,
regardless of their nationality or ethnic background; and secondly to test if by
reconstructing only a fraction of the tooth it is possible to obtain linear regression models
and an equation for age estimation.
MATERIALS AND METHODS
The sample for this cohort study encompasses 81 cone-beam computed tomography
(CBCT) obtained from two different population groups. Latin-American (Colombian
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individuals aged 23 to 71 years, 60% female (n=23) and 40% male (n=15)) and Asian
(Malaysian sample individuals aged 15 to 58 years 46% female (n=20) and 54% male
(n=23)) previously collected for different dental diagnosis and treatment procedures, with
informed consent. All the images were anonymized keeping information about sex and
age.
Table 7.1 shows the age and country of origin distribution. Although the CBCT were
obtained in different institutions, in both cases the reference of the device was the same:
Kodak device, reference K9000-3D (exposure parameters: scanning time: 10.8 s, 3-15 mA,
60-85kVp, field of view FOV: 5.2 cm x 5.2cm to 5.5cm to 5.5cm, 180° rotation, slice
thickness 0.076-0.2 mm).
The tooth analyzed was the upper canine, left or right, one per individual, as previous
studies have shown no right/left difference in tooth development [13]. The reconstructed
root fraction was in all cases 5 mm from the highest point of the vestibular cemento-
enamel junction, towards the root apex, with the aim to include only the cervical third of
the root [12].
Two different proceedings were tested to obtain the pulp/tooth ratio. Firstly, by dividing
the volume of the pulp by the volume of the tooth, and secondly, dividing the volume of
the pulp by the sum of the volume of the tooth and pulp.
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Inclusion criteria
The included roots portions were from sound teeth, teeth with no evidence of physical
trauma, free of active caries, free of evidence of periapical disease, without signs of pulp
pathology, and free of cervical lesion of any nature. The analysis also included teeth with
small coronal fillings, with at least 2 mm of dentine between the tooth restoration and the
pulp chamber, which is assumed to have negative effect on the root portion.
The software used was ITK-SNAP version 3.4 (open source, www.itksnap.org), consistent
with previous studies, doing automatic reconstruction of the root canal and root. In certain
cases, it was necessary to manually correct the semiautomatic root segmentation, as the
software included portions of bone, that were required to be manually deleted. The
measurements were collected by only one observer, who had been previously trained in
the use of this software.
All the data were collected in an Excel spreadsheet, using Excel (version 2013 Microsoft
Redmont, USA), before and after manual correction of the image segmentation. Data
analysis was performed with R Core Team version 3.1.3 (2015). (R: A language and
environment for statistical computing. R Foundation for Statistical Computing, Vienna,
Austria. URL http://www.R-project.org/).
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RESULTS
Pearson correlation coefficient tests were calculated to observe if there was any difference
between the volume values obtained, for pulps and teeth doing automatic segmentation,
and after manual correction slide by slide. There was no significant difference between
both measurements (r2=0.98). The two established proceedings to obtain the pulp tooth
ratio were compared. The second approach, dividing the volume of the pulp by the sum of
the volume of the tooth and pulp, generated a higher correlation coefficient (r2=0.34 vs
r2=0.42).
In the same order, the determination coefficient between the pulp/pulp+tooth ratio (p/pt)
was calculated for the individuals of each group separately (r2=0.26 for the Colombian
sample and r2=0.38 for the Malaysian sample) and for the total sample using the data of
both groups in the same analysis, obtaining a higher correlation coefficient when all the
data are included in the analysis (r2=0.42). (Graph 7.1)
In regard to tooth condition, teeth with small crown fillings, that did not involve the root
portion, as were the used teeth, did not generate any outlier that could affect the linear
regression model (Graph 7.1). Linear regression models were generated to produce a
formula for dental age estimation. The final formula is:
Age=67.104+(-434.741 x p/pt)
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where p/pt is the ratio between the volume of the pulp divided by the sum of the volume
of pulp and tooth. The standard error of estimation (SEE) is ±11.4 years (r2=0.42).
It is necessary to mention, that owed to the age distribution of the sample used for this
study, this formula could not estimate the age if individuals over 67 years of age.
DISCUSSION
It is undeniable that dentistry has made a valuable contribution to anthropological
sciences, bringing insights about human evolution. In the same way, dental analysis has
become an important tool for human identification in forensic sciences. In both fields,
anthropology and forensics, the concepts about racial and ethnic differences have deep
roots and a significant influence in research [14].
However, in a changing world, where day by day the biological boundaries between
individuals of different backgrounds are constantly vanishing, the proposal of methods for
age estimation that are racially or ethnically focused must be re-evaluated.
The last systematic review about Demirjian’s developmental stages of third molars [6] and
the Greulich and Pyle’s bone atlas [7] for age estimation in children and adolescents,
exposes a selection bias called age mimicry, present in numerous publications. This bias
explains the variation, in the accuracy of different studies, which has been wrongly
associated to the population origin and ethnicity of the participants, rather than to the
intrinsic characteristic of the used sample.
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Table 7.1. Distribution of the individuals for age in years and country; Malaysia (Mal)
and Colombia (Col) used for the image segmentation and volume calculation in this
study.
Age range Mal Col Total %
15-20 12 0 12 15
21-30 13 2 15 18
31-40 6 11 17 20
41-50 9 12 21 26
51-60 3 7 10 12.3
61-71 0 6 6 0.7
Total 43 38 81 100%
Graph 7.1. Scatter plot showing the correlation between age and the pulp/pulp+tooth
volume ratio. (P/PT ratio) R2=0.42
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To avoid age mimicry, studies must have a study population with an even age distribution,
large even samples, same number of individuals in each age group, appropriate upper and
lower age limits facilitating the observation of the different age-related changes.
Furthermore, and ideally samples that include data of individuals from different regions, to
conclude whether regional differences are important for age estimation in children [6] and
probably in adults. Subsequently, it is necessary to perform multi population studies in
adults.
The research in this thesis makes a contribution to disclose the population related
differences in age estimation in adults when secondary dentine production is analyzed as
an age predictor.
In terms of age mimicry in this study, it is possible to note that the age distribution is not
even when both samples are analysed separately: 58% (n=25) of the Malaysian sample
belongs to the age range of 15 to 30 years, while for the Colombian sample, 60% (n=23) of
the sample belongs to the age range 31 to 50 years. Once both samples are summed, the
age distribution is more even, as well as the general increase of the total data used to
perform the linear regression analysis, which could explain why the determination
coefficient is higher.
In this study, the production of secondary dentine and the narrowing of the root canal with
age, which is one of the used parameters for dental age estimation in adults, has a similar
behavior in individuals that are not only ethnically different but also geographically
188
separated. Also, that the separate generation of regression models, for each one of the
population groups, would have generated age mimicry, owed to the unequal age
distribution of both samples, as in the Malaysian group the younger group dominates,
while for the Colombian group the middle age dominates (Table 7.1).
By adding both samples it is possible to obtain a more even age distribution and also a
higher correlation coefficient between age and p/pt ratio (R2=0.42). However, for future
studies it is recommended to have a sample with the same number of individuals for the
different populations to analyse per age group, to obtain more reliable results. To follow
up on the current work, further studies will be necessary, to test the proposed formula, and
also, to perform a similar analysis in a much larger sample, that follows the established
requirements to avoid age mimicry (7).
Up to now different methods and formulae have been published to estimate dental age in
adults [15]. Nevertheless, few studies have tested the proposed formulae in groups of
populations different to those included in the original studies. In the few studies that have
done this analysis, it has been suggested that local formulae produce more accurate results
[15].
With the results of the present study it could be possible to affirm that it is necessary to
include the data of individuals of different populations in the same statistical analysis. This
would enable the observation that there is no significant difference between populations
189
or ethnical groups with regards to the production of secondary dentine, and to generate an
equation that can be used regardless the origin of the individual.
Furthermore, there are other factors that can affect the length, area, and the total volume
of the tooth, such as bruxism and attrition [17], among others, that also affect the
production of dentine in the crown and apical third of the root. These factors are not
ethnically related but individual dependent. By analyzing sound cervical root third of
canines, or any other teeth, the problems related to tooth attrition are diminished.
In this study, the maxillary canine was selected as the tooth to analyze, owing to the
reported longer survival, compared to other teeth [18]. It was also preferable to measure
the volume of only the cervical third, as it has been reported that pulp/tooth ratios, had a
higher correlation with age at the cervical root level and that the correlation with age
decreased towards the apex, for different types of teeth, when doing linear [19] or volume
[20] measurements.
In the first studies, that analyzed the production of secondary dentine with age [9], the
methods required not only the use of extracted teeth but also the destruction of the
sample, which is unethical in a modern context. The use of different radiological
techniques has allowed researchers to analyze age indicators in a non-invasive and more
conservative way. The use of CBCT to analyze and obtain the volume of any anatomical
structure is much easier, cheaper and faster, and has great potential for applications in
anthropological and forensic studies.
190
In this study, this radiological technique allowed the observer to separate only a fraction of
the tooth, calculate its volume, and guarantee not only the integrity of the individual but
also the uniformity of the samples size. In terms of accuracy, although the error exceeds
the threshold that must accomplish a method for age estimation in adults (±10) [21] the
results of this study (SEE=±11.4 years) are not so different to previous studies that used
data of individuals from the same country or belonging to the same ethnic group (±12.5
years at best) [22].
In the same way, other studies also based on volume reconstruction has been published.
Never the less, some of them are based only on pulp volume reconstruction [23, 24], or on
a geometrical opproach of rooth canal and root [25]. As their methods are not based on a
clear mesurement of the real volume of the root canal and root, and a pulp/tooth ratio
calculation, their results can not be compared with thos obtained from the present study.
Finally, confirming the tooth selection in our study, the latest study on pulp/tooth volume
ratio calculation for dental age estimation in adults, confirms that the upper canine is one
of the teeth, (next to upper central incsor), that presents a better correlation between age
and pulp/tooth ratio, which encourages future studies based on utilisation of this specific
tooth [26].
CONCLUSION
It has been claimed that in the modern world would testify the end of ethnicity, and that it
changes according to circumstances [13]. This study proposes the use of data from
individuals not only from different countries but also have been historically catalogued as
191
members of different racial and ethnical groups. By calculating the pulp/tooth+pulp
volume of only one part of the tooth there is no significant difference between these two
populations and that is possible to generate a formula to estimate the age for adult
individuals regardless their origin.
192
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GENERAL DISCUSSION.
This thesis emerges as an answer to some observed challenges faced by forensic dentistry
for dental age estimation in adults. The age indicator to do this analysis was the formation
of secondary dentine on the walls of the root canal, which generates a negative correlation
between pulp/tooth ratio with age. As there is a demand for non-invasive methods, this
thesis analyses radiological-based methods for dental age estimation in adults as those
proposed by Kvaal et al., (linear measurements) Cameriere et al., (area measurements),
and the different approaches using volume calculation from cone beam computed
tomography (CBCT).
The above-mentioned methods have been tested in many studies. However, there is no
available systematic review which compares their results and helps forensic dentists to
select a method that can be systematically applied, which was the first observed challenge
in this thesis. To face this challenge, Chapter 1 presents what can be considered the first
systematic review for dental age estimation in adults, following the established parameters
in the Cochrane handbook.
This systematic review discloses some of the weaknesses observed in previous studies as
the lack of consensus for minimum standards for the methodological design of different
studies regarding the materials, methods, minimum sample size, statistical analysis, and
data analysis. Based on this fact, it is possible to state that there is a need to generate
proper methodological guidelines to be followed by the international community, taking in
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account the different requirements to avoid age mimicry, and the over-estimation of age
for young individuals or the under-estimation of age for older individuals, when regression
models are applied, which would guarantee the proposal of more accurate methods as well
as the uniform use of the existent ones. In this way, a proper meta-analysis could be
performed in future studies.
The second observed challenge was the need to test the available methods on individuals
whose dental conditions were different to “totally sound teeth”; to this end, one of the
mentioned methods was used to estimate the age in individuals whose dental conditions
had been affected by the same external factor.
The selected method to do this analysis was that proposed by Kvaal et al. in 1995, owing to
the linear measurements of length and width of tooth and root canal that this method
demands, and the external factor was orthodontic treatment which affects tooth length as
well as the production of secondary dentine. This analysis was perfomed in two papers
following different methodological designs (Chapters 1 and 2) presented in section one.
Section one also defies one of the established parameters for the use and proposal of
dental age estimation methods: the exclusive inclusion of sound teeth, a status that
changes once the individual is exposed to orthodontic treatment, because even though,
these teeth are free from other pathologies, such as caries or periodontal disease, their
integrity is altered once the orthodontic treatment starts.
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No previous study in forensic dentistry, had considered the evaluation of the effects that
orthodontic treatment has on dental anatomy and how these associated dental changes
could affect the accuracy of the available methods.
The hypothesis for this section was that in individuals with orthodontic treatment, the age
estimates would show a considerable over-estimation of age, owing to the root shortening
and the production of dentine associated to this treatment. Before obtaining the results, it
was believed that it would be necessary to propose different standards for dental age
estimation in individuals with orthodontic treatment.
In Chapter 2 different linear regression models were proposed for individuals before and
after orthodontic treatment. The methodological design of this chapter facilitated the
comparison of correlation coefficients of different pulp/tooth ratios, and the standard error
of estimation (SEE) obtained from linear regression models obtained before and after
orthodontic treatment.
Although, for some teeth a higher SEE after orthodontic treatment, in general terms, there
was no significant difference between both observations (Pearson correlation test r=0.58),
with a difference that ranged between -0.69 to 2 years. The results of this chapter also
reassure some previous concepts that are important for the following chapters of this
thesis, as the non-significant correlation between age and the length ratios (Chapter 2
table 2.1), as well as the concept that the more teeth are included to estimate the age of
the individual, the better the results are going to be (Chapter 2, tables 2.3 and 2.4).
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Alike previous studies, that evaluated the root resorption associated to orthodontic
treatment, Chapter 2 also demonstrated that this dental change is evident in dental
radiographs, and affects in a higher percentage upper teeth. Contrary to the expected,
although there are some changes in the morphology of tooth and pulp chamber, these
changes do not alter the accuracy of the linear regression models.
However, Chapter 2 had a debatable point in its methodology: this was a longitudinal study
that observed the same group of individuals before and after orthodontic treatment. To do
a more detailed analysis, that confirmed the findings of Chapter 2, the study presented in
Chapter 3 was designed following the methodology of epidemiological studies for risk
assessment, to test whether orthodontic treatment could be considered a risk factor able
to affect the accuracy of the Kvaal et al method, causing more over-estimation of age.
This methodological design has no precedents in forensic dentistry, making this chapter a
relevant piece for research of dental age estimation in adults. This analysis included data
from different individuals, who were grouped in two cohorts, with the same chronological
age and sex distribution. After age estimation using previously published formulae, a
comparison between age estimation obtained from individuals from both groups,
distributed in equal pairs, was done at the tooth level.
After obtaining the different age estimates, and compare the percentage of observations
where the result showed over- or under-estimation, no significant difference was observed
between both groups (Chapter 3, table 3.1). The respective contingency table was
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elaborated (Chapter 3, table 3.2) revealing that orthodontic treatment could not be
considered as a real risk factor for obtaining over-estimation of age, when the Kvaal et al.
method is used for age estimation in adults (RR=1.0071). It is necessary to mention that
none of the teeth analyzed in this chapter presented severe apical root resorption.
The analysis presented in Chapter 3, is an outstanding contribution to dental age
estimation in adults, as it presents a study design that could be applied to analyze the
effect of other dental conditions on different methods for age estimation. This
methodology could be replicated, including teeth with and without cavities, dental fillings,
or periodontal diseases, to establish whether those teeth are non-suitable for age
estimation of adults.
The fact that this section did not find significant differences among both groups, could
represent two different scenarios: 1. the Kvaal method could be used regardless the history
of orthodontic treatment exposure, or 2. the instrument used to measure the tooth and
pulp dimensions, as well as the statistical analysis are not sensitive enough to detect the
differences between both groups. To clarify which one of the two scenarios is the
applicable, it would be necessary to perform a similar analysis using periapical radiographs,
and data from a larger sample.
Nevertheless, there are some obstacles: the use of periapical radiographs for orthodontic
treatment is not as popular as the use of panoramic radiographs, as they would provide
limited information about the different anatomic structures, for example maxillary sinuses,
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and osseous structures. For that reason, the analysis presented in this section used only
panoramic radiographs.
As the third listed challenge for dental age estimation in this thesis, was the lack of
methods for age estimation in young individuals with absence of third molars, the Kvaal et
al method was tested in a younger population, as presented in Chapter 4. For the analyzed
sample, the Kvaal et al method seems to be a useful tool for younger individuals. However,
owing to the SEE (±4.5 years), it would be necessary to analyse other age indicators, to
establish whether an individual is an adult, using methods with higher accuracy.
To cover the fourth listed challenge in this thesis, Chapter 5 presents a study that explores
new uses and applications of one the existent methods for age estimation in adults. This
chapter presents the first adaptation of the Kvaal et al method on CBCT. For this case,
width measurements only were collected, in sagittal and coronal views. Although the
exclusive analysis of width measurements of root and pulp canal on CBCT also showed
negative correlation between age and pulp/tooth ratio, the accuracy (SEE>10 years) does
not surpass the analysis of dental radiographs with mesio-distal pulp/tooth width
measurements.
Even though the results of the papers presented in Chapters 4 and 5 (section 3), are not as
accurate as expected, the analysis was deemed necessary to be done, exploring different
applications of this method for dental age estimation, especially in the case of the use of
CBCT doing linear measurements. It is necessary to mention that for future studies
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following the presented methodology, it would be necessary to analyze larger samples and
test different statistical methods, not only linear regression models as it was done for these
studies.
On the other hand, the constant advances in imaging analysis and telecommunications,
demand forensic dentistry to evolve and to adapt to new sources of information and
emerging technologies. In this way, Chapters 6 and 7 are clear examples of the application
of one the most recent programs for imaging segmentation on dental CBCT, and illustrate,
how, counting with the support of the international academic community it is possible to
design innovative studies.
The use of CBCT and volume reconstruction of different anatomical structures has led to
the proposal of different methods for identification of individuals. However, when it comes
to their use in forensic dentistry for dental age estimation in adults, the results are limited.
The analysis is more complex and demands more time, than when using dental
radiographs, aspects that could be considered as disadvantages of previously proposed
methods.
To help forensic dentists to face the fifth listed challenge in this thesis: the need to
understand the different technological aspects that affect those methods based on
pulp/tooth volume reconstruction, the study presented in Chapter 6 compares the
previously proposed methodologies, and analyses the possible circumstances that affect
their accuracy.
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Chapter 6, demonstrated that although there are different approaches available to quantify
the volume of root canal, it is difficult to obtain the real volume of this space, also that
regardless the technique used to obtain volume measurements from pulp chamber, there
are more implicit aspects in the software that forensic dentists need to understand and be
aware of, to maintain the objectivity of the proposed methods. In this study, it was also
observed that the method which proved to be more reliable to measure volume was
semiautomatic segmentation using the software ITK-SNAP version 3.4 (open source
software, www.itksnap.org), as it was less likely to be affected by the subjectivity of the
observer.
Based on the findings of the study presented in Chapter 6, the software was used to
analyze a sample that included data from two population groups with different ethnic
backgrounds.
The paper presented in Chapter 7, is a homage to the international community that
collaborated in this research, and an example of how the use of telecommunications is
promoting the generation of innovative methods for forensic sciences, helping researchers
to overcome the geographical barriers, that previously limited the design of studies using
large scale radiological data from different population groups.
This chapter also discusses one of the most recent findings in forensic dentistry as it is a
selection bias called age mimicry, which probably has affected the results of previous
studies for age estimation. This selection bias could be the explanation to the wrong
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assumption that there are population and ethnic differences that affect the accuracy of
past studies.
To avoid age mimicry, the sample needs to meet rigorous conditions that guarantee the
reliability of the results. Although, the paper presented in Chapter 7 could not fulfill all the
required conditions, it presents the pathway forward in proposing a model for inter-
population studies for age estimation in adults.
GENERAL CONCLUSIONS
This thesis confronts some established paradigms for the use of methods for dental age
estimation in adults. Likewise, each one of the chapters that this thesis encompasses,
reveals new concepts, and presents new proposals that might be useful for future studies,
which makes each one of the sections and chapters of this thesis a valuable contribution
for forensic dentistry.
Likely, the existent literature has elaborated some parameters for the design and
application of methods for age estimation. These parameters specify: the study of
individuals from the same population; and the exclusion of teeth with pathologies or dental
procedures. Evidence presented in this thesis challenges these rather limited parameters
which are too restrictive to be used as guidelines. Rather it has been shown that samples
from widely different populations and from teeth which are in various conditions may be
used to generate meaningful data in forensic analyses.
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Despite, the similarities of the study design of previous publications, that followed or
slightly modified the three mentioned methods in this thesis, it was possible to observe
that there are no established protocols for data analysis and the report of the results.
More importantly, there are no parameters that consider the chracteristics of the
individuals included in the study as well as a sample size, which might be big enough, to
simultaneously include individuals with different dental conditions and the uniqueness of
each subject.
Under this frame, it is possible that the main conclusion from section one is that an ideal
research scenario, the study design should ensure the inclusion of individuals with a dental
status different to “totally sound teeth” representing the variability existent in any
population, taking in account the parameters menioned in Chapter 7 to avoid age mimicry
bias.
Section two sends some clear messages:
1. It is necessary to test the available methods for dental age estimation in adults in
individuals with different dental characteristics.
2. Orthodontic treatment is not an obstacle to the application of the Kvaal et al
method.
3. It is necessary to perform similar analyses using periapical radiographs.
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4. The use of CBCT for dental age estimation needs to be thoroughly tested, for linear,
area and volume measurements, and if necessary, discourage its use, due to the
simplicity of those methods using dental radiographs.
5. It is recommended to conduct studies that include individuals from different groups
of population.
After analyzing the results of Section three it is possible to state:
1. The Kvaal et al. method is a validated tool for age estimation, and could be an
alternative for those individuals with agenesis of third molars. However, for the
determination of the age of majority of an individual, it would be advisable to use
the Kvaal et al. method in association with an analysis of other age indicators, such
as skeletal age-related changes.
2. Minor dental changes are not an obstacle to the use of the Kvaal et al method, as
long as they do not affect the root of the tooth.
3. Although CBCT provides more information, the accuracy for age estimation in adults
using the Kvaal et al. method is not better than that provided by dental radiographs.
The main conclusions from Section four are:
207
1. Before proposing a method for dental age estimation using volume measurements,
it is necessary to understand the functioning of the software to be used.
2. Although there are different approaches for tooth volume measurements from
CBCT, the more reliable are those based on semi-automatic or automatic
segmentation.
3. With the new technological advances in telecommunications and imaging analysis,
it is possible to do studies which include data from individuals with different ethnic
backgrounds.
4. Future studies need to follow the stated conditions to avoid the selection bias
called age mimicry, which are:
a. Even number of participants in each age category.
b. Large samples.
c. Well stablished age ranges.
d. Equal numbers of individuals per age range.
e. Individuals from different populations.
5. It is recommended to test the methodology proposed in Chapter7 in a larger
sample, which includes at least two groups of individuals with different ethnic
backgrounds but, with the same age and sex distribution, to ensure the reliability of
the results.
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6. To do a reliable meta-analysis in the future, it is necessary to establish appropriate
standards for the publication of the results and accuracy of different studies.
And finally, the different new approaches and statements presented by this thesis
deserved to be tested, debated, and confronted by future researchers, using innovative
techniques and more developed tools that will be available in the coming years for forensic
dentistry.
Final note: Some of the chapters have been slightly modified after the publication of the
most recent findings about age mimicry (Chapter 1, Chapter 5, Chapter 7).
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APPENDIX 1. Age estimation in adults by dental imaging assessment systematic review.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Kruger, E., & Tennant, M. Age
estimation in adults by dental imaging assessment systematic review. Forensic Science
International Journal. Accepted for publication, March 2017.
Age estimation in adults by dental imaging assessment systematicreview
T.Y. Marroquina, S. Karkhanisa, S.I. Kvaalb, S. Vasudavanc, E. Krugera,*, M. Tennanta
aUniversity of Western Australia, School of Anatomy Physiology and Human Biology, 35 Stirling Hwy, Crawley WA 6009, AustraliabUniversity of Oslo, Department of Oral Pathology and Section of Forensic Odontology, P.O. Box 1109, Blindern, Oslo, NorwaycDepartment of Developmental Biology, Harvard School of Dental Medicine, 188 Longwood Ave, Boston, MA 02115, United States
A R T I C L E I N F O
Article history:Received 26 October 2016Received in revised form 28 January 2017Accepted 17 March 2017Available online 27 March 2017
Keywords:Forensic dentistryAdultsAge estimationDental imagingSystematic review
A B S T R A C T
Importance: The need to rely on proper, simple, and accurate methods for age estimation in adults is still aworld-wide issue. It has been well documented that teeth are more resistant than bones to thetaphonomic processes, and that the use of methods for age estimation based on dental imagingassessment are not only less invasive than those based on osseous analysis, but also have shown similaror superior accuracy in adults.Objectives: To summarise the results of some of the recently most recently cited methods for dental ageestimation in adults, based on odontometric dental imaging analysis, to establish which is more accurate,accessible, and simple.Evidence review: A literature search from several databases was conducted from January 1995 to July2016 with previously defined inclusion criteria.Conclusion: Based on the findings of this review, it could be possible to suggest pulp/tooth area ratiocalculation from first, upper canines and other single rooted teeth (lower premolars, upper centralincisors), and a specific statistical analysis that considers the non-linear production of secondary dentinewith age, as a reliable, easy, faster, and predictable method for dental age estimation in adults. The secondrecommended method is the pulp/tooth width–length ratio calculation. The use of specific populationformulae is recommended, but to include data of individuals from different groups of population in thesame analysis is not discouraged. A minimum sample size of at least 120 participants is recommended toobtain more reliable results. Methods based on volume calculation are time consuming and still needimprovement.
© 2017 Elsevier B.V. All rights reserved.
1. Introduction
Age estimation is one of the most important characteristicsused to establish the identity of any individual in different legal,forensic, or anthropological research context [1]. To this end,forensic teams depend on osseous analysis based methods, whichhave acceptable results for young individuals or in their earlyadulthood [2], and dental development based methods, which arehighly reliable in individuals under 21 years of age [3]. However,these methods have some disadvantages: the poor resistance ofbones to the taphonomic process [4], and once the individual
reaches the threshold of 21 years of age, and the third molarsdevelopment concludes [3], the currently available dental devel-opment based methods are no applicable. In individuals with thecongenital absence of third molar teeth, this threshold falls downup to 14–15 years of age.
To respond to the need of an ageing population, and with theevident resistance of teeth to the taphonomic process, alternativemethods for dental age estimation in adults have been proposed.Primarily, these are based on the formation of secondary dentine,studied since 1950 [5] and the subsequent narrowing of the pulpcavity, which can be observed in dental radiographs, leading to theproposal of minimally invasive methods. This systematic reviewfocuses on three methods based on odontometric analysis of thepulp cavity, performing length and with measurements [6], areameasurements [7] and lastly volume calculation [8]. The objectiveof this review is to summarise the results of these recently mostcited methods for dental age estimation in adults, to establishwhich method is more accurate, accessible, and simple.
* Corresponding author.E-mail addresses: [email protected]
(T.Y. Marroquin), [email protected] (S. Karkhanis),[email protected] (S.I. Kvaal), [email protected](S. Vasudavan), [email protected] (E. Kruger), [email protected](M. Tennant).
http://dx.doi.org/10.1016/j.forsciint.2017.03.0070379-0738/© 2017 Elsevier B.V. All rights reserved.
Forensic Science International 275 (2017) 203–211
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1.1. Description of the problem or issue
Different methods have been published for dental age estima-tion in adults, based on the pulp/tooth dimensions’ ratios.Nevertheless, the obtained results of the application of some ofthese methods for dental age estimation, in adults from differentpopulation groups, surpass the accepted threshold in forensicsciences which says that the standard deviation of a method foradult’s age estimation should preferable be below a standarddeviation (SD) of years �10 years [9].
1.2. Description of the methods being investigated
The methods for dental age estimation in adults analysed in thispaper were selected based on their minimally invasive nature, notrequirement for the extraction of teeth to be performed, and pulp/tooth ratio calculation which have been applied in individuals fromdifferent populations. Kvaal et al. [6] method is based on theanalysis of linear measurements of the pulp, tooth, and root lengthas well as root and pulp width measurements at three differentroot levels, initially applied on periapical radiographs and later onpanoramic radiographs and tomographs. Cameriere et al. [7,10]method is based on the analysis of pulp and tooth area measure-ments on periapical and panoramic radiographs. Finally, thedifferent methods for dental age estimation in adults based onpulp/tooth volume ratio from cone beam computer tomography[8,11–14] were also included in this systematic review.
1.3. How these methods might work
The included methods in this study are based on a negativecorrelation between age and the pulp chamber size, as well as onthe tooth/pulp ratio calculation, regardless the nature of the usedmeasurements: length/width, area, or volume. In other words, allof them look at the association of one age related phenomenon, asit is the formation of secondary dentine and the decrease of pulpchamber size with age, which has been accepted as an ageindicator, observable and measurable with different dentalimaging techniques. As an ideal, the accuracy of the studiedmethods should not exceed the threshold of a SD �10 years [4,1].
1.4. Why it is important to do this review
The relevance of this review is grounded on the need torecommend a method for dental age estimation with the followcharacteristics: simple, fast, non-invasive, non-expensive, repro-ducible and over all, accurate, that can be systematically used indifferent academic and forensic scenarios. Helping the reconstruc-tion of identity profiles of unidentified deceased individuals oralive individuals with doubtful identity documents.
2. Methods
2.1. Criteria for considering studies for this review
Qualitative analysis of the information: original studies, inhumans, reporting the use of any of the listed methods for dentalage estimation, based on pulp/tooth ratio calculation (length/width, area, volume) that preferably reported intra-inter observercalibration, generating population specific formulae or in case thatdid not, that reported if the obtained results were obtained byusing the method’s author’s original formulae. English or Spanishlanguage that expressed the results in terms of accuracy for dentalage estimation.
Quantitative analysis of the information: same criteria thanqualitative analysis plus the exclusion of studies which sample
included individuals younger than 14 years of age, studies withsmall samples (n < 50), studies using extracted teeth, and studiesthat did not report the use of specific population formulae.
2.2. Search methods for identification of studies
The information was searched though the data-base available atthe University of Western Australia which included the collectionsof:
Directory of open access journals (DOAJ), Medline/Pubmed(NLM), OneFile (GALE), ProQuest, collection, (Web of Science),Science Direct Journals (Elsevier), Social Sciences Citation Index(Web of Science, Scopus (Elsevier)), SocialSciences Citation Index(Web of Science), Wiley (CrossRef), Wiley Online Library. Also,google scholar, by looking at the papers that reference the originalstudy performed by Kvaal et al. Cameriere et al., and those methodsfor age estimation that referred in their methodology the use ofCBCT and volume reconstruction of pulp chamber and tooth.
The search key words were as follow: Kvaal and dental ageestimation; Cameriere and dental age estimation; age; and toothvolume.
The literature search included papers published after thepublication of the original papers of the authors to July 2016, thesearch was conducted during the years 2014 to 2016. In the lack of amanual for systematic review in forensic dentistry, this systematicreview follows the Cochrane handbook for systematic reviews-methodology review, and when possible the RevMan softwarerecommended by the Cochrane handbook (Figs. 1–3 ).
2.3. Data collection and analysis
2.3.1. Selection of studiesThe initial selection was based on the title and then abstract.
Papers with titles that referred the inclusion of only minors wereexcluded (children). Studies reporting also the use of third molarsor developing teeth, were excluded. Studies that included in thetittle also the use of other methods for dental age estimation inchildren were excluded (Demirjian) or any other invasive methodfor dental age estimation were excluded (Diagrams 1–3,Tables 1–3 ).
2.3.2. Data extraction and managementThe collected information was organized in an excel spread-
sheet as follow: Author, year, country, number of participants(male and female), age, intra and inter-observer agreementassessment, imaging technique to obtain the images, measuringinstrument, best correlation coefficient between age and thedifferent age predictors, best result in terms of accuracy perindividual tooth or per set of teeth, when possible, as well asthe highest error recorded by set of teeth or individual tooth(Tables 4–6 ).
2.3.3. Assessment of risk of bias in included studiesTo avoid bias in this systematic review, and to avoid false
positive (declare that a method is more accurate than other whenit is not) or false negative conclusions (declare that a method isless accurate than other when it is not), it was necessary toanalyse the possibility of author bias. This owed to theparticipation of the same authors in repeated publications. Tothis end, the results were analysed comparing individual papers,and then grouping them per author. Additionally, in certain caseswere there were doubts in regards to the origin of the sample,which means the likelihood to find studies that had used the samesample, the authors were contacted to confirm the origin of thesample, and in case that two studies had the same sample, theauthors were asked to suggest which study should be included in
204 T.Y. Marroquin et al. / Forensic Science International 275 (2017) 203–211
the meta-analysis, in case that the study met the criteria for thequantitative analysis. In the same way, to deal with missing data,the authors were contacted via e-mail.
There was another possible source of bias observed in thisstudy: the use of non-specific population regression models andequations, which could cause the judgement of a method as no orless accurate. To overcome this issue, only studies using specificpopulation formulae were used in the quantitative analysis.
3. Results
3.1. Kvaal et al. [6] (29 Papers, n = 3254)
3.1.1. Qualitative analysisThe original paper about Kvaal et al. [6] method was published
in 1995. Since then, this method has been applied to a globalsample of 3254 individuals from 12 different countries (Graph 1,Table 1). The initial methodology suggested the use of periapicalradiographs from six different teeth, using vernier callipers tomeasure the maximum tooth length, the pulp length and rootlength, and a stereomicroscope with a measuring eyepiece to thenearest 0.1 mm to measure pulp and root width at three differentlevels previously described by the author of this method [6]. Justfew studies have followed the original methodology with slightadaptations [1,6,9,16–19]. In 2005, this method is applied onpanoramic radiographs (20), which became popular [21–35]. Theuse of digital imaging in dentistry also introduced the use ofdifferent software to perform the odontometric measurements.The most commonly used software are: Adobe Photoshop(different versions n = 5), Image J (n = 4) and Kodak dental imagingsoftware (n = 2). From those studies that tested the effect of sex onthe accuracy of the age estimated, 3 found that sex does not affectthe models [16,20,31] and 2 that it does [19,24]. In the original
Fig. 1. Flow chart of the study selection for Kvaal et al. method.
Fig. 2. Flow chart of the study selection for Cameriere et al. method.
T.Y. Marroquin et al. / Forensic Science International 275 (2017) 203–211 205
study, sex was included as a factor for the mandibular lateralincisor, indicating that pulp cavity size changes occurred faster inmales, as females need another 6 years to get the same age asfemales for this tooth [6].
3.1.2. Quantitative analysisFrom the total sample, only 16 papers met the inclusion criteria
for the quantitative analysis (Table 4). The most accurate result(SD = 5.6, r = �0.95) was obtained from panoramic radiographsusing Hipax program (version 3.01) software, 168 participants(95 female and 102 male) in a Caucasian group [20] The larges errorreported error was SEE > 13 years r2 = 0.1 [16,36] obtained from thelower canine, following original Kvaal methodology on periapicalradiographs [36] and the Adobe Photoshop 6.0 software inpanoramic radiographs [16].
Kvaal et al. measurements have been reported to have a highdegree of intra and inter-observer agreement indicating thereproducibility of the measurements, even in those studies thatdid not follow the original methodology. Only one study reportedsignificant differences in regards to the root length and pulp widthat the level B and root width at the level A measurement, althoughthis study reported a SEE = �13.8 (r2 = 0.38), the average error ofage estimation was �18–21 years using periapical radiographs[36].
Note: the studies that did not meet the inclusion criteria for thequantitative analysis also reported high intra and inter-observer
agreement [32–34], One study reported that the lower lateralincisor produced lower intra-observer correlation [33], and one ofthem affirmed that the use of stereomicroscope improve theaccuracy of the age estimates [9].
Fig. 3. Flow chart of the study selection for methods based on volume calculation.
Table 1Total studies reporting the use of Kvaal et al. method.
Author Year Country Totala Age
Kvaal et al. [6] 1995 Norway 100 20–87Kvaal et al. [17] 1999 Sweden 21 20–60Willems et al. [9] 2002 Belgic 29 26–85Soomer et al. [1] 2003 Caucasian 20 14–95Bosmans et al. [21] 2005 Belgic 197 19–75Paewinsky et al. [20] 2005 Germany 168 18–81Meinl A. [32] 2007 Austria 44 13–24Avendaño et al. [19] 2009 Colombia 107 21–50Landa M. [33] 2009 Portugal 100 14–60Shetty et al. [16] 2010 India 100 20–70Sharma et al. [72] 2010 India 50 15–60Saxena. [31] 2011 India 120 21–60Saxena et al. [41] 2011 India 160 21–60Chandramala et al. [22] 2012 India 100 20–70Kanchan et al. [36] 2012 India 100 25–77Agarwal. [18] 2012 India 50 20–70Erbudak et al. [30] 2012 Turkey 123 15–57Thevissen et al. [34] 2012 Belgic 450 15–23Limdiwala et al. [23] 2013 India 150 20–55Parkin et al. [29] 2013 India 30 15–60Kostenko. [73] 2013 Ukraine 64 –
Karkhanis et al. [25] 2014 Australia 279 20–62Misrlioglu et al. [26] 2014 Turkey 114 17–72Patil et al. [70] 2014 India 200 20–50Ayad et al. [24] 2014 Sudan 99 15–30Muszynska et al. [35] 2015 Poland 3 –
Marroquin et al. [27] 2016 Australia 74 12–28Mittal et al. [28] 2016 India 152 14–56Rajpal et al. [71] 2016 India 50 15–5729 papers 12 countries 3254 12–95
a Number of individuals reported in each study. Sample size.
Table 2Total studies reporting the use of Cameriere et al. method.
Author Year Country Totala Age
Cameriere et al. [7] 2004 Italy 100 18–72Cameriere et al. [53] 2006 Italy 33 –
Cameriere et al. [10] 2007 Italy 100 20–79Cameriere et al. [37] 2007 Italy 100 20–79Cattaneo et al. [65] 2008 Ethiopia 1 52Cameriere et al. [38] 2009 Portugal and Italy 229 20–84Singaraju et al. [39] 2009 India 200 18–72Babshed. [4] 2010 India 178 20–70De luca et al. [2] 2010 Spain–Italy 73 –
Babshed et al. [51] 2011 India 61 21–71Cameriere et al. [74] 2011 Italy 90 50–79Jeevan et al. [40] 2011 India 228 16–72Saxena [31] 2011 India 120 21–60Vodanovic et al. [66] 2011 Croatia 192 –
Zaher et al. [42] 2011 Egypt 144 12–60De luca et al. [52] 2011 Mexico 85 18–60Cameriere et al. [43] 2012 Spain 606 18–75Cameriere et al. [47] 2013 Portugal 116 18–74Charis et al. [44] 2013 India 120 20–70Cameriere et al. [47] 2013 Portugal 116 18–74Azevedo et al. [45] 2014 Italy 81 19–74Misirlioglu et al. [26] 2014 Turkey 114 17–72Azevedo et al. [45] 2015 Brazil 443 20–78Ravindra et al. [48] 2015 India 308 9–68Cameriere et al. [75] 2015 Italy 70 20–70De Angelis et al. [68] 2015 – 1 –
Fabbri et al. [67] 2015 Italy 18 –
Sakhdari et al. [49] 2015 Iran 120 >12Torkian [76] 2015 Iran 120 >1229 papers 11 countries 4167 12–79
a Number of individuals reported in each study. Sample size.
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3.2. Cameriere et al. [7] (29 papers n = 4167)
3.2.1. Qualitative analysisThe original paper documenting Cameriere et al. method [7]
was published in 2004. In this systematic review, 29 papers usingthis method were found, having a global sample of 4167 individualsfrom 11 countries (Graph 2, Table 2). This method was initiallyapplied to digital panoramic radiographs, using (AutoCAD2000,Install Shield3.0, 1997) and different versions of this software havebeen used in 11 studies. The most used software to perform thepulp/tooth area measurements is Adobe Photoshop (13 studies).This method was designed to be applied in single rooted teeth,especially canines, but it has also been tested in premolars andcentral and lateral incisors. From those studies that assessed theeffect of sex on the regression models, the vast majority reportedthat sex does not affect the regression model [4,7,26,31,37–46].Only 4 studies reported that sex affect the regression model [47–50].
3.2.2. Quantitative analysisTwelve studies met the inclusion criteria for the quantitative
analysis (Table 5). The use of this method has shown a standarderror of estimation (SEE) from �1.2 [42] to �12–13 years (r = 0.2–0.4) [51] From these studies, 2 reported a median error < � 5 years[7,38], 6 studies reported an error from �5 to �8.5 years [26,40,42–44,46], and three studies reported an error from �10 to �13 years[4,47,51]. From the included studies in the qualitative analysis, onlyone reported significant intra-observer differences in lateralincisors and first premolars (p < 0.05) [51].
Note: all the studies that did not meet the inclusion criteria forthe qualitative analysis and that did intra and inter-observercalibration, reported high intra inter-observer agreement[37,49,52,53].
3.3. Volume (16 papers n = 2444)
3.3.1. Qualitative analysisOwed to the low number of studies doing pulp/tooth volume
reconstruction, in the qualitative analysis those studies usingextracted teeth were included. The first study doing pulp/toothvolume reconstruction reported the use of micro-focus X-ray in2004 [8]. In this systematic review, 16 studies were found using thepulp/toot volume reconstruction, by means of micro-focuscomputer tomography, CT scan or CBCT, and the use of differentsoftware to do manual or semiautomatic volume reconstruction,
such as Tri 3D Bon, Mimics1, ITK-SNAP 2.4, Osirix, Amira amongothers, in a global sample of 2444 individuals from 7 countries(Graph 3, Table 3). However, the methodology of some of themrequire the use of extracted teeth [8,12,13,54,55]. In regards to theeffect of sex on the regression models, 9 studies reported that sexhas no effect [8,14,26,54,56–60]. 3 studies reported that the modelsare more accurate in female than in male, having a higherdetermination coefficient for women than form men [12,61,62], asfollow: R2 0.6 for males and R2 0.7 for females [12], or R2 = 0.29 formales and R2 = 0.15 for men [61] and R2 = 0.67 for male andR2 = 0.75 for female when the mandibular central incisor is used orR2 = 0.56 for male and R2 = 0.58 for female when the secondpremolar is used. Two studies, which only reconstructed the pulpcavity volume, also reported significant difference between toothtype and sex [63,64], One of them found a significant difference inthe volume between the volume of both genders (p = 0.028 < 0.05)and a stronger relation between pulp chamber and age for female(R2 0.6) than for male (R2 0.5) [63]. The other one reported asignifficant difference in volumebetween genders for 12 types ofteeth (p = 0.000) [64].
3.3.2. Quantitative analysisFour studies meet the inclusion criteria for the qualitative
analysis. The error of these studies variates between �3.47 years[58] to �28 years [59]. It was reported high intra-inter-observeragreement [60]. Among those studies that did not meet theinclusion criteria for the quantitative analysis, seven studies alsoreported high intra-inter-observer agreement [8,11–14,57,63,64].
4. Discussion
Age estimation in adults is a challenge in all forensic contexts,especially in cases that require the use of non-invasive methods.The formation of secondary dentine and the non-linear narrowingof the root canal with age [11], is one age predictor measurable indental radiographs and tomographs, leading to the proposal ofdifferent methods for age estimation in adults as an alternative tomore invasive methods and as a complement to osseous analysis[2,17,35,65–68].
In the same way, many methods have been suggested for dentalage estimation in adults. Nevertheless, there are few availablestudies that compare their accuracy [69]. In the lack of a consensusto uniformly apply a method for age estimation in adults, the needto perform a systematic review seemed to be evident. Thissystematic review summarises and compares the results of some ofthe most used methods for dental age estimation in adults,performing a qualitative and quantitative analysis.
In terms of the qualitative analysis, it has been reported thatthere are no significant differences between right or left teeth[14,57]. Another aspect to test among the different papers was theeffect of sex of the different methods. Although not all the includedstudies assessed the effect of sex on age estimation, those that did(n = 38), 71% (n = 27) affirm that sex has not statistically significanteffect on age estimation, when pulp/tooth ratio is calculated.However, if only pulp volume is measured and used as ageindicator, there is a significant difference between the accuracy formales and females [63,64].
In the light of the evidence one could suggest that ratiocalculation not only diminishes the effects of tooth magnificationin dental radiographs, as reported by Kvaal et al. [6], but alsoreduces the effect of sexual dimorphism related to tooth size. Theage of the participants is also another relevant aspect to include, inthis systematic review those studies including participants under14 years of age where excluded for two main reasons. First, thereare other methods more reliable for aging teenagers and infants,and second, before 14 years of age, not all the teeth have completed
Table 3Total studies reporting the use of volume calculation.
Author Year Country Totala Age
Vandervoort et al. [8] 2004 Belgic 52 24–66Yang et al. [11] 2006 Belgic 19 23–70Someda et al. [12] 2009 Japan 155 12–79Agematsu et al. [62] 2010 japan 258 teeth 20–79Aboshi et al. [13] 2010 Japan 50 20–78Star et al. [56] 2011 Belgic 111 10–65Tardivo et al. [57] 2011 France 58 14–74Jagannathan et al. [14] 2011 India 188 10–70Sakuma et al. [54] 2013 Japan 136 14–79Tardivo et al. [58] 2014 France 210 15–85Sasaki et al. [55] 2014 Japan 363 15–70Mendonca et al. [61] 2015 Brazil 72 22–70Ge et al. [63] 2015 China 403 12–69De Angelis et al. [59] 2015 Italy 91 17–80Pinchi et al. [60] 2015 Italy 148 10–80Ge et al. [64] 2016 China 240 16–6316 papers 7 countries 2296 10–85
a Number of individuals reported in each study. Sample size.
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the apex closure, which by definition, is a requirement for theformation of the secondary dentine [77].
For the qualitative analysis, characteristics related with samplesize and inclusion criteria stablished in different studies werecompared. As compared to previous efforts, we did not find asignificant correlation between sample size and the accuracy of themethod, when all the data were analysed together (r2 = 0.1, p-value<0.05, sample size of the analysed studies n = 50–604) or when thedata were analysed individually for each method. It is necessary tohighlight that from the studies included to perform this analysis(n = 30) only 4 (13.3%) had a sample smaller than 100 individuals(n = 50–91 individuals), which may suggest that in any study forage estimation the minimum sample should include data from atleast 100 participants, or over 100 teeth from different individualsin those studies using only one tooth type. Some of the excludedstudies for the quantitative analysis, fail in this aspect[56,57,61,62], including data from several teeth of the sameindividual and counting them as different samples, which mayaffect the reported results.
A previous study recommended a minimum of 120 participantsto achieve 80% of power and 5% of significance [31]. One almostuniversal inclusion criteria, among the papers, was the use of onlytotally sound teeth. Only two studies did not follow this parameter,using teeth with cervical lessons to do volume calculation [55]. or
using panoramic radiographs that did not meet the inclusioncriteria suggested by Limdiwala et al. [23]. Both of them found notsignificant effect of these situations on the accuracy of the results.
Another aspect to consider, is the description of the differentmethods, in terms of the procedure to measure the different pulp/tooth dimensions, as well as the statistical processing of the data.In certain cases, it was necessary to re-read the papers severaltimes to understand the proposed methodology and how theaccuracy was reported.
In the quantitative analysis two main characteristics werecompared among the studies: repeatability of the measurements,in terms of intra and inter-observer agreement and their accuracy,reported as standard error of estimation (SEE), mean absolute error(MAE) or standard deviation (SD). It is necessary to mention thatowed to this variety in the approach to evaluate and to report theobtained accuracy, it was not possible to perform a deeperstatistical analysis, a meta-analysis, to confirm that one methodwas superior to another, however in this review we found that inaverage, the studies using pulp/tooth area ratio reported a lowererror (Tables 4–6).
All the studies reported significant intra- and inter-observeragreement, regardless the used method and the measuringinstrument, which suggests that after adequate training any ofthese methods is reproducible. However, in regards of the
Table 4Kvaal et al. method. Studies included in the quantitative analysis.
Study Sample Measuring instrument SEE � years per tooth or group of teeth (FDI)
6_teeth upper lower 11/21
12/22
15/25
32/42
33/43
34/44
11/21_32/42
13/23
Kvaal et al. [6] 1995, Norway 100 PER20–87 years
Stereomicroscope andVernier callipers
8.6 8.9 9.4 9.5 10 11 10.5 11.5 11.5
Bosman et al. [21] 2005,Belgic
197 OPG19–75 years
Adobe Photoshopsoftware
9.5 9.2 9.9 9.7 9.8 9.3 11.6 8.2 8.1
Paewinsky et al. [20]a 2005,Germany
168 OPG14–81 years
Hipax program 5.6 6.4
García et al. [19] 2009Colombia
107 PER21–50 years
Scion Image software 7.1
Ranjani et al. [16] 2010, India 100 PER20–70 years
SV- 4 mini slide viewer,digital Vernier callipers,Stereomicroscope
10.5 10.2 11.8 11.5 12.4 11.8 12.7 13.3 11.8
Erbudak et al. [30] 2012,Turkey
123 OPG14–57 years
Image J software 10.01 10.12 8.73 8.82
Saxena et al.b [41] 2011, India 120 OPG21–60 years
AutoCAD2005 software 3.63
Kanchan-Talreja et al. [36]2012, India
Group A47 PER25–75 years
Adobe Photoshop software 12.08 12.08 12.4 12.79 13.25 11.87 13.3 13.28
Group B43 PER25–77 years
11.9 11.27 12.46 11.17 13.4 12.62 13.43 13.89 12.75
Limdawala and Shah [23]2013, India
Group A100 PER25–50 years
Kodak Dental ImagingSoftware
8.3 8.21 9.09
Group B50 PER25-50 years
9.45 9.5 9.88
Misirlioglu et al. [26] 2014Turkey
144 OPG17–72 years
Easy-Dent PC software 5.88 7.36 7.52 6.94
Patil et al. [70] 2014, India 200 PER20–50 years
Image-Pro Plus II software 6.5
Karkhanis et al. [25] 2015,Australia
200 OPG20–62 years
Image J software 8.99 9.6 8.36 9.36 9.64 9.52 10.22 10.9 10.53
Mittal et al. [28] 2016, India 152 OPG14–60 years
VistaScan DBSWIN software 7.97 8.59 7.51 8.15 8.53 7.89 8.85 7.95 7.58
Rajpal et al. [71] 2016, India 50 PER15–57 years
Kodak Dental ImagingSoftware
6.42 7.3 7.84
PER = periapical radiographs. OPG = panoramic radiographs. Tooth numeration FDI (Federation Dentaire International).a Error reported as standard deviation.b Error reported as the difference between the chronological age and the estimated.
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simplicity of the technique, and the access to the required tool tomeasure and to calculate the respective pulp/tooth ratio dimen-sions, Kvaal et al. and Cameriere et al. are more convenient, usingperiapical radiographs or panoramic radiographs, as the radiologi-cal technique does not affect the accuracy of the measurements, aslong as the quality of the image allows the observer to clearlyobserve the boundaries on the root canal and tooth surface [23].The volumetric reconstruction of anatomic structures involves amore technical and time consuming training as well as the use ofmore complex software, that are not always free access. This couldbe considered as an obstacle for the big scale application of some ofthese methods. Likewise, the user spends more time doing thevolumetric reconstruction per tooth, which variates from 4 h [8] to15 min [61], when reported.
Another important aspect in regards of accuracy, is the use ofthe specific population formulae, which also improves the resultsof the age estimates, independently of the used method[14,30,42,46,64,70]. In those studies, using non-specific populationformulae the reported error was notably larger (error > �20 years)[32,33]. However, the use of data from different population in thesame statistical analysis, to generate a unique age estimationequation, is not discouraged [2,21,47]. Furthermore, it has beenreported that the pulp chamber size variation can be detected only
each 10 years, which opens a question mark about the reliability ofthose methods reporting a lower error.
In the specific analysis of Kvaal et al. method, although thismethod required the inclusion of six different single rooted teethper idividual, the use of only one tooth [19], only upper centralincisor [70], canines [26], mandibular teeth [33], or differentcombination of teeth to apply the odontometric analysisdescribed by Kvaal and co-workers [25,27], has also beenreported, with acceptable results (SEE < �10 years). It has alsobeen reported that its accuracy depends on the quality of theimage and on the precision of the measurements [23]. Severalstudies reported that tooth length is not strongly correlated withage [16,18,20,23] as tooth length would depend on tooth wear,bruxism, and food habits, rather than a physiological agingrelated process [16].
In regards to Cameriere et al. method, it only requires the use ofone teeth, and the majority of the studies report the use of canines.However, one study using three different lower teeth (Lateralincisor, canines, first premolars) found that lower canine had thepoorest correlation coefficient with age (r = �0.2) (51). Anotherstudy found more accurate estimations from upper lateral incisors,claiming that the narrowing velocity in the pulp chamber of thistooth is twice faster than in the lower incisors [47].
Table 5Cameriere et al. method. Studies included in the quantitative analysis.
Study Sample Measuring instrumet SEE � years per tooth (FDI)
32/42 11/21 12/22 31/41 32/42 33/43 34/44 35/45 13/23
Cameriere et al. [7]a
Italy, 2004100 OPG18–72 years
AutoCAD2000 3.27
Cameriere et al. [38]Portugal and Italy, 2009
229 PER20–84 years
Adobe Photoshop 4.33 4.24
Babshet et al. [4]India, 2010
178 PER20–70 years
Adobe PhotoshopAutoCAD 2004
10 10
Babshet et al. [51]India, 2011
61 PER21–71 years
Adobe PhotoshopAutoCAD 2004
12.22 12.28 13.08 12.45
Jeevan et al. [40]a
India, 2011228 PER16–72 years
Adobe Photoshop 6.39 4.28
Zaher et al. [42]Egypt, 2011
144 PER12–60 years
AutoCAD2008 2.63 1.94
Cameriere et al. [43]Spain, 2012
606 OPG18–75 years
Adobe Photoshop 6.38 5.75
Cameriere et al. [47]Portugal, 2013
116 PER18–74 years
Adobe Photoshop 7.03 6.64 10.8 10.9
Charis et al. [44]a
India, 2013120 PER20–70 years
Jenoptic ProgRessVersion ss2.7
5.4
Azevedo et al. [45]b
Italy, 201481 PER19–74 years
Jenoptic ProgRessVersion ss2.7
3.05
Misirlioglu et al. [26]Turkey, 2014
114 PER17–72 years
Adobe Photoshop 6.75
Azevedo et al. [45]Brazil, 2015
443 PER20–78 years
Adobe Photoshop 6.41 5.79
PER = periapical radiographs. OPG = panoramic radiographs. Tooth numeration FDI (Federation Dentaire International).***Error reported as mean error.
a Error reported as mean absolute error (MAE).b Error reported as the module of the differences between the chronological and estimated age.
Table 6Volume calculation based methods.
Author Sample Image segmentation method Measuring instrument Accuracy
Star et al. [56]2011, Belgic
111 CBCT10–65 years
Automatic segmentation (threshold),and manual correction
Simplant1 11/21 SD = 12.813/23 SD = 13.115/25 SD = 8.4
Tardivo et al. [58]2014, France
210 CT15–85 years
Semiautomatic Mimics1 13/23 MAE = 3.433/43 MAE = 4.6
De Angelis et al. [59]2015, Italy
91 CBCT17–80 years
Manual Osirix software prediction interval = �28 years
Pinchi et al. [60]2015, Italy
148 CBCT10–80 years
Cone shape approximation Osirix1 software SEE = �11.45
CBCT: cone beam computed tomography; SD: standard deviation; MAE: mean absolute error; SEE: standard error of estimation.
T.Y. Marroquin et al. / Forensic Science International 275 (2017) 203–211 209
Although, the majority of the studies reporting the use of thismethod also mention its creator as part of the authors, which couldgenerate certain bias in the results. It was observed that in thosestudies that did not count with his participation, the results interms of the repeatability of the method and accuracy were similar[26]. In average, Cameriere et al. method reported the lowest error(total average �5.6 years), and a sample of at least 120 individualswas observed as adequate to obtain more accurate age estimates[31].
The combined use of Kvaal et al. width ratios and Camerierearea ratios has been reported on canines from digital panoramicradiographs, finding more accurate age estimates when the pulp/tooth width ratio at level C and pulp/tooth area ratio were usingtogether [31] or when area ratio calculation from canines is usedindividually [26].
In this systematic review we found the following advantagesabout the use of pulpt/tooth area calculation over other methods:area measurement on digital radiographs with different software isfaster, and the most recent study using this method proposes asoftware to do and automatic selection of the borders of the pulpand tooth, which minimizes the required time to obtain the area oftooth and pulp chamber, and reduces the error associated with theobserver, when performing the area selection [75]. Linearmeasurements can also be performed on digital radiographs,but, the observer needs to take nine measurements per tooth, in sixteeth, and calculate several ratios. In the method using pulp/tootharea measurements, only one ratio needs to be calculated andallows the researcher to develop the respective statisticalregression model. In the same way, the use of canines, especiallyupper canines to calculate pulp/tooth area ratio has certainadvantages, as their longer survival, in comparison with otherteeth, less wear, and the big size of the pulp chamber [59]. Also, asobserved in Table 5, there are not only more studies reporting theuse of upper canines to do pulp/tooth area calculation but also,these studies present an acceptable accuracy, in contrast to whatwas reported by Kvaal and Solheim, when doing pulp/tooth length/with ratio calculation who observed that upper canines had thelowest correlation with age, when using dental radiographs ofextracted teeth [77], which was an exclusion criteria in thissystematic review.
Finally, although the use of pulp/tooth volume ratio calculationfrom non-extracted teeth still requires more research. The initialresults of the analysis of pulp volume among individuals ofdifferent age groups, bring important and detailed information tounderstand of the formation of secondary dentine. It has beenreported that the pulp/tooth volume ratios in the cervical areawere more correlated with age, and that this correlation decreasetowards the apex [13]. Also, that the most marked reduction involume ratio was observed between the second and the fifthdecades of life in lower first and second premolars, and betweenthe second and the third decades of life in lower first premolars.[13] This clear findings may enlighten the proposal of future andmore accurate methods for age estimation in adults.
5. Conclusion
The narrowing of root canal caused by the formation ofsecondary dentine is a well-accepted age indicator in adults. Thissystematic review observed that age estimation methods based onpulp/tooth area ratio calculation reported more accurate results,even when one tooth is analysed per individual. However certainconditions need to be fulfilled: a sample of minimum 120 individ-uals, older than 14 years of age, assessment of the accuracy of theobserver, and generation of specific population equation. Theinclusion of data of individuals from different population group inthe same analysis is not discouraged. These studies must consider
in their statistical analysis the non-linear deposition of secondarydentine through life. This systematic review also recommends theuse of dental age estimation methods, firstly pulp/tooth area ratiocalculation of single first, upper canines and other single rootedteeth (lower premolars, upper central incisors) and secondly pulp/tooth length/with ratio calculation, as reported by Kvaal et al., incombination with other methods that include diverse ageindicators to produce a more reliable age estimates. The authorsof this systematic review also recommend future studies to reporttheir results in terms of standard deviation, mean absolute errorand standard error of estimation simultaneously, with this, therewill be more be more homogeneity. Thereby, to perform a propermeta-analysis will be more likely.
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219
APPENDIX 2. Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Changes in age estimation standards secondary to full fixed edgewise
orthodontic treatment. European Journal of Forensic Science, Accepted for publication.
June 2016.
Eur J Forensic Sci ● Jan-Mar 2017 ● Vol 4 ● Issue 1 1
European Journal of Forensic Sciences
DOI: 10.5455/ejfs.225119www.ejfs.co.uk
INTRODUCTION
Kvaal et al. [1] developed a non-invasive method for the estimation of age in adults with the measurement of dimensions of the pulp chamber and tooth length to formulate regression models in the estimation of age. Originally, this method was proposed to be used on periapical radiographs. However, more recent work has focused on the use of the Kvaal et al. [1] method in panoramic radiographs [2-4]. During tooth development, secondary dentin deposition commences once the root formation is complete, and the tooth erupts to the level of the occlusal plane [5]. Annually, the rate of secondary dentin formation has been documented to be 6.5 μm/year for the crown and 10 μm/year for the root [6]. The rate of secondary dentin formation is influenced by external stimuli such as occlusal forces, trauma, and caries [7]. These external factors also generate the production of tertiary dentin [5], which is indistinguishable to secondary dentin on dental radiographs [8].
The estimation of dental age has been a valid tool in forensic and anthropological research [1,9,10]. For younger persons,
including newborns, infants, and adolescents, there are dental age estimation methods, generally based on tooth maturation, which are considered the most accurate to estimate the chronological age in subadults [3,11-13]. In adults, once the root formation is deemed complete, methods for dental age estimation are broadly based on the analysis of secondary dentin deposition and the subsequent narrowing of the pulp chamber [1,6,14]. A potential confounding factor in the estimation of dental age is the high incidence of orthodontic treatment in developed countries [15]. The judicious application of forces is central to successful orthodontic treatment and is well known to induce biological changes in dental hard tissues, including the formation of secondary dentin [7] and root shortening [16]. The corollary being a change in the dental morphological features analyzed in the estimation of dental age in adults [7,17].
Given the potential of the development of tooth structure in adolescents and adult patients to be influenced by the application of orthodontic force, and these structures being the foundation of age estimation methods, and it is important
Changes in age estimation standards secondary to full fixed edgewise orthodontic treatmentTalia Yolanda Marroquin1, Shalmira Karkhanis1, Sigrid Kvaal2, Sivabalan Vasudavan1, Edwin Castelblanco1, Estie Kruger1, Marc Tennant1
Original Research
1School of Anatomy, Physiology and Human Biology, The University of Western Australia, Australia, 2Department of Oral Pathology and Section of Forensic Odontology, University of Oslo, Norway
Address for correspondence: Estie Kruger, School of Anatomy, Physiology and Human Biology, The University of Western Australia. E-mail: [email protected]
Received: April 20, 2016
Accepted: June 15, 2016
Published: March 12, 2017
ABSTRACTObjective: The aim of this cohort study was to evaluate if the side effects of orthodontic treatment have any significant impact when the Kvaal et al., method is used for dental age estimation. The objective of this study was to observe the potential effects of orthodontic treatment on the accuracy of the age estimation, as performed using the Kvaal et al. Standards when it was applied on individuals before and after orthodontic treatment. Materials and Methods: Following the methodological approach of Kvaal et al., odontometric measurements were acquired, and the data were statistically analyzed to develop age estimation regression models. The total number of radiographs analyzed was 182 (644%, n = 58) female and 36% (n= 33) male. The ages ranged from 12 to 50 years for females (mean age 22 years) and 12-52 years for males (mean age 22 years) before starting the treatment. The average length of the treatment was 2.2 years for both females and males. Results: It was observed that the standard error of estimate for the regression models did not change dramatically for the pre- and post-treatment data. Conclusions: It is recommended that similar analyses be performed for other methods of dental age estimation, for example, methods based on cone-beam computer tomography or microfocus computer tomography. These novel approaches, though more accurate, are also potentially more sensitive to dental changes caused by orthodontic treatment.
KEY WORDS: Forensic sciences, forensic odontolgy, adults, dental age estimation, orthodontic treatment, root resorption, secondary dentin formation
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to recognize and quantify the effect. The first aim of this study was to evaluate if the side effects of orthodontic treatment had any significant impact on dental age estimation when using the Kvaal et al. [1] method. The objective of this study was to observe the potential effects of orthodontic treatment on the accuracy of the age estimation as performed using the Kvaal et al. [1] standards when applied on individuals before and after orthodontic treatment.
MATERIALS AND METHODS
Ethics approval was obtained from the Human Research Ethics Committee of The University of Western Australia (Ref: RA/4/1/6797) before commencement. In the design of the study, data collection and analysis have been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki.
Sample
This cohort study consisted of a series of subjects who consecutively presented for orthodontic treatment at a private specialist orthodontic clinic (SV). All panoramic radiographs were acquired from the same machine and in digital format, with the informed consent of the participants. All of the panoramic radiographs were unidentified, and the only information known was the sex and age of the participants at the starting and finishing time of the orthodontic treatment.
Inclusion Criteria
All subjects who had a recorded panoramic radiograph of high quality with respect to factors of image brightness, contrast, and sharpness were included. In addition, all the analyzed teeth were clinically sound with completed root formation and in functional occlusion.
Exclusion Criteria
Any radiographs that did not meet the inclusion criteria or had observable failings (e.g. image distortion, poor contrast, overlap of tooth structure, or improper positioning) were excluded. Teeth with rotations, incomplete root formation, dilacerations, pulpal pathologies, and endodontic treatment and/or restorations were excluded. Teeth with developmental abnormalities in size, shape, and tooth structure, as well as previous pulpal and periodontal pathologies and endodontic treatment, were excluded. Teeth with large areas of enamel overlap between neighboring teeth were excluded in this study.
Sample Population
This study analyzed a total of 182 pre- and post-orthodontic treatment panoramic radiographs from 91 participants, 64% (n = 58) female and 36% (n = 33) male, from a Western Australian population. All the participants presented for orthodontic treatment that, after diagnosis and treatment planning, was completed with fixed appliances. The ages ranged
from 12 to 50 years for females (mean age 22) and 12-52 years for males (mean age 22) before starting the treatment. The average length of treatment was 2.2 years for both females and males. Digital panoramic radiographs were taken as part of routine clinical orthodontic treatment to evaluate the initial condition of the participants and the final treatment results.
Teeth Selection
As established by Kvaal et al. [1], three single rooted upper teeth (with Federation Dentaire International [FDI] notation 11/21, 12/22, 15/35) and three single rooted lower teeth (FDI 32/42, 33/43, 34/44) were measured. Kvaal et al. [1] reported that there are not significant differences between teeth from the left or the right side of the arch. In accordance with this, if one tooth was absent, the contralateral was used, as long as this was observable in a straight position.
Measurement
The measurements were performed using Image J software (version 1.48 19 April 2014 - National Institute of Health, USA). As proposed by Kvaal et al [1], different odontometric measurements were recorded: tooth length, pulp length and root length as well as pulp width and tooth width at three different levels: A (cemento-enamel junction in the mesial surface of the roots); B (midpoint between the points A and C); C (midpoint between the cemento-enamel junction and root apex). After the collection of the figures in an Excel (2013) spreadsheet, a serial of ratios was calculated: (T) tooth/root length, (R) pulp/tooth length, (P) pulp/root length, and root width/pulp width ratio at levels A, B, and C. The ratio calculation and use were proposed by Kvaal et al. [1] with the aim to reduce the effect of magnification and angulation inherent in most radiographs [1,4]. The different mean values calculated with these ratios provided the age estimation predictors (M: Mean value all ratios, W: Mean value width ratios B and C, L: Mean value ratios P and R, W-L: Difference between W-L). The predictors M and W-L were later used to formulate the age estimation models using multiple regression analysis as established by Kvaal et al. [1]. The measurements were completed by a single observer (TYM). All data were collected using Excel (Version 2013 Microsoft Redmont, USA), and statistical analysis was completed using the program R Core Team version 3.1.3 (2015) (R: A language and environment for statistical computing and R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/).
Calibration
Intra- and inter-observer calibration was estimated using five randomly selected panoramic radiographs from the final study sample. These panoramic radiographs were measured on five different days with at least 1 day interval. With the aim to avoid the recall of the measurements and landmarks, five new panoramic radiographs were also measured on each occasion. Data were recorded using the software Image J by TYM and SK. To determine intra-observer precision, three estimates of
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precision were calculated: The technical error of measurement (TEM <1.0), relative TEM (rTEM <5%), and coefficient of reliability were calculated to quantify the inter- and intra-observer measurement error [18].
Statistical Analysis
The strength of linear association between chronological age and the Kvaal et al. [1] dental ratios was determined by Pearson correlation coefficient (r). Following this stage, regression analysis was applied to evaluate the relationship between the ratios and the chronological age. The final results were later used to generate the statistical models for age estimation. To quantify the predictive accuracy of the models, the standard error of estimation (SEE) was used in the cross-validation sample. Multivariable linear regression analyses were used to examine the association between the independent and outcome variables. The outcome variables included chronological age (dependent variable) and the predictors M and W-L (independent variables). Different equations were generated to estimate the chronological age, by individual tooth and by group of teeth, as follows: Three maxillary teeth with M and W-L values (6 predictors) individually calculated for each tooth, and the average of M and W-L for the same teeth (2 predictors). Three mandibular teeth with M and W-L values (6 predictors) individually calculated for each tooth, and the average of M and W-L for the same teeth (2 predictors). All six teeth, with M and W-L values (12 predictors) individually calculated for each tooth, and the average of M and W-L for the same teeth (2 predictors). All regression models were built using the ordinary least squares approach. R2 values were computed to examine the amount of variance explained by the predictor variables. The formula proposed by Preoteasa et al. [19] was used to calculate the percentage of teeth with root shortening.
RESULTS
Measurement Precision
After the estimation of intra- and inter-observer error, the obtained values were as follow: Intra-observer error: TEM <1.0 (0.92), rTEM<5% (2.99%), and R > 0.75 (0.95). Inter-observer error (between SK and TYM) was: TEM <1.0 (0.80), rTEM <5 (2.37), and R > 0.75 (0.98) showing comparable intra- and inter-observer measurement precision.
Age Distribution
The age distribution before orthodontic treatment for females was: 12-19 years (62%, n = 36), 20-39 years (28%, n = 16), >40 years (10%, n = 6), and after treatment, it was: 15-19 years (57%, n = 33), 20-39 years (15%, n = 19), and >40 years (10%, n = 6). For males, before orthodontic treatment was: 12-19 years (52%, n = 17), 20-39 years (42%, n = 14), and >40 years (6%, n = 2), and after orthodontic treatment, it was: 13-19 years (48%, n = 16), 20-39 years (45%, n = 15), and >40 years (6%, n = 2).
The correlation coefficient between chronological age and
the dental ratios was calculated for the data before and after orthodontic intervention [Table 1]. In both cases, the correlation coefficient related with the width ratios (A, B, and C) was more significant than those related with length (P, T, R, and L). As established by Kvaal et al. [1], the predictors M and W-L are required to be included in the final equation for dental age estimation. Based on the Pearson correlation coefficients, it could be observed that after the orthodontic treatment, the significance of the values for the predictor W-L decreased.
Individual tooth regression models and multiple teeth regression models were proposed for individuals that had not received orthodontic treatment [Tables 2 and 3, respectively] and for individuals after finishing the treatment [Tables 3 and 4]. In regards to the models for age estimation using individual teeth, the SEE tends to increase after orthodontic treatment, especially for the mandibular canine, where the increase was ±2 years. Furthermore, while the results for the SEE provided by the mandibular canine showed a lower SEE (±8.26 years) in the data analysis before treatment, the same tooth showed the greatest value of SEE (±10.23 years) for individual tooth analysis after orthodontic treatment.
When multiple regression models were formulated using different combinations of teeth, it is also noticeable that in a few
Table 1: Correlation coefficients between chronological age before(1) and after(2) starting orthodontic treatment and the Kvaal et al.[1] dental ratios
Correlation coefficients before treatment
Tooth number (FDI tooth numeration)
Ratio 11/21 12/22 15/25 32/42 33/43 34/44
P1 0.156 0.079 −0.080 0.085 −0.083 0.205P2 −0.261 −0.137 −0.065 −0.026 −0.220 −0.125T1 0.032 0.034 −0.134 −0.186 −0.237 −0.110T2 −0.162 −0.127 −0.148 −0.098 −0.085 −0.159R1 0.163 0.041 0.076 0.321* 0.174 0.383**R2 −0.099 −0.014 0.130 0.070 −0.143 0.037A1 −0.442** −0.419** −0.422** −0.418** −0.325** −0.168A2 −0.306* −0.388** −0.475** −0.172 −0.209 −0.194B1 −0.439** −0.407** 0.026 −0.211* −0.628** −0.595**B2 −0.440** −0.494** −0.449** −0.221* −0.488** −0.522**C1 −0.347** −0.345* −0.322* −0.185 −0.517** −0.459**C2 −0.349** −0.439** −0.364* −0.320* −0.332* −0.436**M1 −0.130 −0.338* −0.283* −0.194 −0.566** −0.378**M2 −0.308* −0.409** −0.412** −0.227* −0.382* −0.443**W1 −0.448** −0.416** −0.142 −0.237* −0.522** −0.573**W2 −0.450** −0.511** −0.469** −0.299* −0.433** −0.522**L1 0.183 0.074 −0.134 0.193 0.019 0.332L2 −0.223* −0.109 −0.148 0.015 −0.218 −0.076W‑L1 −0.365 −0.329 0.027 −0.327* −0.481** −0.574**W‑L2 −0.013 −0.234* −0.058 −0.227* −0.261* −0.412**
*P<0.05, **P<0.001, NS non‑significant. P: Pulp length/root length, T: Tooth length/root length, R: Pulp length/tooth length, A: Pulp width/root width at level A, B: Pulp width/root width at level B, C: Pulp width/root width at level C and predictors, M: Mean value all ratios, W: Mean value width ratios B and C, L: Mean value ratios P and R, W‑L: Difference between W‑L
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cases the SEE decreased after orthodontic treatment: Maxillary lateral incisor (±0.437), maxillary first premolar (±0.698), the multiple tooth regression models using three maxillary teeth with two (±0.574) and six (±0.613) predictors, and in the multiple regression models using six teeth and two predictors (±0.237). In both circumstances, the multiple regression models using the different teeth combinations improved the accuracy of estimation of chronological age, consistent with previous studies [2].
Root shortening was detected in 62% of the upper central incisors, 53% of upper lateral incisors, 48% of upper second
premolars, 48% of lower lateral incisors, 50% of lower canine, and 51% of lower second premolars, with a formula previously proposed [19].
DISCUSSION
This is the first study to specifically apply the Kvaal et al. method to a group of orthodontically treated subjects, and also the first evaluating the impact of the side effects of orthodontic treatment on one of the proposed methods for dental age estimation in adults based on the formation of secondary dentine and the pulp/tooth dimension ratios. Previous
Table 2: Multiple regression for estimation of chronological age (in years) for individual maxillary and mandibular teeth in subjects before(1) and after(2) orthodontic treatment
Teeth FDI n R R2 Equation SEE±years
11/21(1) 83 0.229 0.21 Age=39.87−76.79(M)−51.75(W‑L) 8.57411/21(2) 83 0.143 0.122 Age=54.50−73.67(M)−30.64(W‑L) 9.06412/22(1) 81 0.186 0.165 Age=68.21−99.54(M)−33.52(W‑L) 8.92312/22(2) 81 0.255 0.236 Age=83.07−128.42(M)−42.68(W‑L) 8.48615/25(1) 58 0.08 0.046 Age=79.8105−81.5881(M)−0.5444(W‑L) 9.99315/25(2) 58 0.213 0.184 Age=90.22−129.66(M)−18.62(W‑L) 9.29532/42(1) 87 0.124 0.103 Age=15.40−37.51(M)−43.05(W‑L) 9.73132/42(2) 87 0.095 0.74 Age=49.10−77.55(M)−37.65(W‑L) 9.89333/43(1) 63 0.476 0.458 Age=111.80−238.35(M)−132.7(W‑L) 8.26033/43 2) 63 0.196 0.169 Age=76.60−159.75(M)−105.79(W‑L) 10.2634/44(1) 68 0.356 0.336 Age=21.67−69.84(M)−69.59(W‑L) 8.40434/44(2) 68 0.312 0.291 73.52−137.96(M)−64.43(W‑L) 8.716
R2: Coefficient of determination. SEE: Standard error of estimation in years. See Table 1 for abbreviations
Table 3: Multiple regression for estimation of chronological age (in years) for the combination of different teeth before orthodontic treatmentTeeth FDI n R R2 Equation SEE±years
3 max 2 pds 50 0.278 0.247 Age=80.40−145.51(M)−47.69(W‑L) 7.7893 max 6 pds 50 0.314 0.219 Age=63.704−6.412(11/21M)−7.216(11/21W‑L)−32.812(12/22M)
−19.332(12/22W‑L)−77.969(15/25M)+10.594(15/25W‑L)7.932
3 mdb 2 pds 46 0.4 0.372 Age=13.11−36.64(M)−19.83(W‑L) 9.1243md 6 pds 46 0.601 0.54 Age=124.528+81.230(32/42M)−7.784(32/42W‑L)
−328.184(33/43M)−121.021(33/43W‑L) −37.503(34/44M)−9.855(34/44W‑L)7.805
6 teeth 2 pds 36 0.45 0.417 Age=133.86−238.98(M)−67.88(W‑L) 7.6096 teeth 12 pds 36 0.729 0.5889 Age=130.727+(15.058(11/21M)+(23.906(11/21W‑L)+61.249(12/22M)−29.091(12/22W‑L)
−100.481(15/25M)−2.441(15/25W‑L)+54.517(32/42M)+3.089(32/42W‑L)−268.438(33/43M)−89.805(33/43W‑L)−41.009(34/44M)‑25.32(34/44W‑L)
6.392
R2: Coefficient of determination. SEE: Standard error of estimation in years. See Table 1 for abbreviations
Table 4: Multiple regression for estimation of chronological age (in years) for the combination of different teeth after orthodontic treatmentTeeth n R R2 Equation SEE±years
3 max 2 pds 50 0.389 0.363 Age=102.46−102.16(M)−63.13(W‑L) 7.2153 max 6 pds 50 0.425 0.344 Age=114.631+(−0.876(11/21M))+(2.218(11/21W‑L))+(−115.748(12/22M))
+(−38.699(12/22W‑L))+(−91.406(15/25M))+(−20.963(15/25W‑L))7.319
3 mdb 2 pds 46 0.337 0.306 Age=98.68−213.10(M)−105.05(W‑L) 9.6323md 6 pds 46 0.447 0.362 Age=42.761(81.109(32/42M))+(1.905(32/42W‑L)+(−111.346(33/43M))
+(−173.252(33/43W‑L))+(−151.769(34/44M))+(−43.162(34/44W‑L))9.232
6 teeth 2 pds 36 0.490 0.460 Age=174.12−288.42(M)−59.22(W‑L) 7.3726 teeth 12 pds 36 0.602 0.395 Age=154.569+9.383(11/21M)+19.718(11/21W‑L)−70.675(12/22M)−39.284(12/22W‑L)
−39.932(15/25M)−4.881(15/25W‑L)+47.114(32/42M)−17.071(32/42W‑L)−58.568(33/43M)−29.183(33/43W‑L)−149.635(34/44M)−0.842(34/44W‑L)
7.803
R2: Coefficient of determination. SEE: Standard error of estimation in years. See Table 1 for abbreviations
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investigations failed to disclose whether subjects had previously received orthodontic treatment. There are well-known biological changes that occur secondary to the application of orthodontic forces including apical root resorption and secondary dentin formation.
External root resorption is one unavoidable, unpredictable, and undesirable sequela [20-22] of orthodontic treatment. The reported frequency of external root resorption is about 100% when it is examined under microscopy. When it is quantified on periapical or panoramic radiographs, the frequency falls to 70%, with a mean reported value of root shortening of 1.42 ± 0.44 mm and 1% to 5% of the cases with a loss of 4mm or one-third of root length [19]. In addition, maxillary teeth are more sensitive than mandibular teeth to root resorption. The most frequently affected teeth, according to severity, are the maxillary laterals, maxillary centrals, mandibular incisors, the distal root of mandibular first molars, second premolars, and maxillary second premolars [21,23], and all these teeth have been used in different methods for dental age estimation in adults [1,2,24]. In this study, a higher percentage of root resorption for upper teeth was also observed.
Confirming the findings of Karkhanis et al. [2], the length ratios (P, T, R, and L ratios) in this study have a non-significant correlation coefficient with age (P > 0.05), and the percentage of negative correlation coefficients [Table 1], closer to −1, is higher in the observed values after orthodontic treatment (23% before vs. 66% after). As the Kvaal et al. method is based on the negative correlation between age and the mentioned ratios, it is possible to observe that after the orthodontic treatment this negative correlation is more evident but not statistically significant. In this study, there was no significant variation in the correlation coefficients of the calculated length ratios with age among the different teeth. Furthermore, as the Kvaal et al. method is based on length ratio calculations, not the linear measurements per se, it is possible that the effect of root shortening on the estimated ages had been diminished when the ratios are calculated.
In terms of secondary dentin formation owed to orthodontic treatment (a phenomenon that has not been as widely investigated as root resorption), there are reports of complete obliteration of the canals in maxillary incisors [25], and in one study analyzing, the tooth changes in terms of root length and pulp chamber within maxillary central incisors (tooth 11 and 21), statistically significant changes in the width of the pulp chamber at the midpoint of the dental root [26] were found, equivalent to the point C in the Kvaal et al. method. [1] Another study using cone-beam computer tomography (CBCT) in maxillary teeth found a statistically significant difference between the volumes before and after orthodontic treatment, with the highest mean volume loss observed in the upper left lateral incisor (3.86 mm3) and the least for the upper right central incisor (3.04 mm3) [7].
In this study, the correlation coefficients of the pulp/root width ratios (A, B, C, and W) maintained their negative correlation with age before and after the treatment, without showing the same variation observed for the length ratios. It would still
be necessary to assess if the root shortening after orthodontic treatment, displaced the location of the reference points B and C toward the crown (where the pulp chamber is wider), and its relation with the observed variation of the SEE before and after orthodontic treatment, which in both cases is acceptable in forensic terms (SEE =±10 years).
CONCLUSION
Our investigation demonstrated an alteration in tooth and pulp chamber morphology and dimension following orthodontic treatment. However, these changes did not serve to significantly influence the validity and accuracy (SEE) of the Kvaal et al. [1] method when applied in the assessment of panoramic radiographs to estimate chronological age. We recommend further analysis of other methods for dental age estimation in adults based on the formation of secondary dentin, such as Cameriere et al. [3], or the more recently proposed methods based on volumetric reconstructions of the tooth and pulp chamber in CBCT [27,28] which could be more susceptible to be affected by orthodontic treatment sequels.
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28. Sakuma A, Saitoh H, Suzuki Y, Makino Y, Inokuchi G, Hayakawa M, et al. Age estimation based on pulp cavity to tooth volume ratio using postmortem computed tomography images. J Forensic Sci 2013;58:1531-5.
Source of Support: Nil, Conflict of Interest: None declared.
226
APPENDIX 3. Orthodontic treatment: Real risk for dental age estimation in adults?
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Orthodontic Treatment: Real Risk for Dental Age Estimation in Adults?
Journal of Forensic Science. Accepted for publication. October 2016.
PAPER
ODONTOLOGY
Talia Yolanda Marroquin Penaloza,1 D.M.D.; Shalmira Karkhanis,1 Ph.D.; Sigrid Ingeborg Kvaal,2
Ph.D.; Sivabalan Vasudavan,1 D.M.D.; Edwin Castelblanco,1 BEcon.; Estie Kruger,1 D.M.D., Ph.D.; andMarc Tennant,1 D.M.D., Ph.D.
Orthodontic Treatment: Real Risk for DentalAge Estimation in Adults?
ABSTRACT: Dental age estimation becomes a challenge once the root formation is concluded. In living adults, one dental age indicator isthe formation of secondary dentine, also associated with orthodontic treatment as well as root shortening. The aim of this study was to establishwhether these secondary effects of orthodontic treatment could generate a statistically significant difference in dental age estimations whenusing Kvaal’s method. The study sample included 34 pairs of pre- and postorthodontic panoramic radiographs, from different individuals withexactly the same age and sex distribution. Females 65%, median age 17.5 years, and males 35%, median age 22.5 years, were included. Afterdata collection, dental age was estimated per tooth using formulae previously published. The risk of obtaining over-estimation of age was calcu-lated. (RR = 1.007). The changes caused by orthodontic treatment do not have any significant effect on age estimation when Kvaal et al.’smethod is applied on panoramic radiographs.
KEYWORDS: forensic science, dental age estimation, secondary dentin formation, adults, orthodontic treatment, root resorption
The analysis of teeth for age estimation has been scientificallyreported since the early 1800’s (1). Methods based on tooth for-mation in juveniles have shown high reliability (2–4). Once theroot formation has finished (generally at the age of 14 years,excluding the third molar) (5), dental age estimation becomes achallenge, partly as a result greater variability in the develop-ment of third molar (6). The most reported noninvasive methodsfor dental age estimation are based on the formation of sec-ondary dentine and the decrease in pulp chamber dimensions.These features are measurable in periapical radiographs (7,8),panoramic radiographs (9,10), micro-focus-computed tomographs(11), computed tomographs (12), and cone beam-computedtomographs (13). These methods proposed different formulae tobe used in specific populations. An important characteristic ofthese studies is that in their analysis, they only included totallysound teeth.It is well known that orthodontic forces generate irreversible
changes on tooth structure, such as root shortening (14) and sec-ondary dentine formation (15). These two biological changes intooth structure may directly affect the features used for dentalage estimation in adults, especially the method proposed byKvaal et al (7). This method is based on the measurement oftooth/pulp length, root canal, and root width at different levels,followed by ratio calculations and linear regression analysis fordental age estimation. It would be expected that with the
mentioned changes, secondary to orthodontic treatment, age esti-mation in participants’ postorthodontic treatment would show ahigher estimation error and higher over-estimation, compared tothat of nontreated participants. If that were to be the case, itwould be necessary to develop specific standards for orthodonti-cally treated participants, not only for the Kvaal et al.’s method(7), but for any method based on secondary dentine formationand the variation of pulp/tooth dimensions with age. In the eventof the results being different to the expected, it would mean thatthe Kvaal’s method could be used despite the evidence of ana-tomic changes related to orthodontic treatment. The aim of thisstudy was to establish whether orthodontic treatment would gen-erate changes in dental age estimations at the tooth level whenthe Kvaal et al.’s (7) method is applied per individual tooth.
Materials and Methods
Ethics approval was obtained from the Human ResearchEthics Committee of The University of Western Australia(Ref: RA/4/1/6797) prior to commencement.
Panoramic Radiographs, Orthodontics, and Dental AgeEstimation
Initially, the Kvaal et al.’s (7) method was proposed to beused on periapical radiographs. However, recent studies havealso applied this method on panoramic radiographs (9,10).Panoramic radiographs have more image distortion than periapi-cal radiographs, but it has been reported that when root resorp-tion associated with orthodontic treatment is measured onpanoramic radiographs, it is significantly higher than when mea-sured on periapical radiographs (16). This study presents the first
1School of Anatomy Physiology and Human Biology, University ofWestern Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia.
2Faculty of Dentistry, Institute of Clinical Dentistry, University of Oslo,P.O. Box 1109, Blindern, N-0317, Oslo, Norway.
Received 4 May 2016; and in revised form 14 Aug. 2016; accepted 18Oct. 2016.
1© 2017 American Academy of Forensic Sciences
J Forensic Sci, 2017doi: 10.1111/1556-4029.13371
Available online at: onlinelibrary.wiley.com
study to see the effect of orthodontic-related changes on age esti-mation, and therefore, no power calculation was achievable.However, based on the size of previous research assessing pulpalchanges associated with orthodontic treatment (17), a samplesize in a similar range was deemed appropriate.
Sample Selection
The study cohort consisted of a series of participants who con-secutively presented for orthodontic treatment at a private special-ist orthodontic clinic (SV). The initial sample for this study was 91participants from a Western Australia population, who had a pre-and post-treatment panoramic radiograph. From the initial sample,a total of 34 pre- and 34 postorthodontic treatment panoramicradiographs were selected, resulting in a final sample of 34 pairsof panoramic radiographs (n = 68). Sample size reduction corre-sponded to the need of age and sex matching between the differentindividuals in each pair, one of them without orthodontic treatmentand the other one with a concluded treatment. Female 65%(n = 22, for both groups), age range 15–50 years old, median17.5. Male 35% (n = 12, for both groups) age range 16–37 yearsold, median 22.5. The minimum length treatment was 1.2 years,the maximum 3.6 years, and median 2.1 years.Intra-observer calibration was performed to test the repeatabil-
ity and reliability of the main observer (TM). All the measure-ments were completed by a single observer (TM), and theanalysis was completed with Image J software (version 1.48 19April 2014—National Institute of Health, Bethesda, Maryland).All data were collated using Excel (version 2013 Microsoft,Redmond, WA), and statistical analysis was completed using theprogram R Core Team version 3.1.3 (2015) (R: A language andenvironment for statistical computing. R Foundation for Statisti-cal Computing, Vienna, Austria. URL http://www.R-project.org/).
Inclusion Criteria
All participants who had a recorded panoramic radiograph ofhigh quality with respect to factors of image brightness, contrast,and sharpness were included. In addition, all teeth included inthe analysis were clinically sound with completed root formationand in functional occlusion.
Exclusion Criteria
Radiographs with observable failings (image distortion, poorcontrast, superposition of tooth structure, or improper position-ing) were excluded. Teeth with pulpal or periodontal pathologiesand endodontic treatment and/or restorations, incomplete rootformation, dilacerations, or rotations were excluded. Teeth withdevelopmental abnormalities in size, shape and tooth structure,or large areas of enamel overlap between neighboring teeth werealso excluded in this study.
Teeth Analyzed
The purpose of this study was to assess the biologic variationeffects of orthodontic treatment at the tooth level. Therefore, thetooth-by-tooth formulae for the Kvaal method were applied(10,18).Following the parameters as provided by Kvaal et al. (7),
three upper and three lower single-rooted teeth were included:one maxillary central incisor (with Federation Dentaire
Internationale (FDI) notation 11 or 21), one maxillary lateralincisors (FDI notation 12 or 22), and one maxillary second pre-molar (FDI notation 15 or 25), mandibular lateral incisors (FDInotation 32 or 42), one mandibular canine tooth (FDI notation33 or 43), and one first premolar teeth (FDI notation 34 or 44).In accordance with the study by Karkhanis et al. (10), panoramicradiographs that presented any combination of the required teethwere included. There is no evidence claiming that the accuracyof the results had varied depending on the use of left or rightteeth. Consequently, in the absence of one of the teeth the con-tralateral was used, as long as they met the inclusion criteria.
Measurements
All the panoramic radiographs were obtained in digital format,and the measurements were performed using the software ImageJ software (developed by the National Institute of Health, USA).According to Kvaal et al. (7), the following measurements wererecorded: tooth, pulp, and root length, as well as the pulp andtooth width at three different levels: A (cemento–enamel junctionon the mesial surface of the roots), B (midpoint between thepoints A and C), and C (midpoint between the cemento–enameljunction and root apex). All the measurements were recordedbefore the sample was categorized into two groups: group prefor panoramic radiographs obtained from nontreated participantsand group post for treated participants, to avoid observation bias.Following the recording of measurements, a series of length andwidth ratios were calculated: tooth/root length; pulp/tooth length,and root width/ pulp width ratio at levels A, B, and C. Theseratio calculations were proposed by Kvaal et al. (7) as it reducesthe effect of magnification and angulation inherent in mostradiographs (7,19). The different mean values from the ratioswere used to obtain age estimation predictors. (M: mean valueall five ratios, W: mean value of width ratios at level B and C,L: mean value of length ratios P and R, W-L: differencebetween W-L) (7). The predictors M and W-L were later used toestimate the age of all the participants.Five randomly selected panoramic radiographs from the final
study sample were used to estimate intra-observer calibration.These panoramic radiographs were measured on five differentdays with at least one-day interval. With the aim to avoid therecall of the measurements and landmarks, five new panoramicradiographs were also measured on each occasion. Three esti-mates of precision were calculated to quantify intra-observermeasurement error and precision: the technical error of measure-ment (TEM), relative technical error of measurement (rTEM),and coefficient of reliability (20).
Statistical Analysis
After the completion of the measurements, dental age estima-tions were calculated using the age estimation equations fromindividual teeth. In participants aged 30 years or older, the equa-tions used were those reported by Karkhanis et al. (10) And forparticipants 29 years or younger, the used equations wereobtained from a different group of nontreated participants(n = 74 aged 12–28 years). Both sets of equations were obtainedfrom a Western Australian population.
Results
For the estimation of intra-observer error, the obtained valueswere within acceptable standards for all the measurements. The
2 JOURNAL OF FORENSIC SCIENCES
intra-observer results were as follows: TEM < 1.0 (0.92),rTEM < 5% (2.99%), and R > 0.75 (0.95).After age estimation per individual tooth, there were a total of
189 age estimates for group pre and 196 estimates for grouppost. The age estimates obtained were then compared betweenparticipants with exactly the same age and sex in group pre andgroup post. In this way, 183 pairs of age estimates wereobtained and compared 1 to 1.For 79% (n = 145) of the total observations, the fluctuation of
the data was the same, regardless whether there was over- orunder-estimation of the age. In terms of over-estimation, in 47%of these observations, the over-estimation was higher after theorthodontic treatment.The fluctuation of the data with regard to the chronological
age of the individual was analyzed per individual tooth(Table 1), showing that there was no significant difference in thepercentages of over- and under-estimation between both groups(Pearson’s correlation coefficient r = 0.78).Although the fluctuation of the data was the same in both
groups, pre and post, there was a clear difference between theages. It was observed that before the age of 25, the large major-ity of results showed a slight over-estimation of age which didnot exceed the reported SEE. In contrast, the majority of ageestimation data obtained from older participants showed under-estimation of the age that notably exceeded the reported SEE.A contingency table (Table 2) was developed to test whether
the secondary effects of orthodontic treatment were a real risk toproduce over-estimation of the age when the Kvaal et al.’smethod is applied. The relative risk calculated was RR = 1.0071(low risk)
Discussion
The reliability of dental age estimation in adults, based on theformation of secondary dentine, has shown superior accuracy toother methods, based on the analysis of other age-related dentalor osseous changes (8,10). However, teeth are subjected to
different changes through life related to pathology as well asbiological, chemical, or mechanical trauma or dental procedures.It has been reported that orthodontic treatment causes mechan-
ical trauma to the periodontal ligament and induces pulpal reac-tions (21). The most frequently reported side effect is externalroot resorption, a process characterized by the destruction of rootstructure (21), with the subsequent diminution of root length(mean reported value of 1.42 � 0.44 mm) (22). Another sideeffect is the reduction in pulp chamber dimensions, owing tosecondary dentine formation (15). With these changes, it wasexpected to obtain significant differences between group pre andpost, with higher percentages of over-estimates of age in treatedparticipants. The analysis of the obtained data facilitated the cal-culation of the potential risk of having over-estimation in partici-pants after finishing the orthodontic treatment (Table 1). Aftercalculating the incidence of over-estimation in groups pre andpost, there was no evidence of association between over-estima-tion of age and orthodontic treatment (RR = 1.0071). However,it is necessary to mention that in this study none of the testedteeth showed signs of severe apical root resorption.According to previous studies, it was found that maxillary
teeth are more affected by root shortening due to orthodontictreatment, specially lateral and central incisors (23,24). In thisstudy, they also presented the higher percentage of under-esti-mates of age for both groups, followed by the mandibular lateralincisor. In the case of under-estimation, it was observed in ahigher percentage in lower canines for group pre and grouppost, 54% and 61%, respectively.Previous studies using the Kvaal et al.’s method and her pro-
posed formulae reported a constant under-estimation of age,from 18 to 20 years (19) up to 47.10 years (25). These studiesdid not use population-specific formulae. In this study, the for-mulae used were obtained from the same Western Australianpopulation. There was a clear-cut line (24 years for both groups)where the estimates would notably exceed the reported SEE (1–5 years), having statistically significant under-estimates. It isnecessary to determine in future studies whether this findingcould be related to the fact that the apposition of secondary den-tine does not occur in a linear manner through life (25), causinga larger decrease in pulp dimensions between 20 and 40 years ofage, than between 40 and 60 years of age (26). A limiting factorto clearly examine this relation in the current study was the lackof individual over 40 years of age.As the main objective of this study was to establish whether
orthodontic treatment would generate changes in dental age esti-mation, and as each type of tooth is affected by different degreesof severity, in this study we used previously published formulaefor dental age estimation for individual teeth rather than per setof teeth or per individual. The use of Kvaal et al.’s (7) individ-ual teeth formulae to estimate dental age has been reported onextracted teeth (27). In the same way, there are other methodsbased on the assessment of a single tooth per individual to
TABLE 1––Comparison of over- and under-estimates obtained per tooth before and after orthodontic treatment. And reported standard estimation error SEEper individual tooth, for participants younger than 30 years (SEE � years (<30 years)) and over 30 years of age (SEE � years (>30 years)).
Tooth 11/21 12/22 15/25 32/42 33/43 34/44
Over-estimation Pretreatment 39% (n = 13) 50% (n = 16) 52% (n = 17) 47% (n = 16) 54% (n = 13) 47% (n = 15)Post-treatment 38% (n = 13) 45% (n = 15) 48% (n = 16) 44% (n = 15) 61% (n = 20) 52% (n = 15)
Under-Estimation Pretreatment 61% (n = 20) 50% (n = 16) 48% (n = 16) 53% (n = 18) 46% (n = 11) 53% (n = 17)Post-treatment 62% (n = 21) 55% (n = 18) 52% (n = 17) 56% (n = 19) 39% (n = 13) 48% (n = 14)
SEE � years (<30 years) 4.344 4.258 4.536 4.465 3.708 3.709SEE � years (>30 years) 9.367 9.648 9.525 10.222 10.903 10.534
TABLE 2––Contingency table to estimate whether orthodontic treatment wasa causal of over-estimation, when the Kvaal et al.’s method is used to age
estimation.
Orthodontic treatment Over-estimation Under-estimation Total
YESPost-treatment
48%n = 94
52%n = 102
n = 196
NOPretreatment
48%n = 184
52%n = 99
n = 189
Total n = 184 n = 201 n = 385
Incidence over-estimation group A = 47.9%. Incidence under-estimationgroup B = 47.6%. Relative risk of presenting over-estimation owed toorthodontic treatment secondary effects when Kvaal et al.’s method is usedfor dental age estimation: RR = 1.0071 (No or low risk).
MARROQUIN PENALOZA ET AL. . EFFECT OF ORTHODONTIC TREATMENT AGE ESTIMATION 3
generate dental age estimation models with acceptable results ina forensic framework (5,7,13).
Conclusion
In our study, orthodontic treatment did not affect the finalresults when the Kvaal et al.’s method was used for dental ageestimation. Although it has been previously established that, touse the pulp complex as a biomarker for general aging, the ana-lyzed teeth have to fulfill the requirements of being in normaland functional occlusion, totally sound and free from dental pro-cedures (7), the real effect of this conditions on methods basedon the formation of secondary dentine, for dental age estimation,has not been tested. The results of our study allow forensic den-tists to use the Kvaal et al.’s method in participants who havehad previous orthodontic treatment, when there are no signs ofsevere apical root resorption.
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15. Venkatesh S, Ajmera S, Ganeshkar SV. Volumetric pulp changes afterorthodontic treatment determined by cone-beam computed tomography. JEndod 2014;40(11):1758–63.
16. Sameshima G, Asgarifar K. Assessment of root resorption and rootshape: periapical vs panoramic films. Angle Orthod 2001;71(3):185–9.
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18. Marroquin TY, Karkhanis S, Kvaal SI, Vasudavan S, Castelblanco E,Kruger E, et al. Determining the effectiveness of adult measures of stan-dardised age estimation on juveniles in a Western Australian population.Aust J Forensic 2017;49(4):459–467.
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Additional information and reprint requests:Estie Kruger, D.M.D., Ph.D.International Research Collaborative – Oral Health and EquityThe University of Western AustraliaNedlands, 6009 WAAustraliaE-mail: [email protected]
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APPENDIX 4. Determining the effectiveness of adult measures of standardized age estimation
on juveniles in a Western Australian population.
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. (2016). Determining the effectiveness of adult measures of standardised age
estimation on juveniles in a Western Australian population. Australian Journal of Forensic
Sciences. Accepted for publication. March 2016.
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ISSN: 0045-0618 (Print) 1834-562X (Online) Journal homepage: http://www.tandfonline.com/loi/tajf20
Determining the effectiveness of adult measuresof standardised age estimation on juveniles in aWestern Australian population
T.Y. Marroquin, S. Karkhanis, S.I. Kvaal, S. Vasudavan, E. Castelblanco, E.Kruger & M. Tennant
To cite this article: T.Y. Marroquin, S. Karkhanis, S.I. Kvaal, S. Vasudavan, E. Castelblanco, E.Kruger & M. Tennant (2016): Determining the effectiveness of adult measures of standardisedage estimation on juveniles in a Western Australian population, Australian Journal of ForensicSciences
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Determining the effectiveness of adult measures of standardised ageestimation on juveniles in a Western Australian population
T.Y. Marroquina* , S. Karkhanisa, S.I. Kvaalb, S. Vasudavana,c, E. Castelblancoa,E. Krugera and M. Tennanta
aSchool of Anatomy Physiology and Human Biology, University of Western Australia, CrawleyWA, Australia; bDepartment of Oral Pathology and Section of Forensic Odontology, Universityof Oslo, Oslo, Norway; cDepartment of Developmental Biology, Harvard School of Dental
Medicine, Boston, MA, USA
(Received 20 December 2015; accepted 15 March 2016)
The estimation of chronological age through assessment of dental radiographs iswell-established and a useful method to assist in the identification of persons inforensic and anthropological scenarios. The objective of our investigation was two-fold: (i) to validate the Kvaal et al. age-estimation method on a sample of WesternAustralian subjects, and (ii) to increase the range of chronological ages to which theKvaal et al. method can be applied. Our sample size included panoramic radio-graphs from 74 subjects (aged 12–28 years). A set of ratios were calculated and thenused to apply different statistical models of linear regression, in order to generate afinal formula to estimate age. The most accurate estimations were obtained from themodels generated by the mandibular canine measurement (SEE ± 3.708 years), andfor the three mandibular teeth (SEE ± 3.388 years). The results indicate that inclu-sion of juveniles did not affect final results, and the method still produced estimatesacceptable in a forensic framework.
Keywords: forensic dentistry; dental age estimation; secondary dentine formation;young adults
Introduction
The accurate approximation of chronological age, secondary to sex determination, is anintegral factor in constructing a biological profile for forensic1 and anthropological pur-poses, including the confirmation of identification at times of mass disasters, crimes,accidents and of unknown remains2−4. Further, the estimation of the chronological agein the living is also needed in situations such as immigration and refugee determina-tions4. Saunders originally proposed the estimation of chronological age based on dif-ferent stages of tooth eruption5; since then, several more methods have been suggestedto estimate dental age in children. Amongst these methods, those that are based on theradiological examination of permanent teeth development, are found to be the mostaccurate6,7 The Demirjian et al.8,9 classification is reported as the best method for den-tal age estimation in children and adolescents thanks to its high observer agreementand correlation between the defined stages and age10. This method has been adapted to
*Corresponding author. Email: [email protected]
© 2016 Australian Academy of Forensic Sciences
Australian Journal of Forensic Sciences, 2016http://dx.doi.org/10.1080/00450618.2016.1177593
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different populations, showing a mean difference between the chronological age andthe dental age of around one year in different studies6,9,11.
The completion of tooth development is marked with the closure of the root apex,with the third molar being the last tooth to complete its eruption and root developmentat approximately 17–21 years of age. Following this stage, the accurate estimation ofchronological age based on dental formation becomes challenging12, leading to thedevelopment of alternative methods of dental age estimation in adults. Bodecker13,identified the relation of the continued apposition of secondary dentine and the subse-quent change in the morphology of the pulp chamber with chronological age. Accord-ingly, several dental age estimation methods have been developed, based on therelation between secondary dentine formation, and the subsequent narrowing andchange in pulp chamber dimensions and shape with age1,2,14,15.
Dental analysis using radiographs for the purpose of age estimation presents numer-ous advantages over other histological and biochemical methods: it is relatively simple,non-invasive and economically viable16. The method developed by Kvaal et al.1 is arelatively non-invasive method and has been validated in diverse populations 17−20.Karkhanis et al.17 applied the Kvaal et al.1 method in a Western Australian populationto develop age estimation standards with acceptable results in a forensic framework(±10 years)2. Originally, the Kvaal et al.1 method was proposed to be applied in anadult population. More recently, the method has been applied in younger populationswith varying degrees of success. The level of error in estimates of ages remains highin younger populations, with Landa et al. reporting a standard deviation approaching15 years20.
The aim of the present study is to validate the applicability of the Kvaal et al.1
method in a younger population (Western Australia sample) and to provide furtherrefinement of the level of variation in younger people. It will also assess the potentialof this method as an additional tool for dental age estimation in juveniles, where meth-ods based on the analysis of tooth development cannot be used.
Materials and methods
Sample selection
The study cohort consisted of a series of subjects who consecutively presented fororthodontic treatment at a private specialist orthodontic office. From the initial sample,74 Western Australians were aged less than 30 years, of those 63.5% (n=47) werefemale and 36.5% (n=27) were male, with a median age of 16 year for both genders.All panoramic radiographs were acquired from the same machine in digital format.Analysis was completed with Image J software (version 1.48 19 April 2014 – NationalInstitute of Health, USA) and the measurements were completed by a single observer(TM). All data was collated using Excel (version 2013 Microsoft, Redmont, USA) andstatistical analysis was completed using R Core Team version 3.1.3 (2015). (R: A lan-guage and environment for statistical computing. R Foundation for Statistical Comput-ing, Vienna, Austria. URL http://www.R-project.org/.)
All subjects with a panoramic radiograph of high quality with respect to factors ofimage brightness, contrast and sharpness were included. Any radiographs that did notmeet this requirement or had observable failings (e.g. image distortion, poor contrast,superposition of tooth structure, or improper positioning) were excluded. All teethincluded in the analysis were clinically sound with completed root formation and in
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functional occlusion. Teeth with rotations, incomplete root formation, dilacerations,pulpal pathologies and endodontic treatment and/or restorations were excluded. Finally,teeth with large areas of enamel overlap between neighbouring teeth were excluded inthis study.
Teeth analysed
Following the parameters as provided by Kvaal et al.1, the teeth analysed were themaxillary central incisors (with Federation Dentaire International (FDI) notation 11 and21) lateral incisors (FDI notation 12 and 22), second premolars (FDI notation 15 and25), mandibular lateral incisors (FDI notation 32 and 42), mandibular canines (FDInotation 33, and 43) and first mandibular premolars (FDI notation 34 and 44). In theoriginal study, Kvaal et al.1 analysed only those periapical radiographs from individualswhere all the six teeth were present and suitable for examination. In the present study,panoramic radiographs with any combination of the required teeth available for mea-surement were included. Previous research1,17,19 has demonstrated the absence of bilat-eral asymmetry in the deposition of secondary dentine. Consequently, teeth from eitherside that fulfilled the inclusion criteria were analysed for the purpose of developing ageestimation standards.
Measurements
Odontometric data were acquired following the methodological approach of Kvaalet al. 1. In this way, the data were obtained from measuring: the maximum tooth length(from the incisal border or cusp tip to the root apex); the maximum pulp length (from thepulp chamber roof to the root apex); and the maximum root length (from the cemento-enamel junction – CEJ – on the mesial surface of each tooth to the root apex). The pulpchamber and root width measurements were collected at the points A (CEJ), B (mid-pointbetween the points A and C) and C (mid-point between the CEJ and root apex).
Measurement precision
A pilot set of 30 panoramic radiographs, which were not included in the final analysis,was used to perform initial training and benchmarking to an expert in the field (SK).Six of the 30 radiographs were measured on six different days, in addition to four ran-domly selected panoramic radiographs, thus resulting in the analysis of ten panoramicradiographs per day. Based on this, intra- and inter-observer error calculations were per-formed17. The measurements were acquired from all the panoramic radiographs with aminimum of one day between each session to minimise the possibility of memorisingreference points and/or measurements in each observer. A second intra- and inter-observer calibration was performed using five randomly selected panoramic radiographsfrom the final study sample, and recording the measurements on five different days,also using four additional panoramic radiographs per day, to avoid measurements mem-orising, with at least one day between each evaluation.
Statistical analysis
Simple descriptive statistics (mean, standard deviation, and frequency distributions)were used to summarise the data. Initial tests for normality (assessment for skewness,
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kurtosis and Shapiro-Wilk) were performed to determine, where appropriate, parametricand non-parametric univariate analysis testing for the continuous variables (Table 1).Pearson’s correlation coefficient (r) was calculated to assess the strength of correlationbetween age and dental ratios based on the Kvaal et al.1 method (Table 1). The correla-tion coefficients calculated (using the width ratios) presented significant correlation val-ues. The most representative were observed for the ratio calculated between pulp androot width at the B point of the root, and for the predictor W-L. The mandibularcanines showed the highest correlation coefficient for the predictors B (–0.570) andW-L (–0.625).
To examine the independent association of several factors with chronological age,multivariable linear regression analysis was used to look at the association between theindependent and outcome variables. The outcome variables included chronological age.The predictor variables M and W-L were used as the independent variables. Age esti-mation models were developed individually for each tooth (Table 2) and the followingtooth combinations (Table 3): three maxillary teeth with the predictors M and W-L indi-vidually introduced for each tooth (six predictors), and the average of M and W-L (twopredictors); three mandibular teeth with the predictors M and W-L individually intro-duced for each tooth, having six predictors in the equation, and the average of M andW-L resulting in two predictors; and mandibular and maxillary teeth M and W-L pre-dictors, introduced individually in the equation (12 predictors) and the average of Mand W-L (two predictors). All regression models were built using the ordinary leastsquares approach. R-square values were computed to examine the amount of varianceexplained by the predictor variables.
All statistical tests were two-sided and a p value of less than 0.01 was consideredto be statistically significant. Corrections were made for multiplicity using a modifiedBonferonni method to reduce the likelihood of Type I errors; an alpha threshold forstatistical significance for all comparisons was set at 0.01. Univariate analyses and
Table 1. Correlation coefficients between chronological age and Kvaal et al.1 dental measure-ments and ratios, for individuals under 30 years of age.
Tooth number (FDI numbering system)
Ratio 11/21 12/22 15/25 32/42 33/43 34/44P 0.129NS 0.236 NS 0.133 NS 0.164 NS 0.455* 0.152 NS
T 0.041 NS −0.071 NS −0.002 NS −0.130 NS 0.171 NS −0.117 NS
R 0.287* 0.287* 0.151 NS 0.327* 0.279* 0.397**A −0.130 NS −0.281* −0.004 NS −0.263* −0.254 NS −0.137 NS
B −0.378* −0.305* −0.280* −0.354* −0.570** −0.381*C −0.345* −0.377* 0.009 NS −0.088 NS −0.605** −0.504**M −0.049 NS −0.202 NS 0.0001 NS −0.123 NS −0.108 NS −0.265*W −0.415** −0.397** −0.150 NS −0.237* −0.123 NS −0.497**L 0.151 NS 0.295* −0.002 NS 0.255* 0.467** 0.297*W – L −0.310* −0.421** −0.052 NS −0.360* −0.625** −0.547**
*= p<0.05; **=p<0.001.NS=Not significantNote: P is the ratio between length of pulp and root; T is the ratio between length of tooth and root; R is theratio between length of pulp and root; A is the ratio between width of pulp and root at CEJ (Level A); B isthe ratio between width of the pulp and root at mid-point between level C and A (level B); C is the ratiobetween width of pulp and root at mid-root level (level C); M is the mean value of all ratios (first predictor);W is the mean value of width ratios from levels B and C; L is the mean value of the length ratios P and R;W – L is the difference between W and L (second predictor) 1.
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multivariable linear regression analyses were performed using R Core Team version3.1.3 (2015) (R: A language and environment for statistical computing. R Foundationfor Statistical Computing, Vienna, Austria. URL http://www.R-project.org/).
Results
Measurement precision
The technical error of measurement (TEM), relative technical error of measurement(rTEM) and coefficient of reliability were within acceptable standards for the intra- andinter-observer measurement precision (TEM<1.0, rTEM<5%, R>0.75). These valueswere 0.92, 2.99% and 0.95 respectively for intra-observer precision analysis. Similarly,the inter-observer calibration (between TM and SK) showed comparable precision21
(TEM 0.80, rTEM 2.37 and R 0.98).
Table 2. Multiple regression for estimation of chronological age (in years) from individualmaxillary and mandibular teeth for individuals under 30 years of age.
Tooth (FDI) n R R2 Equation SEE ± years
11/21 69 0.152 0.1271 Age= 22.915 – 28.78 (M) −22.376 (W – L) 4.34412/22 67 0.197 0.1727 Age= 19.724 – 25.935 (M) – 23.631 (W – L) 4.25815/25 68 0.003 −0.273 Age= 17.78 – 3.962 (M) – 2.204 (W – L) 4.53632/42 71 0.131 0.106 Age= 4.644 – 5.363 (M) – 22.558 (W – L) 4.46533/43 48 0.417 0.391 Age= 11.26 – 41.33 (M) – 86.06 (W – L) 3.70834/44 71 0.327 0.307 Age= 10.513 – 27.075 (M)–38.176 (W – L) 3.709
Note. *R2, coefficient of determination. SEE, standard error of estimation in years. See Table 1 forabbreviations.
Table 3. Multiple regression for estimation of chronological age (in years) from the combinedmaxillary and mandibular teeth, the respective predictors (pds) for individuals under 30 years ofage.
Teeth (FDI) n R R2 EquationSEE ±years
3 mx (2 pds) 60 0.154 0.125 Age= 28.702 – 46.338 (M) – 24.233 (W – L) 4.1413 mx (6 pds) 60 0.237 0.150 Age=24.394 – 30.751 (11/21 M) –12.090 (11/
21 W–L) – 29.2257 (12/22 M) – 12.894 (12/22 W– L)+ 2.611 (15/25 M) – 0.631 (15/25 W – L)
4.08
3 mdb (2 pds) 45 0.409 0.381 Age= −27.44 + 10.48(M) – 63.82 (W–L) 3.6483 mdb (6 pds) 45 0.539 0.466 Age= 1.894 + 13.428 (32/42 M)–5.931 (32/42 W
– L) – 51.067 (33/43 M) – 66.495 (33/43 W – L)– 5.114 (34/44 M) – 16.806 (34/44 W – L)1
3.388
6 teeth (2 pds) 40 0.252 0.211 Age= 31.91 – 63.34 (M) – 63.34 (W – L) 4.1386 teeth (12 pds) 30 0.542 0.339 Age= 2.627 −58.42 (11/21 M) + 4.526 (11/21 W
– L) + 32.169 (12/22 M) – 12.913 (12/22 W – L)+ 25.460 (15/25 M) + 1.098 (15/25 W – L) +5.270 (32/42 M) + 0.096 (32/42 W – L) – 28.692(33/43 M) + 1.686 (33/43 W – L) – 13.857 (34/44 M) – 49.336 (34/44 W – L)
3.788
*R2, coefficient of determination. SEE, standard error of estimation in years. See Table 1 for abbreviations.
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In this way, individual (Table 2) and multiple (Table 3) tooth regression modelswere obtained. The accuracy to predict the age was quantified by the standard error ofestimation (SEE ± years). The most accurate age estimation model based on the analy-sis of individual tooth was for mandibular canines (SEE ± 3.708 years) (Figure 1). Pre-diction accuracy improved with the combined analysis of teeth; it was highest for themodel developed with the three mandibular teeth (six predictors, SEE ± 3.388 years).
Discussion
The estimation of chronological age has been a very relevant topic of discussionthrough human history. For this reason, diverse skeletal and dental methods have beendeveloped, showing variable levels of reliability in different populations. These meth-ods, based on dental changes, are well accepted and have shown their potential forforensic and anthropological applications22. Once the root formation has been com-pleted, progressive dental changes, such as secondary dentine formation, can be radio-graphically assessed based on the narrowing on the pulp chamber. Odontometric andmorphometric measurements can thus be acquired to quantify secondary dentine depo-sition and is the foundation for non-invasive adult age estimation methods such asKvaal et al.1 and Cameriere et al.23.
The Kvaal et al.1 method has been widely validated in different populations becauseof its numerous benefits, such as, among other benefits, its relatively non-invasiveapproach, applicability in live individuals and low cost. Previous research has appliedthis method to a Western Australian population17 and has shown significant results thatare valid under forensic standards. Although the Kvaal et al.1 method was initiallydeveloped to estimate age in individuals over 20 years old, previous studies have testedthis method in younger populations19. The present study applied the Kvaal et al.method1 in Western Australian participants under 30 years of age. The primary aimwas to assess the applicability of this method in a younger population to broaden theage range that the method can be applied to, without compromising the age estimationaccuracy.
Estim
ated
age
toot
h 33
/43
Chronological age tooth 33/43
Figure 1. Scatter plot showing a positive association between the estimated age and the chrono-logical age for the teeth 33/43.
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To this end, regression models were developed, based on the data acquired fromindividual teeth (Table 2) and a combination of teeth (Table 3). The accuracy to predictage was quantified by the standard error of estimation (SEE ± years). The most accuratemodel for individual teeth was for the mandibular canines (±3.708 years), in contrast tothe study of Karkhanis et al.17, where the same tooth presented the highest SEE(±10.903 years).
Prediction accuracy improved when multiple teeth were included in the regressionmodels (Table 3). In this study, the highest level of accuracy was obtained when theequation included three mandibular teeth and six predictors (SEE ± 3.388 years), incomparison with the study of Karkhanis et al.17, where the most accurate model wasfor the combined analysis of the six teeth and 12 predictors (SEE ± 7.963).
It has been observed that age estimation in individuals older than 14 years is diffi-cult, as all permanent teeth, except the third molars (when present), have completedtheir development19. Some examples of previous studies amongst people under 30 yearsof age, using the Kvaal et al. method 1 on panoramic radiographs, are: Erbudak et al.24
in a Turkish population, including in their sample 75 participants between 14 to35 years of age, obtaining a SEE= ± 8.73 years at best, using the regression formulasof Paewinsky et al.25 and Kvaal et al.1; Landa et al.20 in a Spanish population with anage range of 14 to 60 (n=100,) from which 40 were aged younger than 31 years ofage, and with an underestimation of age when using the regression formulae of Kvaalet al.1 and Paewinsky et al.25 and a standard deviation of 12.53 at best when the Kvaalet al1. regression equation was used. The last example is the study of Meinl et al.19,which was conducted in an Austrian population (n=44) with an age range of 13 to24 years, and resulted in a mean underestimation of 31.44 years when the Kvaal et al.1
regression models were applied, or a mean overestimation of 20.88 years when thePaewinsky et al.25 formula was applied. In contrast, the present study (n=74) showsthat the Kvaal et al.1 method provides acceptable results2 in a sample composed ofsub-adults and young adults. Further research is warranted, in other populations withsimilar age ranges and using larger samples.
It is also worth comparing the results of this study with other methods based onthird molar development as an estimator of chronological age. One of the most remark-able studies is the research performed by Lewis and Senn10. In their study, theyreported a standard deviation of no more than 3 years, when different methods areapplied in a North-American population. Another method based on third molars is theexamination of the periodontal membrane in lower third molars in a German popula-tion26, which found a standard deviation of between 1.9 to 4.8 years. However, thirdmolar agenesis has been reported to be between 14% up to 51% in different studies27.The Kvaal et al.1 method can be considered as an alternative in these cases.
Conclusion
Panoramic radiographs are a unique diagnostic tool, but also provide useful informationvalid for forensic purposes. It has been well established that dental records are a highlyprecise instrument for establishing an individual’s identity. The use of the Kvaal et al.1
method was initially purposed on periapical radiographs, obtained from adults, butlately this method was applied using panoramic radiographs, and included juvenile par-ticipants. The validation of the Kvaal et al.1 method for age estimation, using panora-mic radiographs obtained from a population including juvenile individuals, enlarges therange of ages where the ratio between secondary dentine production and the decrease
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of pulp chamber can be applied. This also presents the opportunity to examine theapplication of this method in other juvenile population groups.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This study received ethics approval from the Human Research Ethics Committee ofThe University of Western Australia (Ref: RA/4/1/6797).
ORCID
T.Y. Marroquin http://orcid.org/0000-0002-3335-5305
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using mandibular first molar radiographs: A novel technique. J Forensic Dent Sci. 2013;5(1):56–59.
3. Sheelavant SS, Chandra GYP, Harish S. Estimation of age from the physiological changes ofteeth in adults between 25–60 years. An autopsy study. Indian. J Forensic Med Toxicol.2014;8(1):202–207.
4. Bosmans N, Ann P, Aly M, Willems G. The application of Kvaal’s dental age calculationtechnique on panoramic dental radiographs. Forensic Sci Int. 2005;153(2):208–212.
5. Saunders E. The teeth a test of age. The Lancet. 1838;30(774):492–496.6. Yusof MYPM, Thevissen PW, Fieuws S, Willems G. Dental age estimation in Malay children
based on all permanent teeth types. Int J Legal Med. 2014;128(2):329–333.7. Franklin D. Forensic age estimation in human skeletal remains: Current concepts and future
directions. Legal Med. 2010;12(1):1–7.8. Demirjian A, Goldstein H, Tanner JM. A new system of dental age assessment. Human Biol.
1973;45(2):211.9. Feijóo G, Barbería E, De Nova J, Prieto JL. Dental age estimation in Spanish children.
Forensic Sci Int. 2012;223(1–3):371.e1–.e5.10. Lewis JM, Senn DR. Dental age estimation utilizing third molar development: A review of
principles, methods, and population studies used in the United States. Forensic Sci Int.2010;201(1–3):79–83.
11. Kırzıoğlu Z, Ceyhan D. Accuracy of different dental age estimation methods on Turkishchildren. Forensic Sci Int. 2012;216(1–3):61–67.
12. Panchbhai AS. Dental radiographic indicators, a key to age estimation. Dento Maxillo FacialRadiol. 2011;40(4):199.
13. Bodecker CF. A consideration of some of the changes in the teeth from young to old age.Dental Cosmos. 1925;67:543–549.
14. Cameriere R, Ferrante L, Cingolani M. Variations in pulp/tooth area ratio as an indicator ofage: a preliminary study. J Forensic Sci. 2004;49(2):317–319.
15. Drusini AG, Toso O, Ranzato C. The coronal pulp cavity index: a biomarker for age determi-nation in human adults. Am J Phys Anthropology. 1997;103(3):353–363.
16. Sarkar S, Kailasam S, Mahesh Kumar P. Accuracy of estimation of dental age in comparisonwith chronological age in Indian population – A comparative analysis of two formulas.J Forensic Legal Med. 2013;20(4):230–233.
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17. Karkhanis S, Mack P, Franklin D. Age estimation standards for a Western Australian popula-tion using the dental age estimation technique developed by Kvaal et al. Forensic Sci Int.2014;235:104.e1–104.e6.
18. Kanchan-Talreja P, Acharya AB, Naikmasur VG. An assessment of the versatility of Kvaal’smethod of adult dental age estimation in Indians. Arch Oral Biol. 2012;57(3):277–284.
19. Meinl A, Tangl S, Pernicka E, Fenes C, Watzek G. On the applicability of secondary dentinformation to radiological age estimation in young adults. J Forensic Sci. 2007;52(2):438–441.
20. Landa MI, Garamendi PM, Botella MC, Aleman I. Application of the method of Kvaal et alto digital orthopantomograms. Int J Legal Med. 2009;123(2):123–128.
21. Lewis SJ. Quantifying measurement error. Oxford: Oxbow Books; 1999. Current and recentresearch in osteoarchaeology 2: Proceedings of the 4th, 5th and 6th meetings of the Osteoar-chaeological Research Group, Anderson IS, editor; 54–55.
22. Manual of Forensic Odontology. 5th ed. Edited by David R, Senn R, Weems A, Senn DR,Weems RA. Boca Raton, FL: CRC Press; 2013.
23. Cameriere R, De Luca S, Alemán I, Ferrante L, Cingolani M. Age estimation by pulp/toothratio in lower premolars by orthopantomography. Forensic Sci Int. 2012;214(1–3):105–112.
24. Erbudak HO, Ozbek M, Uysal S, Karabulut E. Application of Kvaal’s et al. age estimationmethod to panoramic radiographs from Turkish individuals. Forensic Sci Int. 2012;219(1–3):141–146.
25. Paewinsky E, Pfeiffer H, Brinkmann B. Quantification of secondary dentine formation fromorthopantomograms—a contribution to forensic age estimation methods in adults. Int J LegalMed. 2005;119(1):27–30.
26. Olze A, Solheim T, Schulz R, Kupfer M, Pfeiffer H, Schmeling A. Assessment of the radio-graphic visibility of the periodontal ligament in the lower third molars for the purpose offorensic age estimation in living individuals. Int J Legal Med. 2010;124(5):445–448.
27. Celikoglu M, Kamak H. Patterns of third-molar agenesis in an orthodontic patient populationwith different skeletal malocclusions. The Angle Orthodontist. 2012;82(1):165–169.
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242
APPENDIX 5. Application of the Kvaal method for adult dental age estimation using Cone
Beam Computed Tomography (CBCT).
Marroquin, T.Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Nurul F., Kanagasingam S., D.
Franklin., E., Kruger, E., & Tennant, M. (2016) Application of the Kvaal method for adult
dental age estimation using Cone Beam Computed Tomography (CBCT). Journal of Forensic
and Legal Medicine, Accepted for publication. October 2016.
Research Paper
Application of the Kvaal method for adult dental age estimation usingCone Beam Computed Tomography (CBCT)
Talia Yolanda Marroquin Penaloza a, Shalmira Karkhanis a, Sigrid Ingeborg Kvaal b,Firdaus Nurul c, Shalini Kanagasingam d, Daniel Franklin a, Sivabalan Vasudavan a,Estie Kruger a, *, Marc Tennant a
a University of Western Australia, School of Anatomy Physiology and Human Biology, 35 Stirling Hwy, Crawley, WA 6009, Australiab University of Oslo, Faculty of Dentistry, Institute of Clinical Dentistry, P.O. Box 1109, Blindern, N-0317 Oslo, Norwayc Radiology Unit, Dental Faculty University of Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysiad Faculty of Dentistry, University of Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia
a r t i c l e i n f o
Article history:Received 11 August 2016Received in revised form13 October 2016Accepted 22 October 2016Available online 24 October 2016
Keywords:AdultsAge estimationTomographyKvaal method
a b s t r a c t
Different non-invasive methods have been proposed for dental age estimation in adults, with the Kvaalet al. method as one of the more frequently tested in different populations.
The purpose of this study was to apply the Kvaal et al. method for dental age estimation on modernvolumetric data from 3D digital systems. To this end, 101 CBCT images from a Malaysian population wereused. Fifty-five per cent were female (n ¼ 55), and forty-five percent were male (n ¼ 46), with a medianage of 31 years for both sexes. As tomographs allow the observer to obtain a sagittal and coronal view ofthe teeth, the Kvaal pulp/root width measurements and ratios were calculated in the bucco-lingual andmesio-distal aspects of the tooth. From these data different linear regression models and formulae werebuilt. The most accurate models for estimating age were obtained from a diverse combination of mea-surements (SEE ±10.58 years), and for the mesio-distal measurements of the central incisor at level A(SEE ±12.84 years). This accuracy, however is outside an acceptable range in for forensic application (SEE±10.00 years), and is also more time consuming than the original approach based on dental radiographs.
© 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
1. Introduction
Currently, the need for developing more accurate and non-invasive methods for age estimation, as part of the identificationof adult individuals in situations of forensic scenarios is increasingglobally.1 Gustafson first proposed a method for dental age esti-mation in adults,2 since then, the analysis of dental changes inadults relative to chronological age has continued. The adultdentition is relatively resistant to environmental and chemical in-fluences, and methods based on the assessment of teeth areconsidered advantageous for this reason.3,4 Furthermore, methods
based on odontometric measurement of pulp and tooth structuresfrom dental radiographs or tomographs are non-invasive/non-destructive and can be applied to both living or deceased in-dividuals.5 Kvaal et al., proposed a method for age estimation inadults which has been tested in different populations around theworld since 1995, but all reported a high standard error (±8.5 to±13 years).1,5,6 The basis of this method is the analysis of the nar-rowing of the pulp chamber with age, which is observable andmeasurable in dental radiographs. However, there is scope forimprovement in the accuracy of the age estimations.
With the emergence of computer tomography (CT) and conebeam computer tomography (CBCT), new methods based on volu-metric reconstruction of tooth and pulp volume and ratio calcula-tions have been proposed for dental age estimation in adults.7,8
However, those techniques have not provided better accuracyrelative to the previously described Kvaal method, using dentalradiographs. Moreover, pulp/tooth volume calculation is labourintensive,9 and can require the use of complex, and often costlycomputer software.10 Clearly, these more technical multi-
* Corresponding author.E-mail addresses: [email protected] (T.Y. Marroquin Penaloza),
[email protected] (S. Karkhanis), [email protected] (S.I. Kvaal),[email protected] (F. Nurul), [email protected] (S. Kanagasingam),[email protected] (D. Franklin), [email protected](S. Vasudavan), [email protected] (E. Kruger), [email protected](M. Tennant).
Contents lists available at ScienceDirect
Journal of Forensic and Legal Medicine
journal homepage: www.elsevier .com/locate/ jflm
http://dx.doi.org/10.1016/j.jflm.2016.10.0131752-928X/© 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
Journal of Forensic and Legal Medicine 44 (2016) 178e182
dimensional systems provide considerably more data, at a sub-stantially more detailed level, and with a reduction in many of thecomplications of simple plane film images. The method describedby Kvaal et al.5 was initially proposed, with measuring dimensionson periapical radiographs with a microscope and a pair of callig-raphers. The applications of this method have been expanded toinclude panoramic radiographs using different analytical soft-ware.6,11 The purpose of the present study is to apply the Kvaalet al.5 method for dental age estimation using modern computertomographic data from 3D digital systems. The null hypothesis isthat the substantially increased quantity (and quality) of the datafrom these systems will provide greater accuracy of dental ageestimation in adults.
2. Materials and methods
2.1. Sample
The study sample included a total of 101 tomographs obtainedas part of normal treatment from the radiology department of theUniversity of Keibangsaan Malaysia. Almost half (n ¼ 47) wereobtained with a Kodak device, reference K9000-3D (exposure pa-rameters: scanning time: 10.8 s, 3e15 mA, 60e85kVp, field of viewFOV: 5.2 cm � 5.2 cme5.5 cm to 5.5 cm, 180� rotation, slice thick-ness 0.076e0.2 mm), and 54 were obtained with an i-CAT device(Dental Imaging Technologies Corporation. i-CAT® FLX™) (expo-sure parameters: scanning time 4 s, 5 mA, 120 kVp, FOV:16 cm � 16 cm, Slice thickness 0.3 mme0.4 mm). Of these tomo-graphs, 55% were from female (n ¼ 55), and 45% were from male(n ¼ 46) patients, with a median age of 31 years for both sexes(Table 1). All the images were received in DICOM format, andanalysed using the Osirix® software package (OnDemand 3D soft-ware CyberMed Inc, Seoul, South Korea). The study sampleincluded teeth with very small coronal restorations, as long as theydid not compromise the pulp chamber and secondary caries wasnot present. Teeth with shape abnormalities, active caries, rootcanal treatment, prosthetic restorations, signs of pulp or periapicalpathologies, or open root apex, were duly excluded from thesample. Multi-rooted upper second premolars were also excluded.
2.2. Teeth analysed
Initially, Kvaal et al.5 proposed a set of linear measurements,including the length of the tooth, pulp and root, in addition to thewidth of the root and pulp chamber at different levels, in sixdifferent teeth: upper central and lateral incisors, and the secondpremolar; and the lower lateral incisor, canine and first premolar. Inthe present study, due to the unclear definition of the pulp chamberand tooth boundaries for the lower teeth (most likely related totheir small dimensions) only upper teeth were included: centralincisor, lateral incisor, canine, and second upper premolar (when
possible). As the dental images are tomographs, it is possible toassess the teeth in sagittal and coronal views; accordingly, the rootlength, and pulp/tooth width measurements proposed by Kvaalet al.5 were acquired in the mesio-distal and bucco-lingual aspectsof the teeth (see below). Significant differences between teeth ofthe left and right side of the maxilla have not been reported pre-viously,5 and therefore in this study, teeth from either the left orright side was measured.
2.3. Measurements
As proposed by Kvaal et al.,5 the mesio-distal measurements ofthe teeth (coronal view) were performed as follows: first, the levelA, was located at the CEJ (cemento-enamel junction) on the mesialside of the tooth, then level C was located halfway between point Aand the root apex, and finally point B was located halfway betweenpoint A and C. As this is the first study applying the Kvaal et al.method exclusively in tomographs, bucco-lingual measurementswere also acquired (sagittal view). Point A was located at thevestibular CEJ, point C halfway between the vestibular CEJ and theroot apex, and point B, halfway between point A and point C. In thisway, there were six pulp/tooth width measurements per tooth. Allthe measurements were recorded by one observer (TYM) using theOsirix® software.
2.4. Statistical analysis
Intra-observer error was tested, four tomographs wererandomly selected (two Kodak and two i-CAT) and all the mea-surements were recorded by one observer (TYM). Upper central,lateral and canine were measured on four separate occasions, witha minimum of one day between repetitions ensuring that theobserver did not remember the previously recorded measure-ments. Measurement error was assessed by calculating the tech-nical error of measurement (TEM), coefficient of reliability (R) andrelative technical error of measurement (rTEM).12
All data were collected in an Excel spreadsheet, Excel (version2013 Microsoft, Redmont, USA), and statistical analysis wascompleted using R Core Team version 3.1.3 (2015). (R: A languageand environment for statistical computing. R Foundation for Sta-tistical Computing, Vienna, Austria. URL http://www.R-project.org/). Descriptive statistics were used to summarise the data (mean,standard deviation, and frequency distributions). Normality wasalso tested (skewness, kurtosis and Shapiro-Wilk) to establishwhether parametric or non-parametric analysis was required.Pearson correlation coefficient (r) was calculated to assess therelationship between the dental ratios and age, for the data ob-tained from the Kodak CBCT and for the data obtained from i-CATCBCT individually, and also when both data sets were combined.This was done with the aim of testing if the difference between theresolutions of both devices could cause any statistically significantdifferences (Table 2). Linear regression models were built with agedesignated as the dependant variable. Different age estimationequations were then formulated using different groupings of agepredictors: 1) the tooth/pulp ratios at the levels A, B or C individ-ually; 2) calculating the average of the pulp/tooth ratios of all theteeth at the different levels (A, B or C) obtaining a formula for eachlevel; 3) calculating the average of the pulp/tooth ratios of thelateral (Lat) and central (Cent) upper incisor at the different levels(A, B and C); 4) Average of the pulp/tooth ratios from all the teeth atthe levels A, B and C in the same formula (Aþ Bþ C); and 5) same as4, but excluding the ratios obtained from the canines (Cent-Lat). Atotal of 17 linear regression models were thus generated per data-set: sagittal (s) view (bucco-lingual measurements); coronal (c)view; and the average of both (sc). The accuracy of the models is
Table 1Age and sex distribution for CBCT and i-CAT tomographs.
Sex Female Male Total
Age range (years) CBCTn ¼ 23
i-CATn ¼ 32
CBCTn ¼ 24
i-CATn ¼ 22
15e20 2 1 7 2 1220e29 12 9 5 8 3430e39 3 5 2 2 1240e49 4 6 8 5 2350e59 2 6 2 0 1060e75 0 5 0 5 10TOTAL 55 46 101
T.Y. Marroquin Penaloza et al. / Journal of Forensic and Legal Medicine 44 (2016) 178e182 179
reported as the standard error of estimation (SEE).11,13
3. Results
Intra-observer error results were considered to be withinacceptable range. (TEM <1.0 and the coefficient of reliabilityR>0.80%), regardless the tomograph source (Kodak or i-CAT) orwhether the measurements were recorded in the bucco-lingual ormesio-distal view of the teeth. In terms of the relative technicalerror of measurement (rTEM), 72% of the observations scored <5%and 28% had a rTEM < 10%. It was also observed that the accuracy ofthe observer was better for the bucco-lingual measurements(sagittal view of the teeth) regardless the source of the tomography.
Pearson correlation coefficient test (r) demonstrated a strongercorrelation between the pulp/tooth ratios and age for the bucco-lingual measurements (sagittal (s)) than for the mesio-distal mea-surements (coronal view (c)) (Table 2). Although there were dif-ferences between the correlation coefficients from the Kodak and i-CAT CBCT's, scatter-plots including the results of both sources donot show outliers associated with the specific use. There was a clearand significant negative correlation between age and pulp/toothratios in all the data sets. Correlation coefficient were calculated asfollows: i) for the measurements obtained from the Kodak tomo-graphs; ii) for the measurements recorded from the i-CAT tomo-graphs; and iii) for the combination of both. The i-CAT tomographsshowed the strongest correlation to age, especially for the uppercentral incisor (r ¼ �0.65), followed by the combination of theKodak & i-CAT data sets (r ¼ �0.61). The correlation coefficientsobtained from the Kodak, although statistically significant, werelower than that obtained from the i-CAT and combined Kodak & i-CAT (Table 2).
In relation to the accuracy of the different linear regressionmodels, it was observed that all the estimates were over thethreshold generally accepted for forensic application (SEE ±10years),14 however the SEE is reduced when both data-sets arecombined into a linear regression model (Table 3). There was onlyone equation with an acceptable level of predictive accuracy (SEE10.58 years (n ¼ 72, r ¼ 0.59, r2 ¼ 0.56)):
Age ¼ 101.46 þ 734.74 (Ac) �374.81 (Ac(Cent-Lat)) e 1075.18 (Csc) þ 327.07 (Bc) þ 310 (Cc(Cent-Lat)) e 159.25 (11/21 As)
Abbreviations: Ac: average of the pulp/tooth ratio in the coronalview at level A from the three teeth. Ac(Cent-Lat): average of the pulp/tooth ratios from the lateral and central incisors. Csc: average of thepulp/tooth ratio at level C from the sagittal and coronal views (sc)from all teeth. Bc: average of the pulp tooth ratio at the level B fromall the teeth in the coronal view. (Cc(Cent-Lat)): average of the pulp/tooth ratios at the level C from the lateral and central incisor in the
coronal view. 11/21 As: pulp/tooth ratio at the level A from thecentral incisor in the sagittal view.
The most accurate linear regression models obtained from theindividual analysis of the bucco-lingual measurements were asfollows: the central incisor at level A (Age¼ 84.059e191.003 (11/21As), r2 ¼ 0.37, SEE ¼ ±12.84), the average of the bucco-lingualmeasurements from the central incisor and lateral incisor at thelevel A, B and C (Age ¼ 102.08e157.94 (As) �73.0 (Bs) �36.81 (Cs),r2 ¼ 0.39, SEE ¼ ±12.73 years).
When both data-sets were combined (Table 3) the highest ac-curacy was achieved from: the average of the bucco-lingual (s) plusthe average of the mesio-distal (c) measurements at level A, (SEE±12.17 years); the average of the bucco-lingual and mesio-distalmeasurements at level A from the central and lateral incisors,(SEE ±12.76); and the average of the bucco-lingual andmesio-distalmeasurements from the central and lateral incisors at level A, pluslevel B, plus level C, (SEE ±12.7). The linear regression modelsgenerated by the inclusion from only the mesio-distal (c) mea-surements did not result in an SEE lower than ±14 years, andtherefore these results are not included.
4. Discussion
This is the first study testing the Kvaal et al. method exclusivelyin tomographs, and also the first one applying Kvaal et al.'s. pulp/tooth width ratio calculations in the bucco-lingual aspect of theteeth. Computer tomography is increasingly being used in dentalpractice and provides three-dimensional information about anyarea of interest, in a relatively quick and cost-effective manner.15 Inthis study it was expected that application of the Kvaal et al.method using CBCT diagnostic images would increase the array ofmethods available for the forensic profiling of living and deceasedindividuals. Until now, there has only been one other study pro-posing a similar method for adult dental age estimation, based onthe assessment of the pulp/tooth bucco-lingual dimensions (area)in canines.16 Although the results of the latter study were satis-factory (Mean prediction error, ME ±2.8 years at best), this methodrequired extracted teeth, and thus has restricted application in aforensic context. The use of tomographs overcomes issues relatedto the requirement for tooth extraction, and also permits theanalysis of multiple teeth with less radiation exposure.
Although, in this study, the number of individuals was small incertain age intervals, there are well documented biological agerelated changes in the human dentition, which have allowedforensic dentists to propose and use different methods for dentalage estimation.17 In previous publications applying the Kvaal et al.method for dental age estimation in adults, it has been noted thatone of the principal limitations is the absence of a clear limit be-tween the dentine and the pulp camber,11 which is observed as a
Table 2Correlation coefficient measurements CBCT.
Tooth number CBCT i-CAT CBCT & i-CAT
Coronal Sagittal Coronal Sagittal Coronal Sagittal
11/21 A �0.05 NS �0.36* �0.634** �0.65** �0.45** �0.61**11/21 B �0.26 NS �0.37* �0.421** �0.59** �0.32* �0.5**11/21 C �0.29 NS �0.45** �0.288* �0.36* �0.23* �0.41**12/22 A �0.53** �0.08 NS �0.326* �0.62** �0.31* �0.41**12/22 B �0.35* �0.5** �0.3* �0.60** �0.22* �0.46**12/22 C �0.24 NS �0.57** �0.013 NS �0.41** �0.05 NS �0.41**13/23 A �0.25 NS �0.13 NS �0.153 NS �0.50** �0.04 NS �0.17 NS
13/23 B �0.59** �0.56** �0.329* �0.41* �0.28** �0.39**13/23 C �0.52** �0.34** �0.348* �0.24 NS �0.28** �0.21*
*p < 0.05, **p < 0.001, NS ¼ non-significant.
T.Y. Marroquin Penaloza et al. / Journal of Forensic and Legal Medicine 44 (2016) 178e182180
grey zone instead of a distinct line.6 This affects the accuracy of themeasurements and intra/inter-observer agreement. In the presentstudy it was observed that neither Kodak nor i-CAT tomographswere exempt from this issue. In certain cases, the border betweenthe pulp chamber and dentine, or tooth and bone are also moreblurred than in periapical radiographs. It is true that dental Kodaktomographs may have higher resolution than i-CAT tomographs.However, in the present study it was observed that the data ob-tained from the i-CAT had a higher correlation to age compared tothe Kodak scans (Table 2). Similarly, the bucco-lingual width ratioshad a higher correlation to age than the mesio-distal width ratios(with the latter measurable in periapical radiographs).
It has previously been reported that Kvaal et al. length mea-surements are both difficult to register and do not provide signifi-cant information to the final equation.5,18 It is important to notethat in the tomographs analysed in the present study, it was evenmore difficult to observe the root apex compared to periapical ra-diographs. The only length measurement registered was the rootlength from the CEJ towards the apex to locate points A, B and C. Inthis way only pulp/toothwidth and ratios were used as the only agepredictors. The exclusive use of pulp/tooth ratios proposed by Kvaalet al. has previously been documented18 on panoramic radiographs,showing more accurate results (SEE ¼ ±10.02 years) than thoseobtained in this study. (SEE ¼ ±10.58 years at best). In a previousstudy that analysed the odontometric age-related changes indifferent teeth, it was found that the rate of secondary dentineformation varied depending on tooth type: in canines the increaseof coronal dentinal thickness was not as high as it was for theincisor and premolars.19 In the present study it was similarlyobserved that although the correlation coefficient between pulp/tooth ratios and age were significant, the exclusion of canine ratioswhen the linear regression models were generated, improved theiraccuracy.
On the other hand, this is also the first study documenting theinclusion of teeth with small crown fillings in the sample togenerate linear regression formulae, in contrast to previous publi-cations using the Kvaal et al. method,5 where one of the inclusioncriteria was to use only totally clinically sound teeth. It wasobserved that there were no statistically significant differencescaused by inclusion of these teeth. This may relate to the nature of
the formation of tertiary dentine or reactionary dentine to externalthreats. It has been reported that tertiary dentine formation ishighly dependent on the stimulus, and that caries mediators inducea focal dentine production,19e21 with a rate formation of about 3 mmper day.22
Regression analysis, has been chosen for age estimation due toits simplicity.23 Nevertheless, it is necessary to note the limitationsof the use of linear regression models for dental age estimation; forexample, the higher standard deviations when the originalformulae of Kvaal et al. are applied in populations of differentethnic backgrounds.24 The latter necessitates the need for popula-tion specific formulae. Also, it assumes that formation of secondarydentine is a linear process, when it is more similar to a curve.25
Additionally, it was observed that, although using tomographyresult in obtaining more odontometric data from the same teeth(mesio-distal and bucco-lingual measurements), this apparentadvantage over the use of dental radiographs, did not improve thefinal outcome. Also, the need to properly align the teeth in thesagittal and coronal plane demands more time than the traditionalKvaal et al. approach in dental radiographs.
Finally, it is necessary to mention that CBCT is not exempt ofartefacts intrinsic to the process of image acquisition.26 This couldexplain, not only the high SEE obtained in this study, but also thepoor accuracy of those methods based on pulp/tooth volumecalculation,9,10 when compared with more simple approaches suchas the measurement of pulp/tooth area on dental radiographs(Cameriere et al. method, with a SEE ¼ ±3.27 years).16
5. Conclusion
Radiological assessment of dental age-related changes is a validtool for age estimation. It is true that new diagnostic technologiesprovide the practitioners and forensic researchers new opportu-nities to use and propose new methods for dental age estimation.However, the use of tomographs in this study, applying the Kvaalet al. method, did not improve the results. It is recommended toalso include teeth with small fillings in studies based on pulp/toothdimension ratios, as long as the pulp chamber is not compromised.The aim of this is to further investigate the application of thesedifferent methods on those individuals who do not have totally
Table 3Linear regression analysis, linear regression formulae, correlation coefficient (r) between age and the ratios of bucco-lingual and mesio-distal width measurements from CBCT& i-CAT.
Sagittal and coronal
Age predictors n Linear regression formulae r r2 SEE
11/21 A sc 86 Age ¼ 99.74�72.07(11Ac)�161.63(11As) 0.4 0.4 12.211/21 B sc 86 Age ¼ 81.82�35.031(11Bc)�147.14(11As) 0.26 0.24 1411/21 C sc 86 Age ¼ 71.92�29.16(11Cc)�134.69(11Cs) 0.17 0.15 14.912/22 A sc 89 Age ¼ 87.43�68.05(12Ac)�129.37(12As) 0.21 0.19 14.512/22 B sc 89 Age ¼ 73.98�24.34(12Cb)�127.46(12Bs) 0.21 0.19 14.512/22 C sc 89 Age ¼ 57.56 þ 37.84(12Cc)�148.22(12 cs) 0.18 0.17 14.713/23 A sc 95 Age ¼ 51.14�5.4(13Ac)�47.192(13As) 0.03 0.01 15.413/23 B sc 95 Age ¼ 69.51�47.15(13Bc)�70.44(13Bs) 0.17 0.15 14.213/23 C sc 95 Age ¼ 60.81�78.34(13Cc)�34.37(13Sc) 0.09 0.08 14.9A sc 78 Age ¼ 100.41�33.11(Ac)�206.40(As) 0.34 0.33 13.5B sc 78 Age ¼ 89.22�20.54(Bc)�178.29(Bs) 0.31 0.29 13.9C sc 78 Age ¼ 69.46 þ 16.4(Cc)�174.42(Cs) 0.17 0.15 15.2A sc Cent/Lat 83 Age ¼ 105.42�72.96(Ac1/2)�187.22(As1/2) 0.4 0.38 12.8B sc Cent/Lat 83 Age ¼ 86.31�19.86(Bc1/2)�180.19(Bs1/2) 0.29 0.27 13.9C sc Cent/Lat 83 Age ¼ 70.41 þ 42.09(Cc1/2)-206.7(Cs1/2) 0.23 0.21 14.4Asc þ Bsc þ Csc 74 Age ¼ 104.09�17.65 (Ac)�135.48 (AS)�38.18(Bc)�105.54(Bs)þ40.87(Cc)þ10.93 (Cs) 0.4 0.35 13.3Asc þ Bsc þ Csc Lat/Cent 82 Age ¼ 106.25�180.14(Asc1/2)�135.83(Bsc1/2)þ51.73(Ccs1/2) 0.4 0.39 12.7
Abbreviations: Tooth number (11/21, 12/22 and 13/23) with Asc, Bsc or Csc ¼ pulp/tooth ratio at the levels A, B or C in the sagittal and coronal view (sc) calculated per tooth.Asc, Bsc or Csc: average of the pulp/tooth ratio at the respective level, from all the teeth. Asc, Bsc or Csc with Lat/Cent: average of the pulp/tooth ratio only from central andlateral incisors. Asc þ Bsc þ Csc ¼ average from the pulp/tooth ratio from all the teeth at the respective level. Asc þ Bsc þ Csc ¼ average from the pulp/tooth ratio from all theteeth at the respective level including only lateral and central teeth. SEE: Standard error of estimation in ± years. Best results in bold.
T.Y. Marroquin Penaloza et al. / Journal of Forensic and Legal Medicine 44 (2016) 178e182 181
sound dentitions.
Conflict of interest
None of the authors have any conflict of interest associated withthis study.
Funding
None.
Ethics approval
Ethics approval for this study was obtained from the HumanResearch Ethics Committee of the University of Western Australia(Ref: RA/4/1/6797). Permission was also granted by the Universityof Keibangsaan Malaysia. The design of the study, data collection,and analyses have been performed in accordance with the ethicalstandards set forth in the 1964 Declaration of Helsinki.
Acknowledgments
The authors would like to thank the department of radiology ofthe dental faculty of the University of Kebangsaan Malaysia, and toDr. Shahida Mohd Said also to Ambika Flavel, from the Centre forForensic Science at the University of Western Australia (UWA) toMartin Firth form the statistics clinic at UWA.
References
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2. Gustafson G. Age determination on teeth. J Am Dent Assoc. 1950;41(1):45e54.3. Soomer H, Ranta H, Lincoln MJ, Penttila A, Leibur E. Reliability and validity of
eight dental age estimation methods for adults. J Forensic Sci. 2003;48(1):149e152.
4. Limdiwala PG, Shah JS. Age estimation by using dental radiographs. J ForensicDent Sci. 2013;5(2):118e122.
5. Kvaal SI, Kolltveit KM, Thomsen IO, Solheim T. Age estimation of adults fromdental radiographs. Forensic Sci Int. 1995;74(3):175e185.
6. Kanchan-Talreja P, Acharya AB, Naikmasur VG. An assessment of the versatilityof Kvaal's method of adult dental age estimation in Indians. Arch Oral Biol.2012;57(3):277e284.
7. Pinchi V, Pradella F, Buti J, Baldinotti C, Focardi M, Norelli G-A. A new age
estimation procedure based on the 3D CBCT study of the pulp cavity and hardtissues of the teeth for forensic purposes: a pilot study. J Forensic Leg Med.2015;36:150e157.
8. Ge Z-p, Ma R-h, Li G, Zhang J-z, Ma X-c. Age estimation based on pulp chambervolume of first molars from cone-beam computed tomography images. ForensicSci Int. 2015;253:133.e1e133.e7.
9. De Angelis D, Gaudio D, Guercini N, et al. Age estimation from canine volumes.Radiol Med. 2015:1e6.
10. Venkatesh S, Ajmera S, Ganeshkar SV. Volumetric pulp changes after ortho-dontic treatment determined by cone-beam computed tomography. J Endod.2014;40(11):1758e1763.
11. Karkhanis S, Mack P, Franklin D. Age estimation standards for a WesternAustralian population using the dental age estimation technique developed byKvaal et al. Forensic Sci Int. 2014;235(0):104.e1e104.e6.
12. Lewis SJ. Quantifying measurement error. In: Anderson IS, ed. Current andRecent Research in Osteoarchaeology 2: Proceedings of the 4th, 5th and 6thmeetings of the Osteoarchaeological Research Group. Oxford: Oxbow Books;1999:54e55.
13. Marroquin T, Karkhanis S, Kvaal S, et al. Determining the effectiveness of adultmeasures of standardised age estimation on juveniles in a Western Australianpopulation. Aust J Forensic Sci. 2016:1e9.
14. Solheim T, Sundnes PK. Dental age estimation of Norwegian adults - a com-parison of different methods. Forensic Sci Int. 1980;16(1):7e17.
15. Oi T, Saka H, Ide Y. Three-dimensional observation of pulp cavities in themaxillary first premolar tooth using micro-CT. Int Endod J. 2004;37(1):46e51.
16. Cameriere R, Ferrante L, Belcastro MG, Bonfiglioli B, Rastelli E, Cingolani M. Ageestimation by pulp/tooth ratio in canines by mesial and vestibular peri-apicalx-rays. J Forensic Sci. 2007;52(5):1151e1155.
17. Panchbhai AS. Dental radiographic indicators, a key to age estimation. Dento-maxillofac Radiol. 2011;40(4):199.
18. Paewinsky E, Pfeiffer H, Brinkmann B. Quantification of secondary dentineformation from orthopantomogramsda contribution to forensic age estima-tion methods in adults. Int J Leg Med. 2005;119(1):27e30.
19. Murray PE, Stanley HR, Matthews JB, Sloan AJ, Smith AJ. Age-related odonto-metric changes of human teeth. Oral Surg Oral Med Oral Pathol Oral RadiolEndod. 2002;93(4):474e482.
20. Hargreaves KM, Berman LH. Cohen's Pathways of the Pulp Expert Consult. ElsevierHealth Sciences. 2015.
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24. Parikh N, Dave G. Application of kvaal's dental age estimation technique onOrthopantomographs on A Population of GujarateA Short Study. BUJOD.2013;3(3):18e24.
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248
APPENDIX 6. Reliability and repeatability of pulp volumetric reconstruction through three
different volume calculations
Marroquin, T. Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Castelblanco, E., Kruger, E., &
Tennant, M. Reliability and repeatability of pulp volumetric reconstruction through three
different volume calculations. Journal of Forensic Odontostomatology. Accepted for
publication. March 2017.
JOURNAL of FORENSIC ODONTO-
STOMATOLOGY VOLUME 34 Number 2 December 2016
35
SECTION AGE ESTIMATION
Reliability and repeatability of pulp volume
reconstruction through three different volume
calculations
Talia Yolanda Marroquin Penaloza1, Shalmira Karkhanis
1, Sigrid Ingeborg Kvaal
2, Sivabalan Vasudavan
1, Edwin
Castelblanco1, Estie Kruger
1, Marc Tennant
1
1School of Anatomy, Physiology and Human Biology University of Western Australia, Crawley, Australia. 2Faculty of Dentistry, Institute of Clinical Dentistry, Oslo, Norway. Corresponding author: [email protected]
The authors declare that they have no conflict of interest.
ABSTRACT
Objective: To test the variability of the volume measurements when different segmentation methods
are applied in pulp volume reconstruction. Materials and methods: Osirix® and ITK-SNAP software
were used. Different segmentation methods (Part A) and volume approaches (Part B) were tested in a
sample of 21 dental CBCT’s from upper canines. Different combinations of the data set were also
tested on one lower molar and one upper canine (Part C) to determine the variability of the results
when automatic segmentation is performed. Results: Although the obtained results show correlation
among them(r>0.75), there is no evidence that these methods are sensitive enough to detect small
volume changes in structures such as the dental pulp canal (Part A and Part B). Automatic
segmentation is highly susceptible to be affected by small variations in the setting parameters (Part
C). Conclusions: Although the volumetric reconstruction and pulp/tooth volume ratio has not shown
better results than methods based on dental radiographs, it is worth to persevere with the research in
this area with new development in imaging techniques.
KEYWORDS: age estimation, pulp volume calculation, image segmentation.
JFOS. July 2017, Vol.34, No.2 Pag 35 xx-xx
ISSN :2219-6749
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
36
INTRODUCTION
Since 1950 different methods have been
proposed to estimate dental age in adults.1
Most of them are based on the formation of
secondary dentine and the decrease of the
pulp chamber size with age.2,3
Methods
that have an invasive approach, (for
example aspartic acid racemization and
cementum annulation), are not of
preference, as they often require the
physical damage of the sample.4 With the
evolution of different diagnostic imaging
techniques, non-invasive methods for
dental age estimation have become the
preferred methods,5 starting with the use of
periapical dental radiographs,2,3
then
panoramic radiographs6 and more recently
cone beam computed tomography
(CBCT).7
Micro-Computer Tomography (µCT) was
introduced in the early 20th century8 to
determine age related three-dimensional
changes in pulp cavities, from maxillary
first premolar teeth. Consistent with early
histological research, µCT study’s findings
indicate that decrease in pulp volume is not
linear. It demonstrates a quicker reduction
between the 20 and 40 years and then it
slows down thereafter. Further research
correlating the ratio between pulp and
tooth volume with the chronological age,
using µCT and linear regression models to
estimate dental age in adults, found
promising outcomes.8 However, in light of
the high radiation doses associated with
µCT, only extracted teeth can be measured
in this way.9 More recently CBCT has
been used for dental age estimation
calculating the volumes from tooth and
pulp chamber. Since then, volumetric
reconstruction from CBCT with different
software have been reported in various
studies for dental age estimation in
adults.10-13
The most recent studies
document the use of CBCT from single- 5,13
and multi-rooted teeth.14
. However,
these new methods have not shown
superior accuracy to the methods based on
dental radiographs.2,15
It is evident that
within each type of software there are a
series of sensitivity settings that influences
the mathematical approach to measure the
baseline volumetric data. These settings
clearly have consequences for the outcome
and may well be in part the cause of the
substantial variation. The primary aim of
this study was to test the variability of the
volume measurements when different
segmentation methods were applied to pulp
volume reconstruction. This study is
designed to ensure that the underpinning
assumptions of a commonly used age
estimation approach based on pulp volume
calculation are as accurate as possible.
MATERIALS AND METHODS
Ethics approval for this study was obtained
from the Human Research Ethics
Committee of the University of Western
Australia (Ref: RA/4/1/6797). This study
has been performed in accordance with the
ethical standards laid down in the 1964
Declaration of Helsinki.
Study sample
A total of 22 anonymized dental CBCT’s
were used in this study. All of them were
recorded with therapeutic purposes, with
the consent of the participants, and there
was no unnecessary or repeated radiation
exposure. All the images were previously
unidentified, and age and sex of each
individual was the only known
information. From these, 57% (n=12) were
female, age range 17-63 years, mean age
33.7, and 43% (n=9) were male, age
range=15-52 years, mean age 36.7. The
CBCT’s were obtained from the radiology
department of the University of
Kebangsaan, Malaysia, and the research
group INVIENDO from the National
University of Colombia, In both cases the
images were obtained using the 9000 3D
Extraoral Imaging System (Carestream
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
37
Dental, Atlanta, GA, USA) which had a
180˚ rotation and a field of view (FOV) of
50 mm by 37 mm. The radiation exposure
parameters were 8-10 mA, 70 Kv, with a
slice thickness of 0.076mm. The images
were saved in DICOM format. The
selected tooth to apply the different
segmentation approaches was the upper
right canine, or the left when the right was
absent (with Federation Dentaire
International (FDI) notation 13 and 23)
reconstructing one tooth per subject. Only
sound teeth, free of any restorations with
completed apex formation were included.
Measurement software ITK-SNAP version
3.4 (open source software,
www.itksnap.org) and Osirix®
(OnDemand 3D software CyberMed Inc,
Seoul, South Korea) were used in this
study. All the segmentations were
completed by a single observer (TYM).
All data was collated using Excel (version
2013 Microsoft Redmont, USA) and
statistical analysis was completed using R
Core Team version 3.1.3 (2015). (R: A
language and environment for statistical
computing. R Foundation for Statistical
Computing, Vienna, Austria. URL
http://www.R-project.org/.)
Description of the method
This study tested the comparative outcome
of three different ways of estimating the
pulp volume,5,13,14
dental age indicator used
in adults. The tests were carried out on the
root pulp chamber of upper canines (n=21),
to calculate the correlation between
automatic14
and manual segmentation5
(Part A)(Table 1) and cone shape approach
volume calculation13
(Part B)(Table 2).
The final part of the study (Part C)(Table
3) tested the variability of the results
obtained with different setting parameter
values combinations for automatic
segmentation of the pulp canal of one
multi-rooted tooth, as previously reported
in the literature14
and one single rooted
tooth. (Figure 1)
Part A. Automatic and manual
segmentation
Automatic segmentation was performed
using the software ITK-SNAP. (Figure 1.
A). Manual segmentation used software
Osirix ® and its 2D viewer, (Figure 1. B)
which allows the observer to go slice by
slice and manually select the boundaries of
the space to reconstruct, using the tool
polygon. The automatic segmentation
process in ITK-SNAP is called seed
region-growing. To apply it, the observer
sets up a “seed” inside the structure to
reconstruct, in this case the pulp chamber.
This seed grows and a volume is finally
obtained.
Automatic segmentation of the pulp was
generated using the same combination of
setting parameters through the entire
sample: Scale of Gaussian blurring: 3.0,
edge transformation contrast: 0.2, edge
transformation exponent: 4.0, expansion
(balloon) force: 1.0, smoothing (curvature)
force: 0.2, edge attraction (advection) force
2.0. In three cases the edge transformation
exponent needed to be adjusted to 0.05.
Regression models were run to establish
which of the setting parameters would
have the most significant influence on the
final results. Little changes in the Scale of
Gaussian generated the bigger changes in
the final obtained values (p< 0.001).
With manual segmentation two approaches
were used. Firstly, every fourth slice was
analysed as for the published method.
Secondly, the first and last slice was used
as the sample. To analyse the same length
of root in the automatic and manual
approaches, a length defined in the
automatic approach was set for the manual
approach.
Part B. Cone shape geometric
approximation
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
38
The geometric approximation of the root
canal to cone is a simple conservative
method and has been used for dental age
estimation in adults. Using Osirix®, ovals
of best fit were formed in the root canal at
the cemento-enamel junction (CEJ) level,
following the reported method.13
Secondly,
instead of best fit ovals, the boundaries of
the pulp canal were drawn using the tool
polygon. (Figure 1, C) The root length was
measured from the CEJ to the apex,
(Figure 1, D) and finally two different
volumes of cones were calculated per tooth
with a mathematical formula.
Part C. Automatic segmentation and
different setting parameters
combinations
As observed in part A, it is not possible to
apply the same combination of setting
parameters values to all teeth with
automatic segmentation. Taking into
account the advantage of this automatic
process16
twenty combinations of different
values for all the setting parameters (Table
3) were used to reconstruct the pulp
chamber of one lower first molar (FDI 36,
Male 23 year old Malaysian origin, slice
thickness 0.2mm) and an upper canine
(FDI 23, Male 31 year old Colombian
origin). The volumetric reconstruction with
each combination was completed twice per
tooth. The variation among the obtained
volume from the same tooth was
calculated.
Statistical analysis Shapiro Wilk normality test, mean,
standard deviation (SD), paired t-Test and
Pearson correlation coefficient, were
calculated to compare the results obtained
using the different segmentation methods
(Part A), cone shape volume approach
(Part B), and the obtained results when
different parameters are used to do the
automatic segmentation of the same tooth
(Part C).
Fig.1: Volumetric reconstructions, upper right canine using different methods Volumetric reconstruction of tooth 13 from a female individual, 36 years old, using the different
methodologies mentioned in this paper. A: Semiautomatic recontruction using ITK-SNAP software. B:
Manual segmentation using Osirix ® software. C and D: Cone shape geometric approximation, following the methodology reported by the author doing area measurement of he root canal at the
level of the CEJ (D) and length measurement of the root from the CEJ up to the root apex (C), using
Osirix ® software.
RESULTS
Part A. Automatic and manual
segmentation
Three data-sets were obtained from the
volumetric reconstruction of the root canal
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
39
of the canines using the different methods
(Table 1).
When automatic and manual segmentation
using each fourth slice were compared, the
Pearson’s correlation coefficient (r=0.83),
shows a greater correlation between them,
than between automatic and manual
segmentation using only the first and the
last slice (r=0.75) or between the two
manual segmentation methods (r=0.79).
However, this does not mean that manual
segmentation using every fourth slice and
automatic segmentation produce
comparable results. The paired t test shows
that there is a statistically significant
difference between the means of the results
of both manual segmentations and
automatic segmentation (p<0.001).
When comparing the obtained volumes, it
was observed that manual segmentation
produced volumes that are larger than
those obtained with automatic
segmentation. To facilitate the
understanding of this difference, a simple
mathematical analysis was used, taking the
obtained volume with automatic
segmentation as 100% of the volume.
Then the difference between the volumes
obtained with automatic segmentation and
both manual segmentation, were used in a
rule of three to calculate the percentage
this difference represents.
The results of this calculation showed that
the volumes obtained using every fourth
slice are in average 25% (1%-53%) larger
than those obtained with automatic
segmentation. Also, that using the first and
the last slice are in average 57% (12% to
210%) larger than those obtained with
automatic segmentation. The average of
the obtained volumes from both manual
segmentation methods is in general 41%
larger than automatic segmentation.
The volumes obtained doing manual
segmentation of each fourth slice were in
average 28% larger than those obtained
using only the first and the last slice.
However, some of them were in average
16% smaller (p>0.05). The mathematical
analysis was like the previously described,
but in this case, the volume obtained with
manual segmentation using only the first
and last slice was taken as 100% in the
rule of three.
Part B. Cone shape geometric
approximation
It was expected to obtain similar area and
volume values when using ovals of best fit
and the tool polygon following the outline
of the pulp chamber. Different than
expected, it was observed that with the tool
polygon the obtained areas and volumes
were noticeably larger (50%) than with the
ovals (Table 2). However, there is a strong
correlation coefficient between both
measured areas using the tools oval and
polygon (r=0.84) at the CEJ and the
obtained volumes (r=0.88).
When the obtained areas using the two
different tools are compared the data show
a big variability and a high SD, this effect
is diminished once the volume is
calculated. In this way, the length of the
root is what really determines the final
obtained volume.
Part C. Automatic segmentation and
different setting parameters
combinations
Repeatability of the automatic
segmentation for the first and the second
repetition for both teeth was evaluated
with the paired t test (r=0.7, p=0.99)
showing that there is no statistically
difference between both repetitions with a
95% level of confidence. The average
between the obtained volumes in both
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
40
repetitions was calculated. The volumes
obtained for the molar pulp chamber (FDI
36), ranged from 31.7mm3 to 53.74mm
3,
with a SD of 5.7and a variance of 33.
For the volumetric reconstruction of the
canine (FDI 23), the volume value ranged
between 29.8 mm3 to 50.8 mm
3, SD=7.12
and variance of 50.75. The SD for the
different parameters was not bigger than
0.6 and the sample variance was not
greater than 0.3
Table 1. Volume results of using automatic segmentation (Vol 1), manual segmentation using
just the first and last slice (Vol 2) and manual segmentation each forth slice (Vol3), of cone
beam computer tomography from upper canines (FDI 13, 23)
Individual Vol 1 (mm3) Vol 2 (mm3) Vol 3 (mm3)
1 10.87 10.6 13.2
2 16.03 17 19.7
3 16.4 20.9 19.8
4 9.309 12.9 14.8
5 5.478 7.1385 8.04
6 11.25 12.5 12.6
7 13.26 25.9 16.3
8 16.72 17 23.2
9 37.01 32.6 41.9
10 16.98 23.4 28.9
11 11.77 19.2 17.7
12 5.857 8.7131 11.7
13 9.107 13.3 28.3
14 17.24 33 29.8
15 12.76 27.5 21.1
16 15.87 16.1 27
17 13.2 19.7 22.6
18 11.61 19.7 16.5
19 24.52 35.3 40
20 15.51 22.1 22.1
21 17.6 29.3 35.5
Mean 14.68 20.18 22.41
DISCUSSION
With the introduction of computer vision
techniques for medical imaging and their
application in dentistry and forensic
sciences, the possibilities to propose
methods for age and sex estimation are
almost unlimited. Owed to the apposition
of secondary dentine, the anthropometric
assessment of the variation in the ratio
between size of the pulp chamber and size
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
41
of the tooth is still an acceptable dental age
predictor.14
The aim of this study was to
test the variability of the volume
measurements when different
segmentation methods are applied in pulp
volume reconstruction, because although it
would be expected that with volume
measurements the results for age
estimation were more reliable, the
literature shows the opposite. To find out
an explanation to the lower accuracy of the
methods based on volume reconstruction,
in this study we tested three different
methods doing only pulp volume
reconstruction.
Table 2. Cone shape approach results using the tool polygon (Pol) and oval (Oval). Pulp area
(in mm2) at the CEJ level and volume (in mm
3) calculation with the measured root length (in
mm).
Area Area Pol Area Oval Root length Vol Pol Vol Oval
1 22 20 1.55 11.2 10.2
2 29 30.5 1.46 14.1 14.8
3 28 24.5 1.46 13.6 11.9
4 20 9.85 1.51 10.0 4.9
5 21 16 1.04 7.3 5.5
6 16 13.5 1.56 8.3 7.0
7 46 29 1.86 28.6 18.0
8 37 20.5 1.64 20.3 11.2
9 52 41 1.38 24.0 18.9
10 32 26.5 1.63 17.4 14.4
11 30 17 1.28 12.8 7.2
12 34 16 1.38 15.8 7.4
13 32 22 2.10 22.4 15.4
14 28 14 1.71 16.1 8.0
15 42 28.5 1.79 24.9 16.9
16 27 16 1.71 15.4 9.1
17 25 17.5 1.96 16.2 11.3
18 35 25.5 1.47 17.2 12.5
19 58 44.5 1.73 33.9 26.0
20 39 26.5 1.52 19.8 13.4
21 46 24.5 2.17 33.3 17.7
SD 8.7 10.86 7.45 5.2
The methodology analysed in this study,
using CBCT, seems to be no more
accurate than those methods based on
radiographs for dental age estimation in
adults, regardless the sample size of the
study which ranges from 19 individuals,
analysing only 12 canines7 to 403
individuals analysing only the pulp
chamber of first molars.14
This is clear
when the reported accuracy of the different
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
42
methods is compared. The reported mean
absolute error using automatic
segmentation of the first molar’s pulp
chamber is 6.26 years at best.14
The cone
shape geometric approach of pulp and
tooth has a standard error of estimation of
± 11.45 years,13
and finally, manual
segmentation of pulp and tooth, has a
prediction interval of ± 12 years.5
Table 3. Setting parameter combinations used in part C
Repetition
Scale of
Gaussian
Edge
contrast
Edge
transformation
exponent.
Smoothing
force
Average
molar volume
mm3
Average
canine
volume mm3
1 2.14 0.09 4 0.2 38.415 36.58
2 3 0.05 3 0.2 45.775 49.7
3 2.05 0.05 3 0.2 34.525 49.7
4 2.5 0.05 3 0.2 46.075 41.81
5 2.5 0.1 2.5 0.2 49.38 48.87
6 2.5 0.2 2.05 0.2 53.74 48.94
7 2 0.1 2.5 0.2 43.55 39.27
8 2.15 0.09 4 0.2 36.53 40.26
9 2.15 0.09 4 0.3 38.94 39.76
10 2.15 0.09 4 0.35 42 39.38
11 3 0.05 3 0.3 47.29 50.89
12 3 0.05 3 0.35 43.555 48.92
13 3 0.05 3 0.4 44.69 48.9
14 2.05 0.05 3 0.3 38.695 35.98
15 2.05 0.05 3 0.35 38.79 35.89
16 2.05 0.05 3 0.4 38.46 36.04
17 1.5 0.05 2.51 0.2 34.3 31.92
18 1.5 0.05 2.5 0.2 34.955 30.08
19 1 0.1 3 0.2 31.73 29.83
20 2 0.05 4 0.2 36.405 35.10
SD 0.53 0.03 0.59 0.07 5.74 7.12
Variance 0.28 0.001 0.35 0.005 32.94 50.75
There are 3 parameters available in ITK-SNAP software that are not listed, as they were constant for all the
reconstructions: Edge attraction force (=2) and step size (=1) and smoothing force which was changed from 1 to 0.5 only for the 18th combination.
Other methods also using automatic
segmentation of canines reported a
prediction interval of 3.47 years at best.17
When these reported results are compared
with some of the most commonly used
adult age estimation methods utilising
dental radiographs, such as Cameriere et
al.3 (with reported mean predictor errors of
2.37 years18
to 11.01 years19
(tooth/pulp
area ratio)), or the method developed by
Kvaal et al.2 (pulp/tooth-linear
measurements ratios with reported
standard estimation errors of ±9.367
years,20
) it is possible to observe that the
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
43
use of CBCT and dental structures volume
reconstruction, do not improve the final
results for adult age estimation. The
relation between the lack of the accuracy
of the mentioned methods for age
estimation and the different methods for
volume reconstruction are presented as
follow:
Part A. Manual and automatic
segmentation may produce similar results,
as observed in this study (r=0.83). Manual
segmentation is time consuming, difficult
to perform and prone to be influenced by
the subjectivity of the observer, and
personnel trained in this aspect is
necessary.21
Additionally, it is not accurate
enough to estimate the variation of the
volume in small anatomic structures, such
as the root canal, as observed in this study.
Although there are different methods for
automatic image segmentation, the first
problem faced in the bio-medical area, is
the exclusive dependence on gradient or
intensity analysis without using anatomical
information.21
In the case of automatic
segmentation, with ITK-SNAP software,
although the software chooses which
pixels will be included in the
segmentation, the observer finally decides
how to adjust the parameters to control the
algorithms in the segmentation, making
this method prone to a certain degree of
subjectivity from the observers. These
parameters may change from one CBCT to
another. Unfortunately, in the previous
study using this software the values of the
setting parameters were not mentioned.14
In this study it was also observed that
although all the CBCT were obtained from
machines with the same reference, and
under similar exposure conditions (slice
thickness, Kv, mA and time of exposure),
and the same parameters for automatic
segmentation, the interaction of the seed
region-growing with the boundaries of the
structure to reconstruct may also differ
from one CBCT to another. For this
reason, it is not possible to follow the
recommendations of the ITK-SNAP
manufacturer, who recommends to keep
the same parameters among different
CBCT, and it is neither possible to
guarantee the uniformity of the
segmentations obtained.14
In this study, we also observe that small
changes in the values of the setting
parameters can generate significant
variation in the final obtained volumes
with automatic segmentation, even though
the segmentation was made on the same
CBCT, same tooth and same anatomic
region.
Which means that the final volume will be
always the same under the same
parameters in the same CBCT and
anatomic region, but these parameters
generally need to be modified from one
CBCT to another, and in the same way,
small changes in the parameters alter the
final volume.
Part B. With the aim of simplifying the
measurement of the tooth structure
volume, a cone shape geometric approach
was proposed (Part B).13
The developers of
this method were aware of the main
disadvantages of this proposal:
measurements inaccuracy and subjectivity.
They also reported that this method tends
to underestimate the real volume of the
tooth structures (56% to 67%), which in
theory would not affect the final pulp/tooth
ratio that was calculated to estimate the
age.
To test this method, we used two differ
approaches for doing the volume
calculation. The first, following the
published methodology13
displaying ovals
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
44
at the CEJ, and a second one selecting
manually the outline of the root canal at
the CEJ, using the tool polygon. As
observed in the results section, despite the
difference between both area
measurements, at the CEJ, once the
volume is calculated the difference
decreases. Neither of these two
approaches is recommended to carry
outpulp volume measurements, , firstly
because of the subjectivity of the observer,
who only counts with the naked eye to
display one or another and secondly,
because both bring a distorted
representation of the root canal, ignoring
the different variations in its internal
shape.
Part C. In this study, it has been shown,
that there are different parameters that
affect the final volumetric reconstruction
of any anatomical region. The scale of
Gaussian, or blurrier factor22
was found to
be the most relevant when doing automatic
segmentation. To increase the value of the
Gaussian scale, allows the observer to
eliminate certain noises in the image,
which affect the “growing of the seed”.
However, the bigger the value the
Gaussian scale is, the more principal
structures and details will be lost.23
This
would mean that the initial volume of the
pulp chamber will be magnified.16
Although automatic segmentation is less
prone to the subjectivity of the observer
than manual segmentation, in this study we
observed that it is not possible to keep the
same volume reconstruction parameters for
all the CBCT, and that minimum changes
may produce significant variations even
though they are done on the same tooth.
The volume obtained with this tool must
be understood as an approximation to the
real volume of the structure being
measured
Taking into consideration the reported rate
of secondary dentin formation is 6.5
μm/year for the crown and 10 μm/year for
the root,24
the analysed methods in this
study are not sensitive enough to detect
such small dimension changes, generating
a big variation of the measurements, which
could explain the greater error of
pulp/tooth volume based methods for age
estimation when compared with simpler
methods based on linear2 or area
measurements3 on dental radiographs.
Previous research in the biomedical area
have highlighted the problems related to
semi-automatic segmentation, and
specifically, to the process that the
software uses to select which pixels or
voxels to be included in the final volume
reconstruction. To overcome this problem,
they have elaborated the probabilistic
anatomic atlas, which facilitates the
segmentation of an organ of interest.21
When doing the semi-autographic
segmentation of teeth and pulp chambers,
different obstacles were observed. Firstly,
owing to the similar density of dentine and
bone and the irregularity of the periodontal
ligament, it was not possible to obtain a
volumetric reconstruction of the tooth as it
is in for the pulp chamber. This is the
reason why the automatic tooth volume
reconstruction was not analysed.
Secondly, owing to the large variety in the
shape of the pulp chamber in the apical
third of the tooth, there was always a leak
of the seed region -growing in to the
dentine. To create a probabilistic atlas for
dentistry could help to overcome these
issues, and help the dentist and forensic
dentist to implement more accurate and
easier methods for automatic segmentation
and volume reconstruction. Thirdly,
although the automatic reconstruction of
the pulp chamber of molars may be
understood as a simple process, it may be
Reliability and repeatability of pulp volume reconstruction through three different volume calculations. Penaloza et al.
45
more reliable to use other methods for age
estimation when using molars.
CONCLUSIONS
Based on the results of this study, it is
possible to affirm that the obtained volume
measurements with any segmentation
method must be understood as an
approximation of the measured structure
and not as the real volume. In the same
way, manual segmentation could produce
volume values that are even more
inaccurate, and should be avoided in future
studies.
Although the volumetric reconstruction
and P/T volume ratio has not shown better
results than methods based on dental
radiographs, it is worth to persevere with
the research in this area with an
interdisciplinary team to build software
that can reliably reconstruct pulp and tooth
volumes for forensic purposes.
ACKNOWLEDGEMENTS
The authors of the study want to thank to
Nurul Firdaus, Dr Shahida Mohd Said and
Dr Shalini Kanagasingam from the
Radiology Unit, Dental Faculty University
of Kebangsaan Malaysia. To the Forensic
Science Centre from The University of
Western Australia and to the research
group INVIENDO from the National
University of Colombia.
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17. Tardivo D, Sastre J, Catherine J-H, Leonetti G, Adalian P, Foti B. Age determination of adult individuals by three-dimensional modelling of canines. Int J Legal Med. 2014;128(1):161-9. 18. Cameriere R, Cunha E, Sassaroli E, Nuzzolese E, Ferrante L. Age estimation by pulp/tooth area ratio in canines: Study of a Portuguese sample to test Cameriere's method. Forensic Sci Int. 2009;193(1–3):128.e1-.e6. 19. Babshet M, Acharya AB, Naikmasur VG. Age estimation in Indians from pulp/tooth area ratio of mandibular canines. Forensic Sci Int. 2010;197(1–3):125.e1-.e4. 20. Karkhanis S, Mack P, Franklin D. Age estimation standards for a Western Australian population using the dental age estimation technique developed by Kvaal et al. Forensic Sci Int. 2014;235(0):104.e1-.e6.
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APPENDIX 7. A new proposal to overtake population group differences for dental age
estimation in adults through pulp/tooth volume calculation. Pilot Study
In press version. Under revision.
Marroquin, T.Y., Karkhanis, S., Kvaal, S. I., Vasudavan, S., Nurul F., Kanagasingam S., D.
Franklin., E., Kruger, E., & Tennant, M. A new proposal to overtake population group
differences for dental age estimation in adults through pulp/tooth volume calculation. Pilot
Study. Submitted to Journal of Forensic Sciences.
A new proposal to overtake population group differences for dental age estimation in adults
through pulp/tooth volume calculation.
Abstract
Objectives.
The formation of secondary dentine on the walls of the root canal, has been used as an age
indicator in adults. The aim of this study is to propose a model for dental age estimation in
adults, regardless of their nationality or ethnicity by volume reconstruction of only a fraction of
the tooth to obtain linear regression models and an equation for dental age estimation.
Materials and Methods
Eighty-one anonymized cone beam computed tomography images obtained from two different
population groups were used. Only sex and age information was known. One group had a Latin-
American background (Colombian individuals aged 23 to 71 years) and the other had an Asian
background (Malaysian individuals aged 15 to 58 years) The analyzed tooth was the maxillary
canine. The used software was ITK-SNAP version 3.4 (open source software, www.itksnap.org),
to do automatic volume reconstruction of the cervical third of root and root canal.
Results
Analysis of the samples showed that the ages were unequally distributed in the two samples, but
by combining them a more equal age distribution was obtained. The correlation coefficient
between pulp/pulp+tooth volume ratio increased when data from individuals of both
populations were included in the same statistical analysis (R2=0.42). A formula for age estimation
regardless the origin of the individual was proposed: Age=67.104+(-434.741 x p/pt) (Standard
error of estimation=±11.4 years)
Conclusion
It has been established that methods for age estimation must be population specific. This study
presents an analysis that included data from individuals that are ethnically different and
geographically separated, obtaining promising results.
Key words:Computed tomography, secondary dentine, age estimation, ethnic variation, Forensic
Anthropology, Population Data
*Manuscript (without author details)
Click here to view linked References
Introduction
Much has been said in biological sciences about race and ethnicity since 1775 when Johann
Friedric Blumenbach defined five different races: Caucasians (whites), Mongolians (East Asians)
Malayans (South Asians), Negroids (Black Africans) and Americans (First Nations) (1), since then,
different studies followed this structure to analyze and interpret data and present results,
phenomena that has been named as scientific racism (2). Owed to the different nomadic and
migration processes in human history, this racial classification is day by day less accurate and
practical (2). Nevertheless, in forensic sciences it is still stipulated that the ethnic background of
an individual is of paramount relevance, to formulate a biological profile, and to clarify the
identity of living or deceased individuals, next to sex, stature and age (3). In terms of age
estimation, many methods have been proposed for individuals of different ages, based on bone
and tooth formation or degenerative changes with age (4).
Methods founded on the radiological analysis of dental development, have shown acceptable
accuracy, owed to the genetically controlled process of tooth formation, which seems to be
similar for individuals from different group of populations (5). The most recent systematic
review about age estimation based on tooth and bone formation (6,7) have stated that those
studies claiming that there are differences among group of populations may be incurring on a
selection bias inducing a phenomenon called age mimicry (6, 7), which has caused the erroneous
need to generate specific population formulae for age estimation, fact that could be also
affecting the results of studies for dental age estimation in adults
Simultaneously, age estimation in adults, by means of non-invasive analysis, is still a challenge for
scientists of different areas, specially, those who are involved in forensic investigations. Although
different methods have been proposed, there is no consensus about a unique method to be
applied to individuals from different countries, and even more, it has been claimed that methods
for age estimation must be population specific (8). Additionally, the few changes that bones and
teeth have after body maturation, are a setback for the accuracy of the existing methods.
One of the first methods for dental age estimation in adults, stablished that the formation of
secondary dentine on the wall of the root canal could be considered an age predictor in adults
(9). Based on the negative correlation of pulp/tooth ratio size with age, different non-invasive
methods were proposed, doing first, linear measurements (10), then area measurements, in
dental radiographs (11) and lastly volume measurements from dental tomography (12).
The aim of this study is to generate a model for dental age estimation in adults, regardless their
nationality or ethnic background, by reconstructing only a fraction of the tooth to obtain linear
regression models and an equation for age estimation.
Materials and methods.
The sample for this cohort study encompasses 81 cone beam computed tomography (CBCT)
obtained from two different population groups. Latin-American (Colombian individuals aged 23
to 71 years, 60% female (n=23) and 40% male (n=15)) and Asian (Malaysian sample individuals
aged 15 to 58 years 46% female (n=20) and 54% male (n=23)) previously collected for different
dental diagnosis and treatment procedures, with the respective informed consent. All the images
were anonymized keeping information about sex and age.
Table 1 shows the age and country distribution. Although the CBCT were obtained in different
institutions, in both cases the reference of the used device was the same: Kodak device,
reference K9000-3D (exposure parameters: scanning time: 10.8 s, 3-15 mA, 60-85kVp, field of
view FOV: 5.2 cm x 5.2cm to 5.5cm to 5.5cm, 180° rotation, slice thickness 0.076-0.2 mm) The
images were shared via online under the strictest security parameters to warrantee the integrity
and safety of the data.
The analyzed tooth was the maxillary canine, left or right, one per individual, as previous studies
have shown no right/left difference in tooth secondary dentine production (13). The
reconstructed root fraction was in all the cases 5 mm from the highest point of the vestibular
cemento-enamel junction, towards the root apex, with the aim to include only the cervical third
of the root.
Inclusion criteria: The included roots portions were from sound teeth, teeth with no evidence of
physical trauma, free of active caries, free of evidence of periapical disease, without signs of pulp
pathology and free of cervical lesson of any nature. The analysis also included teeth with small
coronal fillings, with at least 2 mm of dentine between the tooth restoration and the pulp
chamber, which is assumed to have negligible effect on the root portion.
The used software was ITK-SNAP version 3.4 (open source software, www.itksnap.org), doing
automatic reconstruction of the root canal and root. In certain cases, it was necessary to
manually correct the root segmentation. The measurements were collected by only one
observer, who had been previously trained in the use of this software. All the data were
collected in an excel spreadsheet, using Excel (version 2013 Microsoft Redmont, USA), before
and after manual correction of the image segmentation. Data analysis was performed with R
Core Team version 3.1.3 (2015). (R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/).
Results
Pearson correlation coefficient test was calculated to observe if there was any difference
between the volume values obtained for pulp and tooth doing automatic segmentation and after
manual correction slide by slide. It was found that there is not significant difference between
both measurements (r=0.98). Two different proceedings were tested to obtain the pup/tooth
ratio. First dividing the volume of the pulp by the volume of the tooth, and second, dividing the
volume of the pulp by the sum of the volume of the tooth and pulp. It was observed that the
second approach generated a higher correlation coefficient (R2=0.34 vs R
2=0.42). The
determination coefficient between age and the pulp/pulp+tooth ratio (p/pt) for the individuals
of each group was R2=0.26 for the Colombian sample and R
2=0.38 for the Malaysian sample and
for the total sample using the data of both groups in the same analysis, R2=0.42.
In regards to tooth condition, it was observer that those teeth with small fillings did not generate
any outlier that could affect the linear regression model (Figure 1).
The linear regression models were generated to produce a formula for dental age estimation
from the combined sample. The formula was:
Age=67.104+(-434.741 x p/pt)
where p/pt is the ratio between the volume of the pulp divided by the sum of the volume of pulp
and tooth. The standard error of estimation (SEE) is ±11.4 years (R2=0.42)
Discussion
It is undeniable that dentistry has done a valuable contribution to anthropological sciences
bringing insights about human evolution. In the same way, dental analysis has become an
important tool for human identification in forensic sciences, in both fields, anthropology and
forensics, the concepts about racial and ethnic differences have deep roots and a significant
influence in research (14). However, in a changing world, where day by day the biological
boundaries between individuals of different backgrounds are constantly vanishing, to think
about methods for age estimation, that are regionally, racially, or ethnically focused must be re-
evaluated.
The last systematic review about Demirjian’s developmental stages of third molars (6) and the
Greulich and Pyle’s bone atlas (7) for age estimation in children and adolescents, exposes a
selection bias called age mimicry, present in numerous publications. This bias explains the
observed results variation, which has been wrongly associated to the population origin and
ethnicity of the participants, instead to the intrinsic characteristic of the used sample.
To avoid age mimicry, studies must have a study population with an even age distribution, large
samples, same number of individuals in each age group, appropriate upper and lower age limits
facilitating the observation of the different age related changes, and ideally samples that include
data of individuals from different regions, to really conclude whether regional differences are
important for age estimation in children (6) and probably in adults. Subsequently, it is necessary
to perform multi-population studies in adults. This research, is a good start to disclose the
population related differences in age estimation in adults when secondary dentine production is
analyzed as an age predictor.
In this study, it was found that the production of secondary dentine and the narrowing of the
root canal with age, which is one of the used parameters for dental age estimation in adults, has
a similar behavior in individuals that are not only ethnically different but also geographically
separated. Also, that the separate generation of regression models, for each one of the
population groups, would have generated age mimicry, owed to the unequal age distribution of
both samples, as in the Malaysian group the younger group dominates, while for the Colombian
group the middle age dominates (Table 1). By adding both samples it is possible to obtain a more
even age distribution and also a higher correlation coefficient between age and p/pt ratio
(R2=0.42). However, for future studies it is recommended to have a larger sample with the same
age distribution for the different populations to analyse, and same number of individuals among
the different age groups, avoiding age mimicry, which would generate more reliable results.
Up to now different methods and formulae have been published to estimate dental age in adults
(15). Nevertheless, few studies have tested the proposed formulae in groups of population
different from those included in the original studies. In the few studies that have done this
analysis, it has been suggested that local formulae bring more accurate results. (16) With the
results of the present study it could be possible to affirm that it is necessary to include the data
of individuals of different populations with equal age distribution in the same statistical analysis
to observe that there is not significant difference between population or ethnical groups, in
regards to the production of secondary dentine, and also to generate an equation that can be
used regardless the origin of the individual.
Furthermore, there are other factors that can affect the length, area and the total volume of the
tooth, as bruxism and attrition (17), among others, that also affect the production of dentine in
the crown and apical third of the root. These factors are not ethnically related but individual
dependent. By analyzing sound cervical root third of canines, or any other teeth, the problems
related with tooth attrition are diminished. In this study, the maxillary canine was selected as the
tooth to analyze, owed to the reported longer survival, compared to other teeth (18). It was also
selected to measure only the volume of the cervical third, as it has been reported that
pulp/tooth ratios, had a higher correlation with age at the cervical root level and that the
correlation with age decreased towards the apex, for different types of teeth, when doing linear
(19) or volume (20) measurements.
In the first studies, that analyzed the production of secondary dentine with age, (9) the proposed
methods required not only the use of extracted teeth but also the destruction of the sample,
which is unethical in a modern context. The use of different radiological techniques has allowed
researchers to analyze age indicators in a non-invasive and more conservative way. The use of
CBCT to analyze and obtain the volume of any anatomical structure is much easier, cheaper,
faster and has great potential for applications in anthropological and forensic studies. In this
study, this radiological technique allowed the observer to separate only a fraction of the tooth,
calculate its volume, and warrantee not only the integrity of the individual but also the
uniformity of the tooth sample size.
In terms of accuracy, although the obtained error exceeds the threshold that must accomplish a
method for age estimation in adults (±10 years) (21), the results of this study (SEE=±11.4 years)
are not so different to previous studies that used data of individuals from the same country or
belonging to the ethnic group (±12.5 years at best). (22)
Conclusion
It has been claimed that the modern world would testify the end of ethnicity, and also that it
changes according to circumstances, (14) This study proposes the use of data of individuals not
only from different countries but that also have been historically cataloged as members of
different racial and ethnical groups. It was found that by calculating the pulp/tooth+pulp volume
of only one part of the tooth it is possible propose a formula to estimate the age for adult
individuals regardless their origin.
Ethics
This study received ethics approval from the Human Research Ethics Committee of The
University of Western Australia (Ref: RA/4/1/6797).
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Figure 1. Scatter plot showing the correlation between age and the pulp/pulp+tooth (p/pt) volume
ratio. (P/PT ratio) R2=0.42.
0.01
0.03
0.05
0.07
0.09
0.11
0.13
10 30 50 70
p/p
t ra
tio
Age
Figure 1
Age range Mal Col Total %
15-20 12 0 12 15
21-30 13 2 15 18
31-40 6 11 17 20
41-50 9 12 21 26
51-60 3 7 10 12.3
61-71 0 6 6 0.7
Total 43 38 81 100%
Table 1. Distribution of the individuals for age in years and country; Malaysia (Mal) and
Colombia (Col)
Table 1