Upload
others
View
21
Download
0
Embed Size (px)
Citation preview
Qiyue
(James)Zhang
Anusha Verankki
bull Lesion detection through palpation bull This is not applicable in the detection of smaller internal
abnormal tissues bull invention of the MRI in 1970s the idea was around since
1930s bull Late 1990s MRE is invented by clinic doctors and
scientists at Mayo Clinic as an alternative detection of liver biopsy
bull Using an MRI quantitatively to image and characterize the viscoelastic properties of tissue in vivo
bull More efficient comfortable safer faster and less expensive than biopsy
bull today this is used to detect lesion tissue (cancer fibrosis) in liver heart brain and skeletal muscle
History of MRE
2
Why MRE
Most of the conventional
medical imaging techniques
(CT MRI and US) are not
capable of depicting
properties assessed by
palpation(like stiffness of
tissue)
Property assessed by
palpation is called Elastic
Modulus Elastic modulus
gives information on
palpation on a much larger
scale than CT US and MRI
3
4
5
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
bull Lesion detection through palpation bull This is not applicable in the detection of smaller internal
abnormal tissues bull invention of the MRI in 1970s the idea was around since
1930s bull Late 1990s MRE is invented by clinic doctors and
scientists at Mayo Clinic as an alternative detection of liver biopsy
bull Using an MRI quantitatively to image and characterize the viscoelastic properties of tissue in vivo
bull More efficient comfortable safer faster and less expensive than biopsy
bull today this is used to detect lesion tissue (cancer fibrosis) in liver heart brain and skeletal muscle
History of MRE
2
Why MRE
Most of the conventional
medical imaging techniques
(CT MRI and US) are not
capable of depicting
properties assessed by
palpation(like stiffness of
tissue)
Property assessed by
palpation is called Elastic
Modulus Elastic modulus
gives information on
palpation on a much larger
scale than CT US and MRI
3
4
5
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Why MRE
Most of the conventional
medical imaging techniques
(CT MRI and US) are not
capable of depicting
properties assessed by
palpation(like stiffness of
tissue)
Property assessed by
palpation is called Elastic
Modulus Elastic modulus
gives information on
palpation on a much larger
scale than CT US and MRI
3
4
5
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
4
5
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
5
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Magnetic resonance Elastography
Excitation application ‐dynamic (vibrations) image the propagation of
s‐waves produced by the excitation of the tissue
Measurement of Tissue response to Applied Stress MRI
Mechanical parameter estimation acquiring data to estimate the mechanical properties of
the tissue Quantitative and qualitative data are recorded to produce an elastogram
6
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
How does it work
7
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
1
Generating mechanical waves in the tissue
2
Acquiring MR images depicting the propagation of the waves
3
The resulting data are processed to generate quantitative images
displaying the stiffness of tissue
8
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Deforming the target
S‐wave
‐one of the two main typesof elastic
body waves
‐The S‐wave moves as ashear or
transverse wave
‐Shear wave propagationin biological tissue isrelated to stiffness
9
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
How to generate S‐wave
Oscillating transducer(actuator)
‐MR safety‐MR compatibility
‐3 types of mechanical drivers ElectromagneticPiezoelectricFocused‐ultrasound‐
based
10
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Electromagnetic actuator
11
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Piezoelectric actuator
12
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
13
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
How to detect deformation
Phase‐contrast MRI‐
motion‐
sensitizing gradient
‐
Phase shift in received MR signal
14
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Mechanical model
Mechanical properties of
tissue
‐first Lame constant(λ)
‐second Lame constant(μ)
‐bulk modulus K
= λ
+ (2 3)μ
‐Poissonrsquos ratio(v)
‐Youngrsquos modulus(E
15
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Harmonic motion model
Helmholtzinversion
21 independent parameters
required
16
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
17
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
18
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Applications Liver fibrosis
Causes hepatic diseases chronic Hepatitis C ALD
( alcoholic liver disease) fatty liver disease autoimmune
hepatitis
Response to injury scar formation But in fibrosis the
healing process goes wrong
Fibrosis is the accumulation of tough fibrous scar tissue in the
liver
Fibrosis
if left untreated leads to cirrhosis
Other imaging methods (CT MRI) are very limited in
detecting fibrosis before it has advanced to irreversible
cirrhosis
19
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
20
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Using MRE
21
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Patient A
normal liverMean shear
stiffness of
21kPa
Patient BHepatic
steatosis and
mild fibrosis 48 kPa
Patient CChronic liver
disease L most
areasgt 8kPa in
shear stiffness
22
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
MRE vs Biopsy
Highly accurate in detecting liver fibrosis
Much more efficient than a liver biopsy there
is a chance of underestimation of hepatic fibrosis by about 20 to 30‐
sampling error
94 to 97 accuracy
Most patients tend to delay taking a biopsy
since it is an invasive procedure
The earlier the hepatologist knows the
sooner the treatment can be given 23
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Brain MR Elastography
Brain elasticity data can be used to detect certain diffuse diseases of the brain that are not well evaluated
by conventional imaging methods ‐Alzheimers‐Hydrocephalus‐focal brain lesions‐Multiple Sclerosis‐obtaining quantitative measurements of Elastic
modulus of cerebral tissue is of interest in biomechanical studies of brain trauma and in the
development of neurosurgery simulation techniques
24
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
MRE system designed for the brain
lsquoArsquo
applies vertical
displacement to the head
lsquoBrsquo
applies horizontal
displacement to the head
via a bite block
The θ
between the two can
be varied to image the
waves at various stages of
propagation
25
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
MRE system for a brain
Technical Challenges bullIntroducing s‐waves through the bony calvariumbullPerforming efficient sampling and processing of a 3D displacement field
Developed using a soft pillow like(passive) vibration (50 Hz) source to produce
intracranial s‐waves
26
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Hydrocephalus
Obstruction of CSF flow in either
the lateral ventricles or the
subarachnoid space
Results in an increased size of
ventricles and therefore an
increase in intracranial pressure
(ICP)
MRI and CT assist in diagnosis
but they have limitations
These techniques only detect
ventricular enlargement which
can be confused with cerebral
atrophy or periventricular
leukomalacia (shrinkage of
periventricular white matter)
27
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
MRE diagnosis
Top normal patientBottom patient with hydrocephalus
28
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
MRE for detection of Cardiac disease states
HFPEF heart failure due to preserved ejection fraction
Hypertrophic cardiomyopathy
Load independent contractility
MI Myocardial infarction
29
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Heart failure due to preserved Ejection fraction
30
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
HFpEf
Preserved ejection fraction
Efgt50
40 to 70 of heart failure
cases
Heart is contracting normally
but the ventricle walls are
stiff and do not relax
properly Less blood is
entering the heart during
systole
Patients with pEf also had
hypertension and coronary
artery diseases
31
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Stiffness results
32
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
Future directions
Mechanical driver‐wave frequency‐multiple driver source
Data Processing
‐encoding process‐high‐speed 3D imaging‐new mathematical model for estimation of
tissue properties
33
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
References
Mauduca A Dynamic Magnetic Resonance Elastography Mayo Clinic College of
Medicine
Araoz
P Kolipaka
A mayo Clinic (Producer) (2010)Cardiac MRE [Web Video]
Retrieved from httpwwwyoutubecomwatchv=NyvjE5DpIis
Bachir T (2009)
Advanced MRI methods for assessment of chronic liver disease
Ehman R L (2009) Magnetic Resonance Elastography An emerging Tool for
Cellular Mechanobiology Mayo Clinic Rochester MN USA
Grenier
D Milot
L Peng
X Pilluel
F Beuf
O (2007) A Magnetic Resonance
Elastography
approach for liver investigationProceedings
for 29th
Annual
International Conference of the IEEE EMBS Lyon France
HighleyMan L Franciscus A (2011) Disease progression What is fibrosis
Hepatitis C Support Project Retrieved from
httpwwwhcvadvocateorghepatitisfactsheets_pdfFibrosispdf
Juergen
Braun Karl Braun and Ingolf
Sack Electromagnetic Actuator for
Generating Variably Oriented Shear Waves in MR Elastogrphy Magnetic
Resonance in Medicine 50220‐222(2003)
Kolipaka
A
Araoz
PA
McGee
KP Manduca
A
Ehman
RL (2010) Magnetic
resonance elastography
as a method for the assessment of effective myocardial
stiffness throughout the cardiac cycle
pubMed Retrieved from
httpwwwncbinlmnihgovpubmed20578052
McGee KP Lake D Mariappan
Y HubmayrRD Manduca
A Ansell K and Ehman
RL Calculation of shear
stiffness in noise dominated magnetic resonance elastography
data based on
principal frequency estimation 2011
Phys Med Biol
56
4291 34
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35
References
Owan
TE Hodge DO Herges
RM Jacobsen SJ Roger V Redfield MM (2006)
The new England Journal of MedicineTrends
in prevelance
and outcome of
Heart failure with preserved Ejection Fraction Original article Retrieved from
wwwnejmorg
S Papazoglou U Hamhaber J Braun I and I Sack Algebraic Helmholtz inversion
in planar magnetic resonance elastography Phys Med Biol 53(2008)3147‐3158
Paulsen KDPattison
AJ Perreard LM Weaver JB Roberts DW
(2011)Hydrocephalus detection using intrinsically‐activated mre Academic paper
Thayer School of Engineering Darthmouth
College Hanover New Hampshire
US Retrieved from
httpsubmissionsmiracdcomismrm2011proceedingsfiles41pdf
Zion Tsz
Ho Tse Yum Ji
Chan Henning Janssen Abbi
Hamed Ian Young and
Michael Lamperth Piezoelectric actuator design for MR elastography
implementation and vibration issues Int
J Med Robotics Comput
Assist Surg
2011 7353‐360
YOGESH K MARIAPPAN KEVIN J GLASER AND RICHARD L EHMAN
Magnetic Resonance Elastography A review Clin Anat 23497ndash511(2010)
Y Zheng G Li M Chen Q C C Chan S G Hu X N Zhao R L Ehman E Y
Lam and E S Yang Magnetic Resonance Elastography
with Twin Pneumatic
Drivers for Wave Compensation IEEE(2007)
35