Original Research

Automated T2* Measurements Using SupplementaryField Mapping to Assess Cardiac Iron Content

Brian A. Taylor, PhD,1 Ralf B. Loeffler, PhD,1 Ruitian Song, PhD,1 Mary E. McCarville, MD,1

Jane S. Hankins, MD, MS,2 and Claudia M. Hillenbrand, PhD1*

Purpose: To develop and evaluate an algorithm that auto-matically identifies high-susceptibility areas and excludesthem from T2* measurements in the left ventricle (LV) formyocardial iron measurements.

Materials and Methods: An autoregressive moving aver-age (ARMA) model was implemented on multigradientecho scans of 24 patients (age range 3–45 years, 10male/14 female). Voxels with relatively high susceptibility(>3 Hz/mm) were flagged and deselected from the T2* cal-culations for iron quantification. The mean, standarddeviation, and coefficient of variation (CoV) of the ARMA-defined region were compared to the CoV of four distinctregions of the LV and the entire LV using a Student’s t-test (a ¼ 0.05).

Results: The CoV of T2* values obtained by the ARMAmethod are comparable with that in the interventricularseptum (IS), where susceptibility was the lowest (CoV ¼0.31). The ARMA method provides a greater area (51.9 6

13.7% of the LV) to measure T2* than that using the ISalone (21.1 6 3.4%, P < 0.0001). Areas where low suscep-tibility are measured corroborate with areas reported inprevious studies that investigated T2* variations through-out the LV.

Conclusion: An automated method to measure T2* relax-ation in the LV with minimal effects from susceptibilityhas been developed. Variability is reduced while coveringmore regions for cardiac T2* calculation.

Key Words: cardiac MR; iron overload; T2* mapping; sus-ceptibility; multigradient echo (mGRE); autoregressivemoving average (ARMA) modelingJ. Magn. Reson. Imaging 2013;38:441–447.VC 2013 Wiley Periodicals, Inc.

HEMATOLOGICAL CONDITIONS such as b-thalasse-mia major and sickle cell disease often require chronicblood transfusions for disease management. However,multiple transfusions result in an excessive accumu-lation of iron, which can be deposited in organs suchas the heart, liver, and pancreas (1–3). Iron overloadin the heart can lead to life-threatening conditionssuch as arrhythmias and cardiomyopathy (4). Hepaticiron concentration and serum ferritin levels in periph-eral blood do not accurately predict the presence ofhigh amounts of iron in the heart (5). Therefore, directmeasurements of myocardial iron, either by invasivebiopsy or preferably by noninvasive means, are neces-sary to monitor cardiac iron deposition in patientsreceiving chronic blood transfusions.

One method to noninvasively measure cardiac ironis T2* mapping of the mid-papillary short axis of theleft ventricle (LV) (5–10). Anderson et al (5) showedthat at 1.5T, patients with T2* values of 20 msec orless in the LV are at high risk of developing iron-induced cardiac complications. Typically, T2* meas-urements are made in a region of interest (ROI) in theinterventricular septum (IS) to avoid T2*-lowering sus-ceptibility effects from lung, liver, and epicardial fat.T2* measurements in other regions of the heart aremore variable, and thereby less reliable, because ofthese susceptibility effects (11–14). This limits theareas within which T2* values can be accuratelymeasured, since T2* values in high-susceptibilityareas have cumulative effects of both susceptibilityand iron deposition. Susceptibility effects from vari-ous regions in and around the heart can project to theIS, further causing increased variation in T2* meas-urements (15). In addition, intra- and interobservervariability in the ROI selection can affect the reprodu-cibility of T2* measurements (16).

In this study we implemented and evaluated an auto-mated method that incorporates an autoregressive mov-ing average (ARMA) model of the complex signal from amultigradient echo (mGRE) acquisition (17) to map thefield and T2* of the whole left ventricle. Previous workdemonstrated that this method could be used to quan-tify susceptibility due to iron in the liver (18). In thiswork, by using the field map areas of high susceptibilitycaused by factors such as air–tissue interfaces, deoxy-genated blood in the cardiac veins, and epicardial fatcan be automatically identified. Only areas of the LV

1Department of Radiological Sciences, St. Jude Children’s ResearchHospital, Memphis, Tennessee, USA.2Department of Hematology, St. Jude Children’s Research Hospital,Memphis, Tennessee, USA.

Contract grant sponsor: National Institutes of Health (NIH); Contractgrant number: 5RO1DK088988-02; Contract grant sponsor:American Lebanese Syrian Associated Charities (ALSAC).

*Address reprint requests to: C.M.H., Department of Radiological Sci-ences, St. Jude Children’s Research Hospital, 262 Danny ThomasBlvd. MS 220, Memphis, TN 38105. E-mail: claudia.hillenbrand@stjude.org

Received June 27, 2012; Accepted November 14, 2012.

DOI 10.1002/jmri.23990View this article online at wileyonlinelibrary.com.

JOURNAL OF MAGNETIC RESONANCE IMAGING 38:441–447 (2013)

CME

VC 2013 Wiley Periodicals, Inc. 441

minimally affected by anatomy-related susceptibilityeffects were used to reduce the variability in T2* meas-urements for cardiac iron assessment. Susceptibilityeffects were also measured at different regions of theheart to directly identify areas of high susceptibility thatcan affect cardiac T2* measurements.

MATERIALS AND METHODS

Patient Demographics and Magnetic ResonanceImaging (MRI)

This retrospective study was approved by the localInstitutional Review Board. MR exams from individualswith suspected transfusional iron overload (10 male/14 female, 18.0 6 11.4 years (range: 3–45 years)) wereretrieved from the institution’s diagnostic imagingPACS system and evaluated in MatLab (MathWorks,Natick, MA). Patients underwent a diagnostic cardiacmGRE scan to monitor for possible iron loading in theheart due to their transfusion history and/or increas-ing serum ferritin levels. Diagnoses for these patientsincluded sickle cell disease (n ¼ 10), b-thalassemiamajor (n ¼ 7), sideroblastic anemia (n ¼ 1), and con-genital dyserythropoietic anemia (n ¼ 1). Five patientsreceived at least one bone marrow transplant for thefollowing conditions: acute leukemia (n ¼ 2), Hodgkin’slymphoma (n ¼ 1), aplastic anemia (n ¼ 1), and redcell aplasia (n ¼ 1). After obtaining informed consentfrom patients, MRI scans were conducted on 1.5Twhole-body scanners (Avanto and Symphony, Sie-mens, Malvern, PA) with a phased-array body coil. Anelectrocardiogram-gated, single breath-hold techniquewas used to obtain mid-papillary short-axis mGREimages at the end of the diastole. Echo times rangedfrom 1.5–21.3 msec, and were used in increments of1.8 msec (echo train length ¼ 12). Other imaging pa-rameters were as follows: flip angle 35�, slice thickness8 mm, matrix size 135 � 128, and variable field ofview (300–400 mm)2, depending on patient size. Theacquisition was divided into 15 heartbeats with 9 seg-ments in each heartbeat with a variable TR, between600 and 1200 msec, depending on the heart rate.Total acquisition time ranged from 18–21 seconds.

Automated Identification of High-SusceptibilityRegions in the Heart

The proton resonant frequency (PRF), T2* value, andamplitude of multiple peaks (ie, water and bulk meth-ylene in epicardial fat) were calculated using anARMA model on the mGRE acquisition as described inprevious work (17,18). With this algorithm, the mGREsignal in each voxel is expressed as a rational polyno-mial after utilizing a z-transform. The algorithm theniteratively approximates the coefficients of the polyno-mial where the poles correspond to the PRF and T2* ofeach peak, thereby providing separate values forwater and fat (ie, epicardial fat). The amplitude ofeach peak was calculated using Cauchy’s residue the-orem and the water PRF was used for the field map.

To identify an appropriate threshold for the fieldmap gradient, simulations using identical MR acquisi-

tion parameters were used with T2* values rangingfrom 1–50 msec. For the simulation, effects of fieldgradient in the z-direction was simulated to determineits effect on T2* values, since this typically gives thegreatest effects on T2*. This, in turn, will give a worst-case scenario on field inhomogeneity effects on T2*.Given the water amplitude, r, the effect of the signal,s(t), due to a PRF gradient, G, can be described as:

sðtÞ ¼ rei2pf� 1

T2�

� �tDz sincðgGDztÞ ½1�

where f is the PRF, Dz is the length of which the gradi-ent passes, and g is the gyromagnetic ratio (19,20). Athreshold value was chosen based on these simula-tions which would exclude voxels due to susceptibilityeffects that can affect T2* measurements.

By using the magnitude image at the first TE, anROI was selected that covered the entire LV. This wasthe only user interaction needed for the T2* calcula-tion. The gradient of the field map was generated bymeasuring changes in the PRF as the root of the sumof squares of the field changes in the image’s x and ycoordinates. Based on the results from the simula-tions, voxels with gradient values above 3.0 Hz/mmwere excluded from the T2* measurement. Next, thealgorithm identified extraneous voxels that are notconnected to other voxels (<4 voxels connected to-gether) and omitted them for the T2* calculation. Also,voxels with T2* values greater than 70 msec (signify-ing values that are higher than normal myocardial tis-sue (ie, blood) (21)) were excluded from the measure-ment. The remaining area was used for ARMA-basedT2* measurements. In this ROI, the T2* values can becalculated voxel-by-voxel throughout the LV (Fig. 1).

Coefficient of Variation (CoV) andRegional Analysis

The mean and standard deviation (SD) of T2* valuesin the whole LV, IS, and ARMA-defined ROIs were cal-culated for each patient. Mean values were used sincethe skewness and kurtosis of the T2* measurementswere low (< �0.6), thereby supporting the use of para-metric statistical methods (22). For each of the threeROIs (LV, IS, and ARMA), the CoV was calculated andcompared individually by a paired Student’s t-test (a¼ 0.05). The total area of the LV, IS, and ARMA-defined region was also recorded.

To investigate susceptibility effects in distinct areasof the LV, the LV was divided into four 90� quadrants:the IS, anterior wall (AW), lateral free wall (LFW), andposterior/inferior wall (PIW) (Fig. 2), as done in thestudy by Yamamura et al (8). The mean, SD, and CoVof T2* values were recorded for each region, in addi-tion to the T2* calculated by the ARMA model for eachregion (whole region vs. low-susceptibility areas).Each area excluded from T2* measurement due tofield gradients above the threshold was also recorded.

RESULTS

A field gradient of 3 Hz/mm was chosen for thethreshold to remove voxels that may be decreased due

442 Taylor et al.

to susceptibility effects. As shown in Fig. 3, voxelswith gradients to the right of the white dashed linewere thresholded out. It can be noted on the surfaceplot that susceptibility affects longer T2* values morestrongly in comparison to short T2* tissues, which aregenerally seen in iron overload.

Table 1 gives the mean T2* measurements of the 24patients in the entire LV, IS, and ARMA-definedregions. There was no statistically significant differ-ence in the mean T2* values between the IS andARMA regions (P ¼ 0.32). To visually demonstratethis, a Bland–Altman plot of the IS and ARMA meanT2* values is shown in Fig. 4. The population meanT2* of the entire LV was lower than that of the IS andARMA (P < 0.01). In all cases, the mean ARMA T2*measurement was higher than the LV T2* measure-ment (P ¼ 0.03). The T2* values calculated by theARMA model ranged from 15.8–41.2 msec (mean,32.6 msec; SD, 6.6 msec).

The mean IS ROI area was 21.1 6 3.4% of the totalLV area. Compared with the IS area, the mean areafor ARMA-based T2* measurements was 51.9 6 13.7%(P < 0.0001) of the LV area. Although on average thearea for the ARMA-defined region was significantlyhigher than that for the IS, the CoV of T2* measure-ments between the IS and ARMA did not significantlydiffer from that of the IS. The CoV of T2* measure-ments by ARMA was 19% lower than the CoV of T2*measurements in the entire LV (P < 0.0001).

In evaluating the four regions of the LV, there wereareas where susceptibility was consistently high inour patient cohort regardless of iron-overload status.Table 2 displays which areas were used for ARMA-defined T2* measurements. The IS contained the leastvoxels with gradients above the threshold signifyingthat it had the least susceptibility. The LFW had the

Figure 1. Schematic diagram for automated cardiac T2* measurements. The magnitude and phase images from the mGREacquisition are used to generate a field map. The gradient of the field map is calculated to identify areas of susceptibility. Agradient of 3 Hz/mm is used as a threshold for T2* calculations. Any voxel above the threshold in the LV is excluded fromthe T2* calculation. As shown in the figure on the far right, the algorithm can highlight areas of low susceptibility in the LV(highlighted in red).

Figure 2. Division of the myocardium of the LV into theinterventricular septum (IS), anterior wall (AW), lateral freewall (LFW), and posterior/inferior wall (PIW) in the mid-pap-illary short axis.

Figure 3. Surface plot of the effects of field gradients, par-ticularly in the z-direction, on T2* values. Due to increasedsusceptibility effects at higher TE values, the gradients havea larger effect at higher T2* values. A threshold of 3 Hz/mm(dashed line) was used to negate field gradient effects over alarge range of T2* values.

Automated T2* for Cardiac Iron 443

greatest area of susceptibility with 73.1 6 24.8% ofthe voxels excluded for T2* measurements. Of all theaccepted voxels (<3 Hz/mm gradient), 46.6% of voxelscame from the IS, 38.1% came from the anterior wall,15.3% came from the posterior/inferior wall, and18.1% came from the LFW. Figure 5 shows an exam-ple where the ARMA model identified areas of low sus-ceptibility, which was mostly in the IS. In each of thefour regions the ARMA model decreased the CoV (P <0.01), demonstrating more precise measurements inthe ROI using ARMA compared to ROIs of the entireregion.

Except in one patient, the implementation of theARMA model did not change the indication of low riskof complications (>20 msec) to high risk of complica-tions (<20 msec) from iron overload or vice versa. Thepatient that was an exception had a subcutaneousport in the left chest wall, which led to increased sus-ceptibility in the IS (Fig. 6). The LV for the patient was16.3 6 11.1 msec and the IS T2* was 14.7 6 10.7msec. The ARMA model was used to identify the areaof high susceptibility and exclude it from the T2* mea-surement. By using the threshold, a T2* of 23.5 6 6.7msec was calculated by the ARMA model, and theuncertainty of the measurement placed the 95% confi-dence interval at the level where the patient would bedetermined to be at higher than normal risk of car-diac complications. In the Bland–Altman plot in Fig. 4this patient is marked by an arrow, which demon-strates the wide variation between the T2* measure-ments in this patient.

DISCUSSION

We used the ARMA model and magnitude/phaseinformation from a short-axis mGRE acquisition togenerate field maps and T2* maps without addingimaging time, since the field map was derived and cal-culated directly from the mGRE acquisition. By usingthe field map data, areas of high susceptibility wereautomatically identified and excluded from the analy-sis in an effect to deliver a more precise estimate ofT2* in the myocardium. The procedure needed mini-mal user interaction: the user only outlines the LV,and the T2* is automatically calculated in areas wheresusceptibility from various sources is relatively mini-mal. In addition, the user could further define a more

restrictive ROI (ie, lower threshold) based on theregion preselected by the algorithm as an area of lowsusceptibility.

Iron itself induces a susceptibility effect that isreflected by a reduction in T2* values and a possibleincrease in the field gradient. However, it was foundin this study that the correlation between the medianfield gradient across the heart and the T2* of thetissue was very low (R2 ¼ 0.069). Certain regions ofthe LV showed the same susceptibility effectsindependent of the LV or IS T2*, supporting that thesusceptibility effects measured are from the geometryand/or anatomy of the heart. Therefore, in ouropinion, the majority of voxels excluded for highsusceptibility are due to the cardiac geometry and/oranatomy and not excessive iron in different regions ofthe heart.

It is also important to note that susceptibility is anadded effect. Therefore, measuring the T2* in thesehigh-susceptibility areas may lead to overestimationof the amount of iron present in the myocardium.Meloni et al (14) suggested that this may be negligi-ble in the case of patients with severe iron overload.In severe cardiac iron overload, there can be a

Table 1

Mean T2* Measurements of the 24 Patients in the Entire LV, IS,

and ARMA-Defined Regions

T2* (msec) CoV % of LV

LV 28.6 6 6.0 0.49þ 6 0.08 —

IS 35.1 6 10.0* 0.33 6 0.13** 21.1 6 3.4

ARMA 32.6 6 6.6* 0.31 6 0.07** 51.9 6 13.7***

LV: left ventricle;

IS: interventricular septum;

ARMA: autoregressive moving average model calculation.

*Statistically different from LV T2* (P < 0.05).

**Statistically different from LV CoV (P < 0.001).

***Statistically different from IS % Vol (P < 0.0001).

Figure 4. Bland–Altman plot of the IS and ARMA mean T2*values. The mean deviation (solid line) between the twomeasurements was 0.2 msec with a 95% confidence interval(dashed lines) of �3.2 to 3.6 msec. The point with the arrowcorresponds to a patient with a subcutaneous chest port (seeFig. 6), which lowered the T2* in the IS.

Table 2

ARMA-Defined T2* Measurements in the Four Regions of the Left

Ventricle After Susceptibility Correction

Region

Percent of voxels CoV before CoV after

excluded for

susceptibility correction correction

IS 27.7 6 21.0 0.44 6 0.13 0.25 6 0.08**

AW 40.2 6 27.7 0.42 6 0.20 0.26 6 0.08*

LFW 73.1 6 24.8 0.65 6 0.31 0.26 6 0.12**

PIW 56.6 6 31.2 0.47 6 0.18 0.25 6 0.11*

IS, interventricular septum; AW, anterior wall; LFW, lateral free

wall; and PIW, posterior/inferior wall.

*P < 0.01 and **P < 0.001 when compared before correction.

444 Taylor et al.

gradient of iron concentration along the transmurallayers of the myocardium (5,23). This could cause anincreased susceptibility effect across the myocardialwall. Given that none of our patients had severe ironoverload (T2* <10 msec), we could not assess thealgorithm under these conditions. As is done withsuperparamagnetic iron oxide (SPIO)-labeled cells(24) or in the liver (18), it may be possible in thesecases to measure the susceptibility across the sep-tum using the ARMA-generated field map as an addi-tional measurement to the T2* measurement for ironassessment (6).

In this study a conservative 3 Hz/mm thresholdwas used to remove areas of high susceptibility whilemaintaining a large area to make T2* measurements.While the gradient effects lower T2* tissues less, thisthreshold was chosen to assure that higher T2* values(>20 msec) will not be adversely affected. We foundthat the variation in T2* measurements was signifi-cantly lower when a 3 Hz/mm threshold was usedthan when measuring the T2* of the entire LV. Whilethis simulation used the prescribed acquisition fromthis study, it is important to note that decreased spa-tial resolution and increased slice thickness canincrease the field gradients’ effect on T2* measure-ments. It is typically assumed that the greatest effecton T2* is from the through-plane field gradient(19,20). Since the PRF measurement is an averageover the entire voxel and the greatest dimension wasthrough-plane, this simulation is a reasonable estima-tion to determine the threshold.

Figure 5. Automated ROI selection using combined T2* and susceptibility information. a: A T2* map of the left ventricularshort axis of a patient with sickle cell disease. In the regular workflow, a relatively thin ROI would be drawn in the intraven-tricular septum, thereby avoiding obvious voxels with signal from blood (high T2*) and areas of high susceptibility (ie, AW andPIW, low T2*). b: The gradient of the corresponding field map generated by the ARMA algorithm shows high susceptibility inportions of the AW, LFW, and the PIW (red circles). c: Given the information in (b), a final ROI outlined in red was automati-cally identified by the algorithm circumscribing a large volume in the IS with low susceptibility as a reliable location for pre-cise T2* measurements. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Figure 6. Cardiac iron concentration assessment in a patientwith a subcutaneous port in the left chest wall. a: Circle high-lights the susceptibility artifact on the short axis scout image.b: The proton resonant frequency ranges from 1 to 4 ppm inthe anterior and septal regions of the LV, demonstrating highsusceptibility presumably from the port. c: The areas in redare regions of the LV having a field gradient that is below the3 Hz/mm value, demonstrating the lowest areas of susceptibil-ity. d: The increased susceptibility detected by the algorithmdecreases the T2* in the same area. Measuring the T2* in thisregion may result in overestimation of the amount of iron pres-ent, since other sections of the myocardium have T2* valuesthat reflect normal iron loading. [Color figure can be viewed inthe online issue, which is available at wileyonlinelibrary.com.]

Automated T2* for Cardiac Iron 445

In this study the LFW had the most voxels excludedfrom the T2* evaluation. Yamamura et al (13) reportedthe lowest T2* values in the posterior/inferior and an-terior walls of the heart, which in our study hadslightly fewer areas of high susceptibility on averagethan the LFW did. While the mean values show thatthe LFW had the highest area of excluded voxels, thiswas not the case in every patient, as seen in the largeSDs in Table 2. In eight cases, the AW or PIW had themost voxels excluded due to susceptibility. In addi-tion, in published reports (13,14) the variations in T2*values are used as a marker for susceptibility. Thefact that we are directly measuring the field and notT2* variations may indicate why there are some differ-ences. It is important to note that all these studies,including this study, agree that the IS exhibits theleast susceptibility.

This study shows that there are several sources ofsusceptibility in and around the heart that do notcome from iron deposition. The posterior and middlecardiac veins carry deoxygenated blood from the myo-cardium in areas near the PIW and LFW. The deoxy-genated hemoglobin in the blood has a well-under-stood susceptibility effect that can affect T2*measurements (25,26). Another major source of sus-ceptibility is the air–tissue interface at the lungs,which is mostly prevalent at the LFW adjacent to theleft lung. Other susceptibility sources are epicardialfat (more prominent at the anterior wall along withthe great cardiac vein) and foreign bodies, as seen inFig. 3. Again, these areas were automatically omittedfrom the T2* calculation, which contributed to overallmore precise T2* measurements using the ARMAmodel.

In addition to identifying the areas with the leastsusceptibility, the ARMA technique can be used as anautomated warning of high-susceptibility areas inROIs. For instance, an ROI can be drawn in the IS. Byusing the gradient maps generated by ARMA, the areaof high susceptibility within the ROI can be detectedand identified, which could be particularly useful inpatients with susceptibility artifacts arising from thechest wall. Also since multiple chemical shifts can becalculated, epicardial fat can be detected and auto-matically excluded from the T2* calculation.

As mentioned above, one limitation of this study isthat there were only two patients with T2* values lessthan 20 msec to demonstrate an increased risk of car-diac complications. No patient had T2* values lessthan 10 msec. Although it is encouraging that the ma-jority of our patients did not have heavy iron loadingin the heart, this meant that we were not able to testthe algorithm in myocardia with high iron loads. It isinteresting to note that the median gradients in thetwo iron-overloaded patients were not statistically dif-ferent from those of the other patients. In fact, thehighest median gradient was seen in the patient whohad the subcutaneous port in the left chest wall.Twenty-one of these 24 patients had iron overload inthe liver, which were determined by T2* values cali-brated to liver iron content (27). In this study, liverR2* values ranged from 87–595 Hz in addition to twopatients with R2* values that could not be precisely

determined due to severe iron overload (R2* >1000Hz). Excluding these two cases, the mean liver R2*was 334 Hz with an SD of 161 Hz. Similar to observa-tions in previous reports (28,29), the two patientswith very high liver iron content (LIC) had a cardiacT2* that was normal using both the IS and ARMA T2*measurements (range: 25.9–33.1 msec). In terms ofabdominal imaging such as for the liver and pancreas,this technique can possibly be used to identify areasof high susceptibility due to air/tissue interfaces (ie,from gas in bowel) and omit those voxels from the T2*calculation. It could particularly be helpful when fatis present in the liver and/or pancreas since multiplechemical shifts (ie, water and bulk methylene) can becalculated with the ARMA technique (17,18).

Typically, only magnitude data are used for MRImeasurements. It is important to note that both mag-nitude and phase data are needed to make the fieldmeasurements using ARMA. This can be done onmost MR scanners by using options to output theimages either in magnitude/phase or real/imaginaryform.

Our future studies will focus on making thisapproach a fully automated diagnostic reporting toolto identify patients at risk of developing cardiac com-plications due to iron accumulation. A large studyhas been conducted to develop fully automatedmethods to segment the LV for analysis (30). Thesemethods could be incorporated into the ARMA methodpresented to make the processing fully automated toaid in the standardization of T2* measurements in theheart.

In conclusion, an automated method was evaluatedfor measuring T2* relaxation in the heart, in whichsusceptibility effects are minimized. By using thismethod, the variation of T2* values was found to becomparable with variations in the IS, where suscepti-bility is the lowest. At the same time, the method pro-vided, on average, a greater area to measure T2* thanthat using IS alone. Areas in which low susceptibilitywas directly measured corroborated with areasreported in previous studies that investigated T2* var-iations throughout the LV (8,14). This method couldaid the diagnosis of iron overload in the heart whilereducing interobserver and intraobserver variability,since the only user input needed is a rough outline ofthe entire LV as a starting point for the automatedregion selection algorithm.

ACKNOWLEDGMENT

The authors thank Vani Shanker, PhD, for scientificediting of the article.

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