FULL PAPER

Metabolic MR Imaging of Regional Triglycerideand Creatine Content in the Human Heart

Kilian Weiss,1 Nicola Martini,2 Peter Boesiger,1 and Sebastian Kozerke1*

An optimized echo-planar spectroscopic imaging sequence isproposed to facilitate spatial mapping of triglyceride and totalcreatine content in the human heart. The sequence integrateslocal-look field of view reduction, cardiac and respiratorygating, and dedicated reconstruction steps to account forgradient channel delays, field inhomogeneity, and phase inco-herence due to residual motion. The technique is demonstratedin 12 volunteers in comparison to single voxel point-resolvedspectroscopy in the septal wall at 1.5 T. Triglyceride-to-waterand total creatine-to-water ratios derived from echo-planarspectroscopic imaging (0.48 6 0.18% and 0.06 6 0.03%) andpoint-resolved spectroscopy (0.52 6 0.17% and 0.07 6 0.02%)were found to agree well. In the septal region, intraclass corre-lation coefficients ranging from 0.67 to 0.72 were estimated. Arelatively weak agreement (intraclass correlation coefficients:0.34 and 0.52) was found for sectors in the lateral wall due tofield gradients induced by the posterior vein and limited sensi-tivity of the receive coil array in this area. On the basis of thefindings, it is concluded that fast spectroscopic imaging ofboth cardiac triglyceride and total creatine content is feasible.Shimming and sensitivity challenges in the lateral regionremain, however, to be addressed. Magn Reson Med 000:000–000, 2012.VC 2012 Wiley Periodicals, Inc.

Key words: cardiac spectroscopy; echo-planar spectroscopicimaging; triglyceride; creatine; motion compensation; local-look excitation

INTRODUCTION

Single voxel proton magnetic resonance has been shownto be a promising tool for assessing total creatine (CR)and triglyceride (TG) content in the myocardial musclein humans (1–3). The specificity of in vivo proton mag-netic resonance spectroscopy to probe myocardial TGs inhumans has recently been validated (4). Myocardial TGs,a cellular storage form of fatty acids, are indirectly con-nected to myocardial energy metabolism (5). Therefore,one focus of interest is the correlation between myocar-dial TG content and cardiac dysfunction (6). CR, whichreflects the sum of creatine (Cr) and its phosphorylatedform phosphocreatine, gives insight into the myocardialCr kinase reaction (2). Being the primary energy reserve

in myocardial tissues during periods of ischemia,hypoxia, and stress (7,8), the Cr kinase reaction reversiblytransfers high-energy phosphate between phosphocreatineand adenosine triphosphate. It has been found that CRcontent is depleted in the failing heart (2,9).

Although spectral information from a single volume issufficient when alterations with global effects on theheart are studied, a demand for higher and flexiblespatial resolution exists when probing local changes, likein ischemic heart disease (8,10). Spectroscopic imaginghas been used previously for studying high-energyphosphates using 31P spectroscopy in humans in vivo(11–13). Because of the low sensitivity of this nucleus,spatial resolution is very limited and methods utilizingprotons as a signal source are preferred. To this end,implementation of 1H spectroscopic imaging of the heartcan give insight into regional differences of CR and TGcontent and hence potentially allows for detection of het-erogeneous myocardial pathologies.

Technically, 1H spectroscopic imaging of the heart ischallenging. Results of earlier attempts of spectroscopicimaging of myocardial TG content were found to bedominated by epicardial lipids (1). Parts of the problemhave been associated with motion sensitivity and thelong scan times. To compensate for cardiac and respira-tory motion, navigator-based dual triggering has beenproposed (14,15), which has been found to be a prerequi-site for reproducible proton spectroscopy of the heart(3,16). However, long scan times of conventional phaseencoded chemical shift imaging techniques make cardiacspectroscopic imaging with sufficient resolution and sizeof the field of view not feasible. Therefore, fast spectro-scopic imaging techniques trading signal-to-noise ratioper unit time and effective scan time are needed (17).

The objective of this work was to implement andoptimize an echo-planar spectroscopic imaging (EPSI)technique (18,19), which permits mapping of spatial dis-tribution of TG and CR content of the in vivo heart dur-ing free breathing acquisitions. Cardiac triggering and re-spiratory navigator gating were incorporated for motioncompensation. A spin-echo-based local-look field of exci-tation (FOX) reduction and appropriate reconstructionwere incorporated. The sequence was tested on a seriesof volunteers and the results were compared with datafrom single voxel spectroscopy.

MATERIALS AND METHODS

A local-look navigator gated spin-echo EPSI (Fig. 1a,b)sequence was implemented on a 1.5 T Philips Achievasystem (Philips Healthcare, Best, The Netherlands). For

1Institute for Biomedical Engineering, University and ETH Zurich, Zurich,Switzerland.2Fondazione G. Monasterio CNR-Regione Toscana, Massa, Tuscany, Italy.

Grant sponsor: Swiss National Science Foundation; Grant number:#CR3213_132671/1.

*Correspondence to: Sebastian Kozerke, PhD, Institute for BiomedicalEngineering, University and ETH Zurich, Gloriastrasse 35, 8092 Zurich,Switzerland. E-mail: kozerke@biomed.ee.ethz.ch

Received 15 September 2011; revised 19 December 2011; accepted 22December 2011.

DOI 10.1002/mrm.24178Published online in Wiley Online Library (wileyonlinelibrary.com).

Magnetic Resonance in Medicine 000:000–000 (2012)

VC 2012 Wiley Periodicals, Inc. 1

all experiments, an equatorial slice in short axis viewwas acquired (Fig. 2a,b). To avoid signal contaminationfrom tissue outside the region of interest, FOX reductionbased on an optimized selective excitation pulse inphase encoding direction and a slice selective refocusingpulse was implemented (Figs. 1b and 2c,d). Pencil-beamnavigator echoes were integrated for respiratory gatingpurposes. To minimize both scan time and residualrespiratory motion, weighted gating was incorporatedwith a gating window of 4 and 3 mm for 70% of theouter k-space and 30% of the inner k-space, respectively.In every measurement, water-suppressed and -unsup-pressed reference scans were acquired. Water suppres-sion was implemented using two frequency selectiveexcitation pulses each followed by a gradient spoiler justbefore signal excitation. During preparation, iterativelocalized linear shimming was performed using a breathhold scan to avoid respiratory motion artifacts. All scansand preparations were acquired using cardiac triggeringduring an end-systolic phase to have maximum thicken-ing of the cardiac muscle, as can be seen in Fig. 2a,b.

The parameters of the EPSI sequence were as follows:field of view 300 � 150 mm2, FOX 65–85 mm, nominalresolution 3 � 3 mm2, slice thickness 15 mm, spectralband width 1064 Hz, spectral resolution 4.2 Hz, echotime (TE) 12 ms, pulse repetition time (TR) 750–1250 msdepending on heart rate, eight signal averages for water-suppressed scans, and nominal acquisition time forwater-suppressed/-unsuppressed scans: 6:40/0:50 minresulting in a total acquisition time of about 18:45 minwith a navigator efficiency of 40%. The cardiac triggerdelay to peak systole was estimated using cine scans atapproximately 320 ms after the R-wave. To optimize sig-nal-to-noise ratio of the CR resonance at 3.01 ppm, Ernstangle excitation for the water-suppressed scans was usedleading to an excitation angle of 115–125� combined withthe 180� refocusing pulse, depending on heart rate.

For comparison, a navigator gated and cardiac trig-gered point-resolved spectroscopy (PRESS) sequence was

implemented and applied in the same session (16). Bothwater and water-suppressed spectra were acquired.Before data acquisition, iterative linear shimming of thesingle voxel using breath hold and water suppressionoptimization using navigator triggering for respiratorymotion compensation were performed. To avoid contam-ination from epicardial fat, the single voxel was placedin the septum (Fig. 2a,b). For PRESS, only data from thissingle position were acquired. The parameters of thePRESS sequence were as follows: voxel size 10 � 20 �40 mm3, TE/TR 33/2000 ms, 128 signal averages forwater suppressed and eight signal averages for the water-unsuppressed scans. Nominal acquisition time for water-suppressed/-unsuppressed scans: 4:16/0:16 min, result-ing in a total acquisition time of 11:20 min with a gatingefficiency of 40%.

For all experiments, the body coil was used for signalexcitation and a five-channel cardiac array was used forsignal reception. A total of 12 healthy volunteers (meanage: 29 years; range 23–46 years) were measured afterinformed consent was obtained according to institutionalguidelines.

RECONSTRUCTION—EPSI

A flow chart of the EPSI reconstruction steps with illus-trations of their effect on water-unsuppressed data areshown in Fig. 3.

Coil Combination

Coil sensitivity maps were calculated using the water-unsuppressed data. Taking into account the noise varian-ces ci of coil i, the sum-of-squares SoSð~xÞ, and thephase-corrected signal maps Fið~xÞ at spatial positions ~xare given by:

FIG. 1. a: Schematic representation of the local-look navigator

gated EPSI sequence. The ECG trigger is followed by the acquisi-tion of the pencil beam navigator for respiratory motion compen-sation and the water-suppression pulses. The signal is acquired

using an echo planar readout train. b: Schematic drawing of thespin echo-based orthogonal excitation using a 90� and a 180�

pulse. The 90� excitation pulse is selective in phase encodingdirection. Slice selection is achieved by the selective 180�

refocusing pulse. The echo maximum is centered on the first

readout of the echo planar readout train. The signal is sampledduring gradient plateaus only.

FIG. 2. Position of the PRESS voxel (solid line) and the FOX of

the EPSI acquisitions (dashed line). a: Short axis view with thelimited FOX in phase encoding direction of the EPSI acquisitions.

b: Four-chamber view with the EPSI slice prescribed. c: Excitationprofile of the FOX in phase encoding direction. d: Refocusingprofile in slice direction.

2 Weiss et al.

SoSð~xÞ ¼Xi

r0ið~xÞ2

Fið~xÞ ¼ r0ið~xÞQ�ð~xÞ with Qð~xÞ ¼Xi

r0ið~xÞ

where r0i ¼ c�1i ri refers to the noise variance weighted

maximum signal in each coil’s free induction decay(FID) and * denotes complex conjugate. Coil sensitivitymaps Sið~xÞ can then be computed according to:

Sið~xÞ ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

r0ið~xÞr0�i ð~xÞFið~xÞF�

i ð~xÞSoSð~xÞ

sFið~xÞ

Using the coil sensitivity maps Sið~xÞ, the actual time-domain signals rið~x; tÞ of the water-suppressed and -unsuppressed EPSI data were combined using (20):

1ð~x; tÞ ¼Xi

rið~x; tÞS�i ð~xÞ

Ghost Correction

Spectral N/2 ghosts resulting from delays between evenand odd readout gradients were corrected for by maximiz-ing the water and fat signals in the water-unsuppressedscans (21). The delays of the gradients cause a linear phaseshift along the readout direction in image domain afterspatial Fourier transformation according to the Fouriershift theorem. To estimate this phase shift, a trial set ofphase shifts between 0 and 2p were applied to every sec-ond point of the FIDs to every pixel of the spectroscopicimages, and the shift with the lowest N/2 ghost wasdetected. The estimated optimal phase shifts were then fit-ted with a linear function along the readout direction.Finally, the linear phase shifts were applied to every sec-ond readout of the FIDs tominimize the spectralN/2 ghostsin both the water-suppressed and -unsuppressed scans.

Spatial Filtering

To reduce effects of the point-spread function side lobes,k-space data were filtered using a Hamming function in

FIG. 3. a: Flow chart of the EPSI reconstruction. After preprocessing of the data, complex coil maps are calculated from the water-

unsuppressed reference scans and coils are combined. Spectral N/2 ghost artifacts are corrected based on parameters estimated fromthe water scans. After spatial Hamming k-space filtering, the data are corrected for B0 inhomogeneities. Finally, spectra in the individualsegments are phase corrected and subsequently averaged. Correction results without the reconstruction steps marked by * and ** are

shown in Fig. 5a,b, respectively. Correction steps are illustrated for water-unsuppressed data in (b–l); (b) data before and (c) after coilcombination, (d) spectrum before and (e) after spectral N/2 ghost correction, (f) spatial point-spread function (PSF) before and (g) after

Hamming filtering, (h) spectrum before and (i) after B0 correction, (j) segmentation of the myocardium, and (k) spectrum before and(l) after phase correction. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

MRI of TG and CR Content in the Human Heart 3

the spatial dimensions resulting in an effective spatialresolution of 4.4 � 4.4 mm2 (22).

B0 Correction

For B0 correction, the position of the water and fat peakswas detected using a model spectrum for every pixel inthe spectroscopic images of the water-unsuppressedscans. From the position of the water peak, B0 mapswere estimated. Using the B0 maps, corrections wereperformed on a pixel-by-pixel basis using linear phaseshifts applied to the time-domain signals of the water-suppressed and -unsuppressed signals.

Cardiac Segmentation

For analysis, the myocardial muscle was divided into sixsegments (Fig. 4a,b). As spatial reference, the waterimage of the water-unsuppressed scan was used. A fatimage from the water-suppressed scan was utilized as asecond spatial reference (Fig. 4b) to accurately draw theepicardial contour, hence avoiding the contaminationfrom epicardial fat in the segments.

Constructive Averaging

To ensure phase coherent averaging, all spectra withineach of the six regions of interest and all averages ofthe water-suppressed scans were phased using the fatresonance at 1.3 ppm (23). The water-unsuppressedscans were phased using the first points of the FIDs.

All spectra from the selected regions were subsequentlyaveraged.

RECONSTRUCTION—PRESS

Coil phases were automatically estimated using the waterpeak in the water-unsuppressed scans (23) and used forcoil combination for the water-unsuppressed and thewater-suppressed data. To remove motion-related phasedifferences and to ensure constructive averaging, all scanswere phased before averaging in a manner identical to theone used for EPSI reconstructions.

QUANTIFICATION AND STATISTICAL ANALYSIS

For quantification of both the EPSI and the PRESS data,the resonance of trimethyl ammonium (TMA) compoundat 3.2 ppm, the resonance of CR at 3.01 ppm, and the fatresonances at 2.1, 1.3, and 0.9 ppm in the water-suppressed spectra of the six defined segments were fit-ted using the AMARES function of the jMRUI softwarepackage (24,25). Before fitting of the water-suppressedspectra, the residual water peak was filtered using aHankel-Lanczos singular value decomposition method(26). In addition, the water peak was fitted usingAMARES in the same segments of the water-unsup-pressed reference scans. All estimated signal amplitudeswere corrected for longitudinal and transversal relaxa-tion effects and the Ernst angle excitation used for thewater-suppressed EPSI scans. Relaxation values weretaken from literature as follows: T1 ¼ 1100 ms and T2 ¼

FIG. 4. a: Six segments for the midcavity region used for data analysis. b: Segments were chosen on basis of a water image from the

non-water suppressed reference scan (gray) and a fat image from the water-suppressed scan (green overlay) to avoid partial volumeeffects. c: B0 map as estimated from the position of the water resonance in the water-unsuppressed scans. The position of the posteriorvein of the left ventricle where strong B0 inhomogeneities are visible is indicated. d: Linewidth map of the water resonance in the water-

unsuppressed scan on a voxel-by-voxel basis.

FIG. 5. Water-unsuppressed spectra of one segment in the lateral wall of the EPSI scans showing different reconstruction steps of theEPSI data. a: Spectrum without the B0 correction step, (b) without spectral N/2 ghost correction, (c) with all correction steps.

4 Weiss et al.

40 ms for myocardial water (27), T1 ¼ 280 ms and T2 ¼86 ms for TG estimated in skeletal muscle (28–30), andT1 ¼ 1500 ms and T2 ¼ 135 ms for myocardial CR (9,28).The TG signal was estimated as the sum of thefat resonances at 0.9 and 1.3 ppm (16). TG and CR inten-sities were then calculated as a fraction of the unsup-pressed water peak in the same region of interest.Moreover, the water peak was fitted on a voxel-by-voxelbasis to assess the linewidth distribution of the waterlineover the myocardial muscle.

For comparison of the quantification results of TGcontent with EPSI and PRESS, intraclass correlationcoefficients (ICCs) were calculated using a mixed effectanalysis of variance. To test differences between meanvalues of linewidths and concentrations of the EPSI andPRESS measurements, a two-tailed paired t-test wasused. A level of P < 0.05 was considered statistically sig-nificant. The analyses were performed using IBM SPSS(IBM SPSS, version 19; SPSS, Chicago, IL).

RESULTS

Results of the reconstruction steps are shown in Fig. 5.Spectral N/2 ghosts were reduced by 90.9 6 6.1%(Fig. 5b,c) resulting in a remaining ghost signal of 1.54 60.57% of the water-peak height. Line broadening due toB0 inhomogeneity in the regions of interest was reducedfrom 12.3 6 3.8 to 9.7 6 1.8 Hz (Fig. 5a,c). Overall fieldmap values across the myocardium showed variations of29.6 6 7.6 Hz (Fig. 4c). However, the actual linewidthsof the water-unsuppressed resonance in the individual

voxels varied between 5 and 25 Hz (Fig. 4d). Linewidthvariations in the six regions of interest from the EPSIdata and the single voxel of the PRESS scan across all 12subjects are shown in Table 1. The small linewidths andthe small variations in the septal region (segment 2 and3) allowed for detection and a good discrimination of theresonances of TMA at 3.2 ppm and CR at 3.01 ppm.However, the increased linewidths and variations inthe lateral segments 5 and 6 caused a degradation of thespectral quality in these regions. For the PRESS measure-ments, linewidths of the water resonance in the refer-ence scans significantly exceeded those obtained in theseptal region in the EPSI scans (Table 1). Despite thisobservation, no statistical differences were foundbetween linewidths of the EPSI data in the lateral walland the PRESS data in the septal region. For the EPSIscans, the linewidths of the water resonance were signif-icantly higher in the lateral segment 5 compared withevery other segment.

Figure 6 shows spectra from six regions of interestlocated in the midcavity region of the heart and a PRESSspectrum from the septal wall for comparison. Spectrafrom two measurements of a single volunteer are shownfor every segment. Between the two scans, the subjectwas taken out of the scanner and subsequently reposi-tioned. The mean values of all segments for the twomeasurements were 0.42 6 0.06% and 0.41 6 0.08% forTG content and 0.063 6 0.025% and 0.081 6 0.024% forCR content. The spectral quality of the EPSI spectra wasfound to be comparable to the PRESS spectrum in theseptum (Fig. 6).

Table 1Measured Line Width (Hz) of the Water Resonance in Water-Unsuppressed EPSI Reference Scans for the Six Regions of Interest

(Fig. 4a,b) and of the PRESS Measurements (N ¼ 12)

Segment 1 2 3 4 5 6 PRESS

Mean over subjects 9.0 6 1.6 9.1 6 1.5 8.7 6 1.0 9.6 6 1.3 11.6 6 2.3 10.2 6 1.6 11.2 6 1.8

Mean over intrasubject SD 2.70 6 0.91 2.08 6 0.91 1.94 6 0.54 2.11 6 0.69 3.33 6 1.65 2.42 6 0.61 –

Mean values overall subjects and mean values of the SD across voxels of the individual subjects are shown for the EPSI data.

FIG. 6. a: PRESS (SV) and EPSI

regions of interest indicated in theEPSI reference scan. b: Spectra from

the regions of interest indicated in(a). To illustrate the reproducibility ofthe EPSI scans, two spectra from a

single subject are shown for everysegment. In all spectra, the TG reso-nance at 1.3 ppm (TG) and the CR

resonance at 3.01 ppm (CR) can beclearly seen. For comparison, a

PRESS (SV) spectrum is shown.[Color figure can be viewed in theonline issue, which is available at

wileyonlinelibrary.com.]

MRI of TG and CR Content in the Human Heart 5

The quantification results of all 12 volunteers are sum-marized in Tables 2 and 3. The ICC for the TG contentestimated with PRESS and EPSI was found to be 0.72(95% confidence interval: 0.27, 0.91; P < 0.004) for theseptal segment 2 and 0.67 (95% confidence interval:0.12, 0.90; P < 0.001) for the mean overall segments. Allcorrelation values are shown in Table 3. For the EPSIand PRESS measurements, the coefficient of variationwas 24%. Linear regression and Bland-Altman plots forthe segments and the mean overall segments are shownin Fig. 7. Within the subjects, a mean coefficient of varia-tion of 21 6 6% was found for the different segments.

Because of line broadening in the lateral wall and theregion of the posterior vein of the left ventricle (Fig. 4c),spectra from the lateral segments 5 and 6 revealed lowereffective spectral resolution and a lower spectral quality.Moreover, coil sensitivities were lowest in this region(Table 4). As a result, the correlation and significance ofthe correlation relative to the PRESS measurementsfound for segment 5 (ICC 0.32, 95% confidence interval:�0.29, 0.74; P < 0.05) was comparably low (Table 3). Nosignificant differences were found between the septalregion of the EPSI (segments 2 and 3) and the PRESSscans, demonstrating good agreement of the two meas-urements (P ¼ 0.35 for TG, P ¼ 0.40 for CR, Table 2).However, significant differences were detected between

the mean of all segments of the EPSI measurements andthe PRESS measurements in the septal region (P ¼0.021). The lower mean TG content measured with EPSIindicates that the EPSI measurements underestimate theTG content compared with the PRESS measurements.

DISCUSSION

An optimized EPSI sequence has been proposed to maprelative CR and TG content in the heart in a proof-of-principle study including 12 healthy volunteers. EPSIspectra showed significant correlation with single-voxeldata acquired in the septum for all segments. Correlationcoefficients were found to be in accordance to previousvalues obtained with navigator gated single voxel spec-troscopy (16). The values measured for TG with EPSIand PRESS agree with values reported earlier by van derMeer et al. (16). The CR content as measured in thisstudy, however, was found to be lower compared withprevious data from single voxel measurements (2,9).Although T1 and T2 was not measured in the this study,absolute CR concentrations, based on a mean tissuewater content of 76.4% (2), literature T1 and T2 values(9,27–30), and nominal scanner flip angles, are projectedto be about 17.2 6 8.6 mmol/g and 20.0 6 5.7 mmol/gwet weight for EPSI and PRESS, respectively. These

Table 2Quantification Results in Each Volunteer and Mean Values Overall Volunteers for EPSI and PRESS

Volunteers

TG/W (%) CR/W (%)

EPSI mean ofsegments

EPSI septalsegment 2, 3 PRESS

EPSI mean ofsegments

EPSI septalsegment 2, 3 PRESS

1 0.40 6 0.10 0.45 0.47 0.09 6 0.02 0.08 0.062 0.39 6 0.07 0.45 0.59 0.08 6 0.03 0.11 0.09

3 0.32 6 0.05 0.34 0.47 0.06 6 0.02 0.06 0.084 0.71 6 0.09 0.73 0.77 0.09 6 0.05 0.10 0.085 0.36 6 0.08 0.37 0.68 0.06 6 0.03 0.04 –a

6 0.68 6 0.14 0.69 0.59 0.05 6 0.04 0.04 0.067 0.56 6 0.16 0.72 0.75 0.07 6 0.03 0.09 0.10

8 0.25 6 0.07 0.30 0.25 0.05 6 0.02 0.03 0.059 0.16 6 0.05 0.18 0.31 0.02 6 0.01 0.02 0.0910 0.39 6 0.06 0.43 0.39 0.03 6 0.02 0.07 0.05

11 0.39 6 0.06 0.47 0.39 0.04 6 0.02 0.06 0.0612 0.51 6 0.11 0.64 0.53 0.04 6 0.01 0.04 0.06

Mean 0.43 6 0.16 0.48 6 0.18c 0.52 6 0.17c 0.06 6 0.02 0.06 6 0.03d 0.07 6 0.02b,d

For EPSI mean values, overall segments are shown. Values for TG content (TG/W) and CR content (CR/W) are given as percentage ofwater fraction after T1 and T2 correction.aCR was not found in this spectrum.bAverage and SD of 11 volunteers.c,dNo significant differences have been found (P > 0.05).

Table 3

Quantification Results for the Different Segments for EPSI and Single Septal PRESS Voxel

Segment 1 2 3 4 5 6 PRESS

TG/W (%) 0.45 6 0.20 0.52 6 0.21 0.44 6 0.16 0.42 6 0.21 0.37 6 0.14 0.36 6 0.16 0.52 6 0.17

ICCPRESS 0.64 0.72 0.67 0.65 0.34 0.52 –CR/W (%) 0.04 6 0.03 0.07 6 0.03 0.06 6 0.03 0.06 6 0.03 0.07 6 0.05 0.06 6 0.04 0.07 6 0.02Na 10 11 12 9 11 12 11

Values for TG content (TG/W) and CR content (CR/W) are given as percentage of water fraction. ICC to PRESS is given.aNumber of volunteers where CR was successfully fitted using jMRUI.

6 Weiss et al.

values are smaller than previous estimates of 28 6 6mmol/g (2) and 28.9 6 4.4 mmol/g wet weight (9) possiblyreflecting uncertainties in the relaxation corrections, dif-ferences between time and frequency domain spectralanalysis and partial contamination of the CR signal if theTMA resonance at 3.2 ppm is not fitted independently.However, when comparing the data of this work against

biochemical analysis of CR concentrations [17.9 mmol/g(31) and 20.8 6 4.5 mmol/g (32)] very good correspon-dence is noted. Likewise, when comparing the data with31P measurement results with phosphocreatine concentra-tion found at 9 6 1.2 mmol/g wet weight (33) and assum-ing a flux ratio of Cr to phosphocreatine of 0.81, as derivedfrom isolated perfused rat hearts (34), a CR concentrationof 16.3 mmol/g wet weight is found in reasonable agree-ment with the results of this study.

The lateral segment in the region of the posterior veinof the left ventricle was found to be compromised withsignificantly lower correlation when compared with bothEPSI and PRESS data from the septal region. This find-ing is associated with strong B0 inhomogeneities inducedby the vicinity of deoxygenated blood inside the poste-rior vein. Significant stronger line broadening comparedwith all other segments was detected in the related seg-ment 5 (11.6 6 2.3Hz, Table 1) in agreement with previ-ous data by Reeder et al. (35). B0 inhomogeneities alsocompromised the individual estimation of TMA and CRresonances. These resonances are separated by 0.19 ppm,which corresponds to 12.1 Hz at 1.5 T. Furthermore, coilsensitivity drop-off due to greater distance between thelateral wall and the coil array (Table 4) relates tothe reduced sensitivity in the lateral area. Relative to theanteroseptal segment, the signal-to-noise ratio in theposterolateral segment was reduced by 30%.

Overall, shimming was found to be a limiting factor.Voxel volumes were 0.290 mL for EPSI and 8 mL forPRESS. Accordingly, significantly smaller linewidthswere detected in the septal region for the EPSI scan com-pared with the PRESS scans (Table 1). With the avail-ability of higher order shims, the linewidth limitationsin the regions of the lateral wall and the posterior veinof the left ventricle can be addressed in future work.Multiple channel coil arrays are expected to leverage thelimited sensitivity in lateral and posterior regions along-side translating the work to higher B0 field strengths.High-field application will also improve the separationof the TMA and CR resonances, which was found to belimiting in this study at 1.5 T.

The quantification of TG and CR was corrected forlongitudinal and transversal relaxation effects based onliterature values for T1 and T2. The effect of T2 correc-tion on the quantitative results was found to be small forEPSI given the short TEs used. The TE of the doublespin echo PRESS sequence, however, was almost threetimes longer and hence inaccuracies in T2 may haveresulted in significant differences in the quantitativeresults of the PRESS measurements. The T2 correctionfactors for TE of 33 ms (PRESS)/12 ms (EPSI) did changerelative TG and CR content by 36%/15% and 44%/19%,respectively. Assuming a 10% uncertainty in T2, the cor-rection factors for PRESS/EPSI are offset by 12%/5% and

FIG. 7. Linear (a) and Bland-Altman plot (b) of EPSI and PRESS.The line of identity is indicated in (a) by the solid line. In (b), thesolid line indicates the mean values; the dashed lines indicate

mean value 61.96 times the standard deviation. Data are shownfor mean values over all segments and the single segments 1, 2,

3, 4, 5, and 6 in comparison with the PRESS measurements.

Table 4Comparison of Sensitivity in the Six Compartments

Segment 1 2 3 4 5 6

S/N compared with segment 2 0.91 6 0.13 1 0.88 6 0.12 0.70 6 0.08 0.68 6 0.10 0.81 6 0.11

The intensities of the water-unsuppressed signals are compared with the water-unsuppressed signal from segment 2, the segment with

the highest mean intensity.

MRI of TG and CR Content in the Human Heart 7

11%/4% for TG and CR and thus may explain in partsthe difference seen between PRESS and EPSI in the sep-tal region. Correction for longitudinal relaxation didchange the relative TG and CR content by 26 6 5% and9 6 4% depending on heart rate. A 10% uncertainty inthe estimated T1 relaxation time would result in an offsetfor TG and CR content of 6.7 and 11%, respectively. Asthe influence of T1 relaxation for EPSI and PRESS iscomparable, differences of TG and CR content measuredwith EPSI and PRESS are not explained by the uncer-tainty in T1 values. However, they may partly explaindifferences compared with CR content reported in theliterature (2,9). In other applications, it was demon-strated that corrections for longitudinal and transversalrelaxation effects can introduce systematic errors (28,29).Accordingly, subject-specific measurements of relaxationconstants seem warranted and need to be included infuture studies.

The variance found across all segments of the EPSI datais attributed in parts to the reduced coil sensitivity forlateral and posterior segments and to a loss in spectralresolution given strong B0 gradients in particular close tothe posterior vein of the left ventricle compromising time-domain fitting of the TG and CR resonance lines.

In contrast to single voxel techniques, the presentedEPSI technique allows assessing myocardial CR and TGcontent from several regions of interest. These regions ofinterest were defined according to a six-segment modelfor a midcavity region. Contamination from epicardial fatwould be a potential risk in all but the septal region andcould lead to an increase in the measured TG content(3). Segments were chosen to avoid voxels, which werebiased by partial volume effects. These voxels could beclearly identified using a fat map from water-suppressedscans (Fig. 4b), as the epicardial fat content is about twomagnitudes higher compared with the intramyocellularTG content. To prevent signal contamination due to anonoptimal point-spread function, Hamming filteringwas used, reducing the side lobes of the point-spreadfunction. To reduce partial volume effects, two strategiescould be used in future work. First, the EPSI grid can befreely moved using the Fourier shift theorem, thus thenumber of voxels used for analysis can be maximized.However, the shape of the point-spread function wouldstill be nonoptimal and Hamming filtering would still berequired. The second strategy could be based on theapproaches of spectral localization by imaging (36) andspectral localization with optimal pointspread function(37). These methods reconstruct signals in a predefinedregion of interest from a set of phase encodings, optimiz-ing the point-spread function for these regions of inter-est. Coil sensitivities can be used additionally to localizethe signals from different regions of interest as it hasbeen shown recently for brain spectroscopy (38).

CONCLUSIONS

This study has demonstrated that spatial distributions ofmyocardial CR and TG content can be assessed by meansof navigator gated and cardiac triggered 2D local-lookEPSI during free breathing acquisitions. The presentedmethod is considered a promising tool for investigation

of spatial alterations of myocardial energy metabolism incardiac diseases.

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MRI of TG and CR Content in the Human Heart 9