cardiac proton spectroscopy using large coil arrays

Cardiac proton spectroscopy using largecoil arraysKilian Weissa, Nicola Martinib, Peter Boesigera and Sebastian Kozerkea*

Large coil arrays are widely used in clinical routine for cardiovascular imaging providing extended spatial coverageand enabling accelerated acquisition using parallel imaging approaches. This work investigates the use of large coilarrays in single-voxel cardiac spectroscopy for the detection of myocardial creatine and triglyceride content. For thispurpose, a navigator-gated and cardiac-triggered point-resolved spectroscopy sequence was implemented, and dataobtained in 11 healthy volunteers using 32- and 5-element coil arrays were compared. For combination of theindividual coil element signals, four strategies were evaluated differing in the manner of estimation of the complexcoil weights and the amount of additional information required for coil combination. In all volunteers, and with boththe 32- and 5-channel coil arrays, triglyceride-to-water (0.44� 0.19% and 0.45� 0.17%) and total creatine-to-water (0.05� 0.02% and 0.05� 0.01%) contents were computed. The values were found to agree well, showingan intraclass correlation coefficient of 0.76 (p< 0.003). The results revealed a gain in signal-to-noise ratio ofapproximately 24% with the 32-channel coil relative to the 5-channel array. The findings may foster the integrationof cardiac spectroscopy into clinical practice using large coil arrays, provided that appropriate reconstructionalgorithms are implemented. Copyright © 2012 John Wiley & Sons, Ltd.

Keywords: cardiac spectroscopy; coil arrays; coil combination; triglyceride; creatine; signal-to-noise ratio

INTRODUCTION

MRS can provide fundamental insights into the role of cardiacmetabolism in normal and diseased hearts (1,2). Localizedproton MRS (1H MRS), in particular, has been demonstrated tobe a valuable technique for the noninvasive measurement ofhuman myocardial triglyceride (TG) and total creatine (CR)contents (3–6). Recent studies based on 1H MRS have highlightedcorrelations between lipid accumulation in the myocardiumand reduced cardiac function, and have revealed the role ofsteatosis in the pathogenesis of type 2 diabetes mellitus (4,7,8).Assessment of the total CR content, which reflects the sum ofcreatine and its phosphorylated form phosphocreatine, hasbeen reported, and depletion in the failing heart has beendemonstrated (3,5).Several technical and practical issues have, however, limited the

widespread use of cardiac 1H MRS in clinical routine so far. Cardiacand respiratory motions degrade the spectral quality because ofinhomogeneous B0 and B1 fields, outer voxel contamination andphase changes as a result ofmotion of the spins during localizationgradients. Although electrocardiogram (ECG) triggering to end-systole is commonly used to synchronize volume selection anddata acquisition with cardiac motion, several approaches havebeen proposed to compensate for respiratory motion. Triggeringbased on respiratory signals provided by air-pressure sensors hasbeen shown to improve the quality of cardiac spectra (9). Breath-holding has been used to assess myocardial TG content (10,11).However, restricted breath-hold durations inherently limit thenumber of signal averages, and hence the sensitivity for thedetection of myocardial CR. An alternative method used tosynchronize the acquisition to end-respiration is based onnavigator echoes to measure the position of the diaphragm(12,13). Navigator gating has been found to be a prerequisite forthe reproducible assessment of myocardial TGs (6).

Other practical issues of cardiac MRS concern radiofrequency(RF) coil selection and coil placement for signal reception.Traditionally, single-element surface coils are positioned on thechest wall of the subject. However, the use of single-loop coilshas drawbacks. The limited spatial coverage requires carefulpositioning of the coil as close as possible to the region of interestto maximize the signal-to-noise ratio (SNR). Coil repositioning isnecessary in some cases to accurately place the coil center overthe mitral valve level of the heart (6). At the same time, single-channel receive coils continue to be replaced by coil arrays onmodern MR systems, providing larger spatial coverage andpermitting accelerated acquisition using parallel imagingtechniques. Coil arrays with 32 elements are becoming a standardfor highly accelerated cardiovascular imaging (14,15). The largespatial coverage provided by these coil arrays renders coilrepositioning during examinations unnecessary. Accordingly, it

* Correspondence to: S. Kozerke, Institute for Biomedical Engineering, Universityand ETH Zurich, Gloriastrasse 35, 8092 Zurich, Switzerland.E-mail: [email protected]

a K. Weiss, P. Boesiger, S. KozerkeInstitute for Biomedical Engineering, University and ETH Zurich, Zurich,Switzerland

b N. MartiniFondazione G. Monasterio CNR-Regione Toscana, Massa, Italy

Abbreviations used: 4CH, four chamber; CR, total creatine; ECG, electrocar-diogram; FID, free induction decay; FWHM, full width at half-maximum; 1HMRS, proton MRS; PCA, principal component analysis; PCAs, principalcomponent analysis of the water-suppressed signals; PCAw, principal componentanalysis of the water-unsuppressed signals; PRESS, point-resolved spectroscopy;RF, radiofrequency; SA, short axis; SD, standard deviation; SNR, signal-to-noiseratio; SNRw, SNR weighting; SV, single voxel; TG, triglyceride; TMA,trimethylammonium.

Research article

Received: 5 April 2012, Revised: 19 July 2012, Accepted: 25 July 2012, Published online in Wiley Online Library: 2012

(wileyonlinelibrary.com) DOI: 10.1002/nbm.2845

NMR Biomed. 2012 Copyright © 2012 John Wiley & Sons, Ltd.

would be desirable to use large coil arrays for both imaging andspectroscopy of the heart, and thereby facilitate the integrationof cardiac 1H MRS into clinical workflow.

The purpose of this work was to explore the use of large coilarrays for navigator-gated and ECG-triggered detection ofmyocardial creatine and TG content using cardiac 1H MRS.Suitable reconstruction techniques of spectroscopy data frommultiple receiver elements are compared, and in vivo resultsobtained with 32- and 5-element coil arrays in 11 healthy volun-teers are presented.

METHODS

Sequence implementation

A short-TE (33ms) navigator-gated point-resolved spectroscopy(PRESS) sequence (16) was used for single-voxel (SV) localizationin the interventricular septum to avoid epicardial fat contamina-tion (Fig. 1a,b). Pencil-beam navigator echoes were implementedfor respiratory motion compensation (13). Prior to data acquisition,iterative shimming was performed during a breath-hold using avoxel slightly larger than the SV (Fig. 1a,b). Navigator triggeringwas employed for water suppression optimization. The PRESSsequence was ECG triggered to the end-systolic phase, theminimum TR was set to 2000ms and voxel dimensions were10mm� 20mm� 40mm, resulting in an 8-mL volume. Watersuppression was implemented using two frequency-selective RFpulses, each followed by a gradient spoiler; 1024 complex datapoints were collected with a spectral width of 2000Hz.

In vivo experiments

In vivo experiments were performed using a 1.5-T Philips Achievasystem (Philips Healthcare, Best, the Netherlands) on a total of 15volunteers who gave their written informed consent beforeparticipating in the study. Cine images in four-chamber (4CH)and short-axis (SA) views were acquired to accurately placethe SV volume in the septum and to determine the triggerdelay of the end-systolic phase (Fig. 1a,b). A balanced steady-state free precession sequence was used with the followingparameters: TR = 3ms; TE = 1.5ms; flip angle, 60� ; spatialresolution, 2mm� 2mm; slice thickness, 8mm; 40 heart phases.Data were collected during free breathing using navigator gatingin end-expiration to plan the SV volume. Two different protocolswere used for the 1H MRS acquisitions. For the comparison ofthe 5- and 32-element cardiac coil arrays, experiments were per-formed on 11 volunteers [seven men, four women; mean age�standard deviation (SD), 33� 11 years; range, 20–54 years;mean body mass index� SD, 23� 3 kg/m2; range, 17–27 kg/m2).In every acquisition, eight water-unsuppressed scans and 128water-suppressed scans were acquired, resulting in an overall scantime of 11min 20 s with a gating efficiency of about 40%. Both the5- and 32-element cardiac coil arrays were used consecutively forsignal reception in the same session, changing the order of bothcoils for every other volunteer.To test reproducibility for each coil array, experiments were

performed on four volunteers (two men, two women; mean ageSD, 30� 12 years; range, 21–47 years; mean body mass indexSD, 24� 2 kg/m2; range, 21–25 kg/m2). In every acquisition,eight water-unsuppressed scans and 64 water-suppressed scans

TMA CR

TG

TMA CR

TG

4 3 2 1 0 4 3 2 1 0frequency in ppm frequency in ppm

32 channel 5 channela)

b)

c)

d)

e)

Figure 1. Position of the point-resolved spectroscopy (PRESS) voxel (inner box) and the shimming volume (outer box) in short-axis view (a) and four-chamber orientation (b). (c–e) Spectra from three different volunteers acquired with the 32- and 5-channel coil arrays showing the resonances of myo-cardial trimethylammonium (TMA) compound, total creatine (CR) and triglycerides (TG).

K. WEISS ET AL.

wileyonlinelibrary.com/journal/nbm Copyright © 2012 John Wiley & Sons, Ltd. NMR Biomed. 2012

were acquired, resulting in an overall scan time of 6min with agating efficiency of about 40%. The volunteers were takenout of the scanner and were repositioned in between twosubsequent scans using either the 5- or 32-element cardiac coilarray for signal reception. The measurement was repeated usingthe other coil array for signal reception on the same volunteer ina second session. The time between the two sessions was ap-proximately 1week. Each session, including subject preparation,acquisition of MRI cine images and acquisition of MRS data, tookapproximately 1 h in total.

MRS data processing

For each dataset, offline reconstruction of multichannel MRSdata was performed using Matlab (The Mathworks, Natick, MA,USA). Data reconstruction steps are listed in Fig. 2. Noisecovariance matrices were estimated from a separate noise scanand were used to decorrelate the coil channels before coilcombination. This step has been shown to be a prerequisite forthe optimal combination of spectra from receive coil arrays atlow SNRs (17,18).For subsequent coil combination, four strategies to estimate

complex coil weights Wc were compared. The first approachwas based on a linear combination of the coil signals using anSNR weighting (SNRw) approach (19). The second approach wasbased on principal component analysis (PCA) of the coil signals(18,20) from the water-unsuppressed reference scans (PCAw).The third strategy employed PCA of the mean signals of thewater-suppressed scans (PCAs). The PCAw and PCAs coilcombination strategies are summarized in Fig. 3. In the fourthapproach, complex coil weights were estimated from cineimages in SA and 4CH orientations acquired for optimal

placement of the SV. Although the first and second approachesrequired water-unsuppressed data, the third and fourth coilcombination methods did not rely on any additional type ofreference data.

Using the estimated complex coil weighting factors Wc, theindividual coil signals were combined according to:

Scomb tð Þ ¼X

c

WcSc tð Þ [1]

where Sc(t) refers to signals of the individual coils and Scomb(t)to the resulting combined signal at time point t of the freeinduction decay (FID).

The general processing steps as outlined in Fig. 2 wereidentical for all coil combination strategies. A phase correctionprocedure of individual acquisitions was applied after coilcombination before coherent averaging to reduce SNR loss asa result of residual motion-induced phase fluctuations (21).Phase correction of the water-unsuppressed spectra wasperformed using the first points of the FID. Phase correction ofthe water-suppressed spectra was based on the spectral peakof the main TG resonance located at 1.3 ppm.

Coil combination using the SNRw approach

The SNR of every coil was calculated as the ratio of the signalamplitude and the SD of the noise in the time domain. The phaseand amplitude of the water-unsuppressed signals were estimatedfrom the first points of the FID; the SD of the background noise wasestimated from the last points of the FID when the signal hadalready decayed. The SNR and phase of every coil were used toestimate the complex weighting factors Wc. The coil signals weresubsequently combined according to Equation [1].

Raw water signals

DC correction

Raw water -suppressed signals

Phase correction(based on water peak)

Phase correction(based on TG peak)

a)

b)Noise decorrelation

Estimation of complex coil weights*

Constructive averaging

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Water signals Water-suppressedsignals

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Figure 2. (a) Overview of the reconstruction steps of multichannel single-voxel data. Four different approaches were implemented and tested toestimate the complex coil weights for coil combination. TG, triglyceride. The noise correlation matrix of the individual channels of the 32-element coilbefore and after noise decorrelation is shown (b). Coil element weights for the 32-element (c) and 5-element (d) coil arrays are given as a function of thecoil element number.

CARDIAC PROTON SPECTROSCOPY USING LARGE COIL ARRAYS

NMR Biomed. 2012 Copyright © 2012 John Wiley & Sons, Ltd. wileyonlinelibrary.com/journal/nbm

Coil combination using the PCA approach

PCA is used to reduce the dimensionality of a problem byprojection onto a subspace. In the case of coil combinationfor SV spectroscopy, the Hermitian matrix Q was calculatedaccording to:

Q ¼X

t

S tð ÞS tð ÞH [2]

where S tð Þ contains the data from all n coils for time point t ofthe FID. PCA was used to perform a singular value decompositionof Q such that:

Q ¼ UFVH [3]

with F containing the sorted eigenvalues as described in ref. (22)for coil array compression. The complex coil weights Wc wereapproximated by the first column of U and the signals werecombined according to Equation [1].

For the PCAw approach, S tð Þ contained the signals of thewater-unsuppressed reference data. For the PCAs approach, themean signal of the water-suppressed data was used to populateS tð Þ in Equation [2]. This is summarized in Fig. 3.

Coil combination using reference images

The complex valued reference images acquired for correctplacement of the SV were used to estimate the complex coilweights. All pixels within the region of the SV (Fig. 1a,b) wereaveraged and normalized, leading directly to the complex coilweights Wc which were used for coil combination according toEquation [1].

Data analysis

Water-unsuppressed and water-suppressed spectra were fittedin the time domain using the AMARES function of the Java-basedMR user interface software (jMRUI version 3.0) (23). The fullwidth at half-maximum (FWHM) of the water peak in water-unsuppressed spectra was calculated. Three lipid resonanceswith chemical shifts of 0.9, 1.3 and 2.1 ppm, the CR resonanceat 3.01 ppm and the resonance of the trimethylammonium(TMA) compound at 3.2 ppm were fitted in water-suppressedspectra. The sum of the amplitudes of the TG resonances at

0.9 and 1.3 ppm and the resonance of CR were divided by theamplitude of the water peak and multiplied by 100 to yieldthe percentage of myocardial TG and CR content (6). Correctionfor longitudinal and transverse relaxation was applied usingT1 = 1100ms and T2 = 40ms for myocardial water (24),T1 = 280ms and T2 = 86ms for TG estimated in skeletal muscle(25–27), and T1 = 1500ms and T2 = 135ms for myocardial CR(5,25).The SNR of the signals after coil combination was calculated

from time domain amplitudes of the fitted water and main TGsignals at 1.3 ppm and the SD of the last 128 points of the FID.To test differences between the individual measurementsobtained with the 5- and 32-element coil arrays and thedifferent coil combination strategies, a two-tailed paired t-testwas used. For comparison of the quantification results of TGcontent using the 5- and 32-channel coil arrays, intraclasscorrelation coefficients were calculated using a mixed effectanalysis of variance. A level of p< 0.05 was considered to bestatistically significant. Analyses were performed using IBM SPSS(IBM SPSS, version 19; SPSS, Chicago, IL, USA).

Numerical simulations

Numerical simulations were carried out to investigate the noisedependence of the PCAs, PCAw and SNRw coil combinationapproaches. Water-unsuppressed and water-suppressed spectraincluding three lipid resonances with chemical shifts of 0.9, 1.3and 2.1 ppm, the CR resonance at 3.01 ppm and the resonanceof TMA at 3.2 ppm were simulated using parameters obtainedfrom an in vivo scan. To simulate the 32-channel array, thesimulated FIDs were split into 32 channels using complex coilweighting factors Wc estimated from an in vivo scan using theSNRw approach. Random noise was added to the individual coilsignals to provide SNR values of the main TG peak at 1.3 ppmof 3, 4, 5, 6, 8, 13, 23, 38 and 50 in the coil-combined water-suppressed signals and associated SNR values of 100, 150, 200,250, 300, 500, 900, 1500 and 2000 of the water peak in thecoil-combined water-unsuppressed signals. To optimize the PCAs

coil combination strategy, the Hermitian matrix Q in Equation [2]was calculated from a filtered subset of the FIDs which werefiltered using a matched filter and cropped to an acquisition timeof TFID = 2 T2* according to ref. (28), where T2* is the exponentialdecay time estimated from the FID of the coil with the highestsignal. Complex coil weighting factors Wc were estimated usingthe PCAs, PCAw and SNRw approaches and the signals weresubsequently combined according to Equation [1]. As a referencestandard, the simulated signals were additionally combined usingthe known correct complex coil weightsWc used for simulating thesignals of the individual coils. All resulting signals were fitted, signalSNR values were calculated and mean values were compared asdescribed above for the in vivo data. All simulations were repeated100 times. The resulting SNRs are presented as the mean� SD.

RESULTS

Figure 1(c–e) shows representative spectra acquired with bothcoil arrays in three different volunteers. Spectra obtained withthe 32- and 5-channel coil arrays were found to agree well. Inall spectra, the TG resonance at 1.3 ppm, the CR resonance at3.01 ppm and the resonance of TMA at 3.2 ppm were clearly vis-ible. Spectral quality and sensitivity were found to becomparable for both coils. For low SNR signals (SNR< 10), the

Figure 3. Schematic diagram of principal component analysis (PCA)-based coil combination. PCAw, water-unsuppressed signals of the individualcoils were analyzed by PCA to estimate the coil weights Wc. PCAs, water-suppressed signals of the individual coils were analyzed by PCA to estimatethe coil weights Wc.

K. WEISS ET AL.


results of the numerical simulations revealed significant differ-ences in the SNR after coil combination using the PCAs approach.However, no significant differences were found when onlyfiltered subsets of the FIDs were used to calculate the complexcoil weights Wc employing the PCAs approach. Differences inthe resulting SNR when the full FIDs or filtered subsets of theFIDs were used are shown in Fig. 4a. However, no significantdifferences were found for high SNR values (SNR> 10). Figure 4bcompares the SNR of the three different coil combinationstrategies (PCAs, PCAw, SNRw) relative to the SNR of the coilcombination using known complex coil weights. No significantdifferences were found between the combination strategies.In vivo spectra obtained with the 32- and 5-channel arrays forthe four coil combination strategies are shown in Fig. 5. In allspectra, the resonances of TG, CR and TMA are well defined.Spectral quality and sensitivity appear to be similar in the spectraof the investigated coil combination strategies. A quantitativeestimation of the resulting SNRs using the PCAw, PCAs and SNRwapproaches for coil combination and the two coil arrays is givenin Table 1. Differences between the mean values of the SNR for

the combination approaches were found to be small for bothcoils, and not significantly different. SNR values obtained withthe 32-element coil were 24% higher than those obtained withthe 5-element coil array, on average (Table 1), although thedifferences did not reach statistical significance. SNR variationsbetween subjects were found to be large, as reflected by thelarge SDs (Table 1). Figure 6 shows the comparison betweenthe complex coil weights Wc estimated from water-unsuppressed spectra using the SNRw approach and fromimages in SA and 4CH view orientations. For both coils,combination weights estimated from spectroscopic (SNRw) andimaging data were found to be highly correlated. Mean valuesof the FWHM of the water peak across all subjects werebelow 10Hz for both coils (Table 2). The estimated values formyocardial TG and CR content after correction for T1 and T2relaxation are shown in Table 2. A close agreement is seenbetween the mean values across subjects obtained with thetwo coil arrays. In particular, the percentage of TG content wasvery consistent between the coil arrays, showing an intraclasscorrelation coefficient of 0.76 (p< 0.003). No significantdifferences in the CR and TG contents between the two coilarrays were detected.

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est.

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ref. SNR

est.

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ref. SNR

a)

b)

Figure 4. Numerical simulations. (a) Estimated signal-to-noise ratio (SNR)after coil combination using the water-suppressed principal componentanalysis (PCAs) approach employing a filtered subset and all points of thefree induction decays (FIDs) to estimate the complex coil weights Wc. (b)Comparison of the PCAs, water-unsuppressed PCA (PCAw) and SNRweighting (SNRw) combination approaches. A filtered subset of the FIDswas used to estimate Wc using the PCAs approach. No significantdifferences were found between the different combination strategies. Allvalues are plotted against the reference SNR (ref. SNR) values for coilcombination using the known weights Wc.

SNRW

PCAW

PCAS

Image-based

32 channel 5 channel

TMA CR

TG

TMA CR

TG

4 3 2 1 0 4 3 2 1 0frequency in ppm frequency in ppm

Figure 5. Spectra of one healthy volunteer. The signals of the individualcoil elements were combined using complex coil weights estimatedby signal-to-noise ratio (SNR) weighting (SNRw), principal componentanalysis (PCA) of the water reference signals (PCAw), PCA of the meanof the water-suppressed signals (PCAs) and the image-based approach.The resonances of myocardial trimethylammonium (TMA), total creatine(CR) and triglyceride (TG) are indicated. Differences between coil arrayswere not statistically significant.



For the 5-element coil, the two elements with the highest sig-nal provided 99% of the SNR (Fig. 7a). For the 32-element coil, 16elements with the highest signals provided 99% of the SNR

(Fig. 7b). The test–retest reliability measurements on four healthyvolunteers (n=4) showed a higher SNR for the 32-channel arrayrelative to the 5-channel array in both measurements (Fig. 8a).However, no significant differences were found for estimatedmyocardial TG and CR content, either between two subsequentmeasurements with the same coil array or between the two coilarrays (Fig. 8b). Differences between coil combinationapproaches (PCAs, PCAw, SNRw) were statistically nonsignificant.

DISCUSSION

In this work, the feasibility of 1H cardiac spectroscopy using largecoil arrays has been demonstrated. The performance of a32-channel coil array was assessed relative to a 5-channel array inthe same scanning session. In all volunteers and with both coil

Table 1. Comparison of signal-to-noise ratio (SNR) performance of the different coil combination strategies using 5- and 32-channel coil array data. SNR was determined using the water and triglyceride (TG) peaks. For the PCAs approach, only the SNRof the TG peak was estimated, as no water reference is available for this method. All values are reported as themean� standard deviation

Reference Coil SNRw PCAw PCAs

Water 5 2181� 1067 2180� 1067 –32 2698� 1392 2700� 1379 –

TG 5 47.3� 33.5 47.2� 33.5 47.4� 33.732 53.8� 33.9 54.0� 33.9 54.1� 33.8

PCAs, water-suppressed principal component analysis (PCA); PCAw, water-unsuppressed PCA; SNRw, SNR weighting.

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Imag

e-ba

sed

∠ W

k Im

age-

base

d [r

ad]

∠ W

k Im

age-

base

d [r

ad]

Figure 6. Comparison of complex coil weighting factors estimated using the signal-to-noise ratio (SNR) weighting (SNRw) approach and the image-based approach for the 5-channel (a) and 32-channel (b) coil arrays. Angles reflect phase differences with respect to the coil element with maximumSNR. The line of identity is shown in gray.

Table 2. Full width at half-maximum (FWHM) of the waterline, myocardial triglyceride (TG) and total creatine (CR) con-tent estimated from 5- and 32-coil array data. All values arereported as the mean� standard deviation

Coil FWHM water TG (%) CR (%)

5 8.6� 1.5 0.45� 0.17 0.05� 0.0132 9.8� 2.0 0.44� 0.19 0.05� 0.02

K. WEISS ET AL.


arrays, spectral quality allowed for the estimation of CR and TGcontents. The TG content showed a high correlation for both coilarrays, and no statistically significant variation of the estimatedCR and TG contents was found between data obtained with thedifferent arrays. Furthermore, estimated values for myocardial CRand TG contents are in good agreement with the values reportedpreviously (6,29).

Four different strategies for coil combination were implementedand compared in terms of SNR performance using numericalsimulations and in vivo measurements. The test–retest reliabilityof the measurements was evaluated on four healthy volunteersusing both coil arrays and the presented coil combinationstrategies. No significant differences were found. Hence, thereproducibility of navigator-gated and cardiac-triggered SVspectroscopy reported previously (6) was confirmed. All coilcombination approaches showed comparable SNR values andquality in the resulting spectra. However, the numericalsimulations revealed a dependence of the PCAs approach on thenumber of points of the FIDs used to estimate the complex coil

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Figure 7. Relative signal-to-noise ratio (SNR) depending on the number of coils used for the reconstruction of the 5-channel (a) and 32-channel (b) coilarray data. In the case of the 5-channel array, two coil elements provide 99% of the maximum SNR (broken line in a). For the 32-channel array, 16 coilelements provide 99% of the maximum SNR (broken line in b). The SNR values were normalized to the mean SNR of the 5-channel coil array. The datapresented are the mean over all 11 volunteers reconstructed using the water-unsuppressed principal component analysis (PCAw) approach.

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[% o

f wat

er p

eak]

a) b)

Figure 8. (a) Signal-to-noise ratio (SNR) of the main triglyceride (TG) peakat 1.3 ppm of the 5- and 32-channel coil arrays in the reproducibility experi-ments on four healthy volunteers. (b) Estimated myocardial TG content ofthe repeated measurements with both coil arrays given as a percentageof the water reference.

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W, voxel wise

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ise

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31P

Figure 9. Signal-to-noise ratio (SNR) of the 32-channel coil array data as a function of the size of the area of interest in a spectroscopic imagingexperiment. The two-dimensional spectroscopic imaging datawere acquired using an echoplanar spectroscopic imaging sequencewith a 3mm� 3mm� 15mmresolution (28). (a) Short-axis view image illustrating the different sizes of the areas of interest. (b) SNR for voxel-wise coil combination using the SNR weighting(SNRw, voxel wise) and water-unsuppressed principal component analysis (PCAw, voxel wise) approaches, and for coil combination after summing over all pixelsin the area of interest using the PCAw approach, mimicking a single voxel (PCAw, single voxel). Typical voxel sizes for 1H and 31P spectroscopy are indicated bythe vertical broken lines.



weights for low SNR (SNR< 10). When a large number of points oflow SNR FIDs are used, the PCA is dominated by noise andthe PCAs coil combination approach may fail, as shown in Fig. 4a.For low SNR data, it is beneficial to restrict the PCA to a smallnumber of points at the beginning of the FIDs, where the signalis still high, before it decays into the noise level. To address thisissue, a matched filter was applied and only a subset of the pointsof the FIDs (28) was used to estimate the complex coil weightsWc.Given these considerations, the numerical simulations did notreveal significant differences between the PCAs, PCAw and SNRwapproaches (Fig. 4b). In general, spectral quantification of TGbecomes unreliable at SNRs below 10 and CR resonances approachnoise level.

The investigated coil combination strategies differ in theamount of information required to estimate the complex coilweights Wc. Both the SNRw and PCAw approaches are based onwater-unsuppressed reference scans, which need to be acquiredin addition. The PCAs approach, estimating the complex coilweights Wc from the water-suppressed data, does not requireadditional data. Likewise, image-based coil weight estimationutilizes cine images, and hence makes use of survey imagesacquired in any case for SV planning purposes. Both PCAs andthe image-based coil combination allow a shortening of theexamination time if alternative quantification approaches areapplied (30), and water reference data are not required asinternal reference. However, for the estimation of the complexcoil weights Wc from images, the exact position of SV needs tobe known and translated into the orientation of the image itself,adding some complexity to the reconstruction process whencompared with the PCAs approach. Furthermore, the imagesneed to be exported as complex data for every coil element,which is usually not part of standard imaging workflow andhas not been performed for all datasets in the current work.

On average, the mean SNR of the 32-element array was about24% higher (Table 1) than that of the 5-element coil. However,no statistically significant difference was found. This is relatedto the fact that a high variation of SNR between volunteerswas detected, which led to large SDs of the mean SNR values.Parts of this large variation may be explained by variations inthe cardiac trigger delay of the PRESS sequence. In initial tests,it was observed that small changes in the trigger delay led tolarge changes in the SNR of the acquired signals. This is partlyassociated with the motion sensitivity of the PRESS sequenceintroduced by gradient spoilers to suppress FID signalsgenerated by imperfect RF pulses. Further investigations arewarranted to study these effects in detail.

In SV coil combination methods, only spectral correlationscan be utilized, as demonstrated with the PCAw and PCAs

combination strategies. In contrast, multivoxel techniques cantake advantage of the spatial variation of coil sensitivities foroptimal signal combination. To this end, the presented coilcombination approaches can be applied on a voxel-by-voxelbasis for spectroscopic imaging data.

Figure 9 shows the SNR after coil combination as a functionof the size of the area of interest of a spectroscopic imagingscan using the 32-channel coil array. Three approaches wereused for coil combination; voxel-wise SNRw and PCAw of aspectroscopic imaging scan (29) and, to simulate an SV, the PCAw

coil combination after summing over all voxels in the area ofinterest. Voxel-wise SNRw and PCAw coil combinations showedsimilar performance. For a small number of voxels, the differencebetween the voxel-wise coil combination and the combination

after averaging over all voxels, mimicking an SV, was found tobe small. In the case of a single spatial point, all methodswill give the same results. However, losses caused by spatialphase variations cannot be recovered in SV acquisitions and,accordingly, extended single volumes may compromise theoptimal coil combination, as can be seen in Fig. 9. For typicalSV sizes as used for 1 H MRS, losses caused by spatially varyingcoil phases are minimal and may be neglected. However, forMRS of less sensitive nuclei, such as phosphorus, larger voxelsare used and losses caused by spatial variations of coil phasesmay become more prominent.Given the availability of large coil arrays in cardiovascular

imaging today, the results of the current work will contributetowards the integration of cardiac spectroscopy into clinicalprotocols. In addition to an advantage in SNR performance, largecoil arrays also provide sufficient coverage, and hence rendercoil repositioning during examinations unnecessary.

CONCLUSIONS

This study has demonstrated the use of large coil arrays for theconsistent detection of CR and TG content in the human heart.Four different coil combination strategies were comparedand the differences were found to be insignificant. Principalcomponent-based coil combination was found to be a simpleand practical approach as it operates on water-suppressed datadirectly and hence does not require additional data as input.Accordingly, the approach can be easily integrated into clinicalMR systems.

Acknowledgements

The authors acknowledge funding by the Swiss National ScienceFoundation (grant #CR3213_132671/1).

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