Introduction

Proton MR spectroscopy has been shown to be a valuable tool to study cardiac triglyceride (TG) levels¹. While single voxel spectroscopy only provides information from a single volume of the interventricular septum, spectroscopic imaging could provide insights into regional TG variations, as it is required in e.g. myocardial ischemia, infarction and other heterogenous cardiac diseases. In contrast to conventional water-suppressed spectroscopic approaches, metabolite cycling² allows to perform phase and frequency correction on the high-SNR water signal, which can be especially beneficial in small voxels³.
The aim of the present work was to implement and compare metabolite-cycled echo-planar spectroscopic imaging (EPSI) relative to single voxel measurements for assessing triglyceride-to-water (TG/W) ratios in the human heart.

Methods

Measurements were performed on 5 volunteers (age = 25.6 ± 6.0 years; 3 male) using a 1.5T Achieva scanner (Philips Healthcare, Best, the Netherlands) with a 5-channel cardiac receiver array. Metabolite cycling was implemented by adding an optimized Hwang pulse^4–6 in front of a local-look EPSI sequence⁷ (Figure 1). Frequency modulation and -offset of the Hwang pulse were inverted for half of the total number of averages acquired per scan. Data was acquired in an equatorial slice in short-axis view (Figure 2). Parameters for EPSI were as follows: NSA = 8, FOV = 300×150 mm², voxel size = 3×3×15 mm³, TR = 1 heartbeat, TE = 12 ms, spectral BW = 1064 Hz, spectral resolution = 4.2 Hz.
For comparison, single voxel spectra were acquired in the interventricular septum (Figure 2) using a PRESS sequence with reduced spoiler areas⁸ and the following sequence parameters: NSA = 96 (water-suppressed) + 16 (water), voxel size = 10×20×40 mm³, TR = 2 s, TE = 22 ms and CHESS based water suppression (BW = 100 Hz). Both EPSI and PRESS measurements were ECG-triggered to end systole and a navigator positioned on the liver was employed for respiratory gating (window = 4 mm).
EPSI data was reconstructed in Matlab (Mathworks, Natick, MA) using a customized reconstruction pipeline. Complex coil maps were calculated for coil combination and spectral ghosts caused by delays between even and odd readout gradients were minimized. B₀ correction was performed for every voxel in every single average individually; the position of the water peak was detected and accordingly shifted in the frequency domain. A Hamming filter was applied to the k-space data in the spatial dimensions to reduce side lobes of the point spread function. Phase correction was applied on the water peak of every voxel in every single average; upfield- and downfield-cycled averages were averaged separately subsequently. Water spectra were calculated by addition of the mean upfield- and downfield-cycled spectra; subtraction was performed to obtain metabolites. For analysis, the heart was divided into six segments (Figure 3). Care was taken not to include epicardial fat when drawing the epicardial contours. Finally, all spectra within each of the segments were averaged.
PRESS data was reconstructed as described in (6). Both EPSI and PRESS spectra were fitted in the time-domain using AMARES (jMRUI)⁹ assuming Lorentzian line shapes. TG/W ratios were calculated and T₁ and T₂ correction applied. Bland-Altman analyses were performed for comparison of EPSI and PRESS.

Results

Exemplary spectra of all six EPSI segments together with a PRESS spectrum for comparison are shown in Figure 3. Although SNR is significantly lower for EPSI compared to PRESS, myocardial TG can be detected in all EPSI regions. Data quality is best in segments 2 and 3 given the proximity of these sectors to the surface coil array. Segments 4 and 5 suffer from reduced coil sensitivity and increased field inhomogeneity due to the presence of the posterior vein of the left ventricle. Bland-Altman analyses of TG/W ratios are shown in Figure 4 comparing individual EPSI segments to PRESS data. The coefficient of variation was found to be smallest for segments 2 and 3. Figure 5 shows mean and standard deviation for the linewidth of the water peak for all EPSI segments and PRESS.

Discussion

Metabolite-cycled EPSI has a number of advantages over water-suppressed EPSI⁷. Total scan time is shorter as no additional reference scan is required. In water-suppressed EPSI a B₀-map is calculated based on the reference water scan and a B₀ correction based on this map is applied to all water-suppressed averages. Using metabolite-cycled EPSI, the B₀ shift can be calculated for every single average individually, which leads to improved B₀ correction. Finally, phasing in metabolite-cycled EPSI can be performed on the high-SNR water signal as opposed to the low-SNR TG signal in water-suppressed EPSI. Limitations of metabolite-cycled EPSI include potential contamination of target segments from adjacent epicardial fat. Accordingly, segments were chosen carefully to avoid tissue interfaces and partial volume voxels as confirmed by Bland-Altman analyses which did not show an overestimation of TG/W for any of the EPSI segments.
While these preliminary results show that TG/W can be detected using metabolite-cycled EPSI, SNR remains limited in order to reliably assign resonances other than TG. To this end, assignment of creatine was not possible in all segments.

Conclusion

Metabolite-cycled echo-planar spectroscopic imaging allows detecting triglyceride-to-water ratios in different regions of the in-vivo human heart.

Acknowledgements

No acknowledgement found.