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Bouchard, A. E.

Publications and source records attributed to Bouchard, A. E..

2 recordsLinked to original sources

Test-retest reliability of multi-metabolite edited MRS at 3T using PRESS and sLASER

PurposeSpectral editing is the most common MRS approach for noninvasive in vivo measurement of low-concentration, strongly overlapped metabolites in the brain, such as {gamma}-aminobutyric acid (GABA) and glutathione (GSH). Multi-metabolite editing methods, including HERMES and HERCULES, have recently been introduced, where multiple J-coupled metabolites can be edited in a single acquisition without increasing total scan time. Yet little is known regarding the reliability of these methods. This study assessed the test-retest reliability of HERMES and HERCULES, where volume localization was achieved using either PRESS or sLASER. MethodsSixteen healthy adult volunteers were scanned twice in two separate sessions. Single-voxel edited MRS data were acquired in the medial parietal lobe using the following sequences: (1) HERMES-PRESS; (2) HERMES-sLASER; (3) HERCULES-PRESS; (4) HERCULES-sLASER. Spectra were processed and metabolites were quantified using the Osprey software. Data quality metrics and reliability statistics were estimated for all four acquisitions. ResultsHERMES-sLASER demonstrated lower within-subjects coefficients of variation (CVws) for GSH, glutamine (Gln), and glutamate (Glu) + Gln (Glx), suggesting improved reliability compared to HERMES-PRESS. However, GABA + co-edited macromolecules (GABA+) and Glu showed higher CVws for HERMES-sLASER. HERCULES-sLASER produced better reliability than HERCULES-PRESS for GABA+, GSH, Glu, Gln, Glx, aspartate (Asp), and lactate (Lac). N-acetylaspartate (NAA) and N-acetylaspartylglutamate (NAAG) showed higher CVws for HERCULES-sLASER. These findings suggest that sLASER may be more advantageous than PRESS for volume localization in simultaneous multi-metabolite editing. ConclusionUsing sLASER yielded better test-retest reliability for most metabolites than using PRESS for volume localization for HERMES and HERCULES.

neuroscience↗

Noise decorrelation optimizes SNR of GABA-edited MRS data: A comparison of RF coil combination methods

Introduction: Determining the best radiofrequency (RF) coil combination method is crucial for maximizing the signal-to-noise ratio (SNR) to detect low concentration metabolites (e.g., {gamma}-aminobutyric acid (GABA)) in magnetic resonance spectroscopy (MRS). We hypothesized that algorithms accounting for noise correlations between coil elements would optimize SNR, given that phased-array coils provide better SNR than surface coils and allow accelerated acquisitions, and methods accounting for noise correlations outperform those assuming no correlations. Methods: We examined six coil combination methods, the latter half accounting for noise correlations: 1) equal weighting; 2) signal weighting; 3) S/N2 weighting; 4) noise-decorrelated combination (nd-comb); 5) whitened singular value decomposition (WSVD); 6) generalized least squares (GLS). We utilized MEGA-PRESS data from 119 participants (mean age: 26.4 {+/-} 1 SD 4.2 years; males/females: 54/65) acquired on 3T GE and Siemens MRI scanners at 11 research sites, obtained from the Big GABA study. We measured the SNR of GABA and N-acetylaspartate (NAA). We also calculated the intersubject coefficients of variation of GABA. Results: There were significant differences in SNR between coil combination methods for both GABA+ and NAA. More specifically, the noise decorrelation methods produced higher GABA+ and NAA SNR than the other approaches, where nd-comb, WSVD, and GLS produced, on average, ~37% and ~34% more SNR than equal weighting, respectively. GLS produced the highest SNR for GABA+ and NAA. The coefficients of variation for GABA+ were generally slightly smaller for the noise decorrelation methods. Conclusion: Noise-decorrelation methods produced higher SNR than other methods, especially GLS, which should be investigated in advanced editing protocols.

neuroscience↗