LAUSR

The purpose of this work is to develop and validate a new atlas‐based metabolite quantification pipeline for edited magnetic resonance spectroscopic imaging (MEGA‐MRSI) that enables group comparisons of brain structure‐specific GABA levels. By using brain structure masks segmented from high‐resolution MPRAGE images and coregistering these to MEGA‐LASER 3D MRSI data, an automated regional quantification of neurochemical levels is demonstrated for the example of the thalamus. Thalamic gamma‐aminobutyric acid + coedited macromolecules (GABA+) levels from 21 healthy subjects scanned at 3 T were cross‐validated both against a single‐voxel MEGA‐PRESS acquisition in the same subjects and same scan sessions, as well as alternative MRSI processing techniques (ROI approach, four‐voxel approach) using Pearson correlation analysis. In addition, reproducibility was compared across the MRSI processing techniques in test–retest data from 14 subjects. The atlas‐based approach showed a significant correlation with SV MEGA‐PRESS (correlation coefficient r [GABA+] = 0.63, P < 0.0001). However, the actual values for GABA+, NAA, tCr, GABA+/tCr and tNAA/tCr obtained from the atlas‐based approach showed an offset to SV MEGA‐PRESS levels, likely due to the fact that on average the thalamus mask used for the atlas‐based approach only occupied 30% of the SVS volume, ie, somewhat different anatomies were sampled. Furthermore, the new atlas‐based approach showed highly reproducible GABA+/tCr values with a low median coefficient of variance of 6.3%. In conclusion, the atlas‐based metabolite quantification approach enables a more brain structure‐specific comparison of GABA+ and other neurochemical levels across populations, even when using an MRSI technique with only cm‐level resolution. This approach was successfully cross‐validated against the typically used SVS technique as well as other different MRSI analysis methods, indicating the robustness of this quantification approach.