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Edited MRS sequences are widely used for studying γ‐aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA‐edited (GABA+, TE = 68 ms MEGA‐PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL‐MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor‐specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms …