Towards harmonized spectral quantification in MRSI: comparative analysis of backward-linear-predicted and original 1H-FID-MRSI dephased data

OBJECTIVE: H-FID-MRSI can introduce systematic LCModel quantification biases due to strong spectral dephasing, and that Backward-Linear-Prediction (BLP) reconstruction toward AD = 0 ms can harmonize LCModel metabolite estimates across acquisitions with various delays. MATERIALS AND METHODS: H-FID-MRSI spectra at multiple ADs under realistic SNR conditions. BLP was applied to in vivo and simulated FIDs to back-predict missing points up to AD = 0 ms, enabling quantification within a unified basis set framework. RESULTS: In vivo and simulated data showed clear AD-dependent variations for several metabolites (Gln, tCho, tNAA, Ins, Tau), with discrepancies frequently > 10% despite AD-specific basis sets. Simulations confirmed metabolite-specific biases increasing with AD. BLP reconstruction preserved quantification consistency up to ~ 0.98 ms of recovered FIDs, reducing inter-AD mismatches in vivo-particularly for Tau, tNAA and tCho-lowering the mean discrepancy from 10.5% to ~ 5%. DISCUSSION: This work supports BLP as a practical strategy to improve consistency and comparability in MRSI studies.