Multi-compartment susceptibility source separation (mc-chi-separation) using GRE data only: Integrated model of QSM and myelin water imaging

Motivation: Chi-separation enables separate estimation of diamagnetic myelin and paramagnetic iron, but requires quantitative R2 measurements, limiting its application. Goal(s): To develop a new chi-separation method combining both macroscopic and microscopic field perturbation information to perform chi-separation using only GRE data. Approach: We propose multi-compartment chi-separation (mc-chi-separation) that models effects of myelin and water compartmentalization on transverse relaxation (as in myelin water imaging [MWI]) as well as their contributions to bulk susceptibility (as in QSM). Results: Mc-chi-separation successfully estimates iron and myelin distributions with higher SNR and reduced sensitivity to B₀-field inhomogeneity compared to MWI, while maintaining contrast comparable to conventional chi-separation. Impact: Mc-chi-separation enhances susceptibility source separation by enabling chi-separation using GRE data only, expanding its applications to clinical settings and pre-acquired data lacking R2 measurements. This may also facilitate better monitoring of iron and myelin-related neurodegenerative disease with reduced inter-site variability.