Microstructural phenotyping and clinical relevance of multiple sclerosis lesions using quantitative susceptibility source separation

Background: Quantitative susceptibility mapping (QSM) exhibits phase cancellation between paramagnetic (e.g. iron) and diamagnetic (e.g. myelin/protein) sources, obscuring microstructural lesion heterogeneity in multiple sclerosis (MS). We evaluated whether biophysical {chi}-separation identifies clinically meaningful lesion phenotypes and whether reduced echo sampling preserves microstructural sensitivity. Methods: In this cross-sectional study of 183 people with multiple sclerosis (PwMS), we analyzed 3327 quality-controlled white matter lesions using 3T MRI with a five-echo gradient-recalled echo sequence (GRE5) and a subsampled two-echo dataset (GRE2). A hybrid framework combining unsupervised clustering on whole-lesion paramagnetic ({chi}para) and diamagnetic ({chi}dia) features with rule-based compartmental edge-core gradient assignment resolved MS lesion phenotypes. Intralesional microstructural properties were evaluated using linear mixed-effects models. Multivariable linear regressions assessed associations with physical disability (Expanded Disability Status Scale, EDSS; n = 158), cognitive processing speed (Symbol Digit Modalities Test, SDMT; n = 79), and disease duration (DD; n = 161), with sensitivity models adjusting for total lesion volume, count, or DD. Results: The framework identified four reproducible lesion phenotypes (Adjusted Rand Index = 0.924): Type 1 (22.7%; preserved {chi}dia), Type 2 (32.9%; high {chi}para without positive edge-core gradient), Type 3 (35.8%; attenuated {chi}dia), and Type 4 (8.6%; high {chi}para with a positive edge-core paramagnetic gradient). Higher EDSS was selectively associated with more negative signed {chi}dia within Type 4 lesions (whole: {beta} = -0.37, q = 0.020; core: {beta} = -0.37, q = 0.006; edge: {beta} = -0.34, q = 0.030) and Type 2 edge ({beta} = -0.33, q = 0.044). Type 4 core associations remained robust across sensitivity models adjusting for total lesion volume ({beta} = -0.35, q = 0.004), total lesion count ({beta} = -0.37, q = 0.008), and DD ({beta} = -0.32, q = 0.033). Abbreviated GRE2 attenuated Type 4 compartmental associations to non-significance (all q greater than 0.05; core: {beta} = -0.20, q = 0.215). Conclusions: Quantitative {chi}-separation identified four internally stable susceptibility-defined MS lesion phenotypes, revealing disability-associated tissue heterogeneity beyond total lesion burden. Higher EDSS was associated with more negative diamagnetic measures within Type 4 cores after adjustment for lesion burden, pointing toward complex intralesional non-myelin tissue remodeling or reactive astrogliosis. Two-echo subsampling may influence compartment-specific clinical associations. By uncoupling susceptibility sources, {chi}-separation provides a quantitative framework for characterizing disability-associated lesion heterogeneity.