Conventional MRI-Based Structural Disconnection and Morphometric Similarity Networks and Their Clinical Correlates in Multiple Sclerosis.

Abstract

Although multiple sclerosis (MS) can be conceptualized as a network disorder, brain network analyses typically require advanced MRI sequences not commonly acquired in clinical practice. Using conventional MRI, we assessed cross-sectional and longitudinal structural disconnection and morphometric similarity networks in people with MS (pwMS), along with their relationship with clinical disability. In this longitudinal monocentric study, 3T structural MRI of pwMS and healthy controls (HC) was retrospectively analyzed. Physical and cognitive disabilities were assessed with the expanded disability status scale (EDSS) and the symbol digit modalities test (SDMT), respectively. Demyelinating lesions were automatically segmented, and the corresponding masks were used to assess pairwise structural disconnection between atlas-defined brain regions based on normative tractography data. Using the Morphometric Inverse Divergence method, we computed morphometric similarity between cortical regions based on FreeSurfer surface reconstruction. Using network-based statistics (NBS) and its extension NBS-predict, we tested whether subject-level connectomes were associated with disease status, progression, clinical disability, and long-term confirmed disability progression (CDP), independently from global lesion burden and atrophy. We studied 461 pwMS (age = 37.2 ± 10.6 years, F/M = 324/137), corresponding to 1,235 visits (mean follow-up time = 1.9 ± 2.0 years, range = 0.1-13.3 years), and 55 HC (age = 42.4 ± 15.7 years; F/M = 25/30). Long-term clinical follow-up was available for 285 pwMS (mean follow-up time = 12.4 ± 2.8 years), 127 of whom (44.6%) exhibited CDP. At baseline, structural disconnection in pwMS was mostly centered around the thalami and cortical sensory and association hubs, while morphometric similarity was extensively disrupted (<i>p</i>_FWE < 0.01). EDSS was related to frontothalamic disconnection (<i>p</i>_FWE < 0.01) and disrupted morphometric similarity around the left perisylvian cortex (<i>p</i>_FWE = 0.02), while SDMT was associated with cortico-subcortical disconnection in the left hemisphere (<i>p</i>_FWE < 0.01). Longitudinally, both structural disconnection and morphometric similarity disruption significantly progressed (<i>p</i>_FWE = 0.04 and <i>p</i>_FWE < 0.01), correlating with EDSS increase (ρ = 0.07, <i>p</i> = 0.02 and ρ = 0.11, <i>p</i> < 0.001), while baseline disconnection predicted long-term CDP (accuracy = 59% [58-60], <i>p</i> = 0.03). Structural disconnection and morphometric similarity networks, as assessed through conventional MRI, are sensitive to MS-related brain damage and its progression. They explain disease-related clinical disability and predict its long-term evolution independently from global lesion burden and atrophy, potentially adding to established MRI measures as network-based biomarkers of disease severity and progression.