Ultra-low-field MRI for bedside imaging of severe multiple sclerosis

Abstract Background Severe multiple sclerosis (MS) presents challenges for clinical research due to patient mobility constraints and specialized care needs. Traditional MRI studies often exclude this population but portable, ultra-low-field (ULF) MRI at 0.064 T enables bedside imaging. Objectives To (i) compare ULF MRI volumetry with standard 3 T, (ii) assess the capability of portable ULF MRI in characterizing severe MS. Methods This prospective study enrolled two cohorts. Cohort 1 included healthy controls (HC) and people with MS (pwMS). Cohort 2 enrolled individuals with progressive MS, with either severe or less severe MS. Both cohorts underwent ULF MRI while those in Cohort 1 were also scanned on 3 T MRI. Clinical assessments included disability and cognition. MRI data was processed using both conventional (e.g., SIENAX) and AI-driven (e.g., WMH-SynthSeg) techniques. Group comparisons and MRI-clinical associations were assessed. Results Cohort 1 included 14 HCs (39 ± 13 years, 11 females) and 33 pwMS (32 ± 10 years, 24 females). Cohort 2 included 24 severe MS individuals (62 ± 10, 15 females) and 16 less severe MS individuals (61 years ± 11, 8 females). MRI passed quality control except for scans from 2 individuals in Cohort 2. In Cohort 1, 3 T and ULF MRI showed robust disease differences, with strongest effect sizes for ULF MRI-derived whole brain (partial η 2 = 0.264), cortical gray matter (GM) (partial η 2 = 0.234), and thalamic volumes (partial η 2 = 0.266) from WMH-SynthSeg. In terms of severe versus less severe disease in Cohort 2, the largest effect sizes were obtained with SIENAX-derived cortical GM volume (partial η 2 = 0.349) and whole brain volume (partial η 2 = 0.290), while WMH-SynthSeg yielded the highest effect size for WM volume (partial η 2 = 0.209). For clinical outcomes, associations were dependent on processing method, although SIENAX yielded the most consistent correlations in Cohort 2. Conclusion Portable, ULF MRI is feasible in pwMS and provides insights into late-stage neurodegeneration in severe MS.