Aug 2026· Academic Radiology· 0 citations· 26 references
Medicine
TL;DR
Advanced diffusion MRI-derived U-fiber metrics may complement clinical measures for exploratory PIRA risk stratification in RRMS and warrant validation in independent multicenter cohorts.
Abstract
Rationale
AND
Objectives
Progression independent of relapse activity (PIRA) contributes to disability accumulation in relapsing-remitting multiple sclerosis (RRMS), but magnetic resonance imaging (MRI) markers of its microstructural substrate remain unclear. We evaluated whether U-fiber metrics derived from neurite orientation dispersion and density imaging and diffusion tensor imaging are associated with subsequent PIRA and may support MRI-based risk stratification.
Materials And Methods
This single-center longitudinal study included 138 patients with RRMS who underwent 3 T brain MRI and were followed for a median of 3.0 years. PIRA required an Expanded Disability Status Scale (EDSS) worsening confirmed over 6 months; events preceded by a relapse within 90 days or followed by a relapse before the 6-month confirmation assessment were excluded. Metrics were extracted from 16 atlas-based superficial U-fiber bundles. Candidate variables underwent univariable screening, variance inflation factor filtering, and exploratory multivariable logistic regression to construct a reduced model. Performance was assessed using five-fold cross-validation, calibration, Brier score, decision curve analysis, and continuous net reclassification improvement (NRI).
Results
PIRA developed in 35 patients (25.4%). Symbol Digit Modalities Test (SDMT), EDSS, right occipitotemporal neurite density index (NDI), right parietotemporal NDI, and right occipitotemporal FA were retained. The reduced model achieved an AUC of 0.793 (95% confidence interval [CI], 0.693-0.893) and a Brier score of 0.143. Adding U-fiber metrics improved reclassification beyond SDMT and EDSS (continuous NRI, 0.518; 95% CI, 0.138-0.882; p = 0.006).
Conclusion
Advanced diffusion MRI-derived U-fiber metrics may complement clinical measures for exploratory PIRA risk stratification in RRMS and warrant validation in independent multicenter cohorts.
Ocrelizumab is an effective treatment for relapsing–remitting multiple sclerosis (RRMS), but its impact on brain and retinal atrophy requires further investigation. To assess the effects of ocrelizumab on brain and retinal atrophy over two years and explore the relationship between imaging biomarkers, early inflammat...
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BACKGROUND
The 2024 McDonald criteria allow multiple sclerosis (MS) diagnosis in pre-symptomatic individuals but their association with MRI activity remains uncertain. We assessed whether paramagnetic rim lesions (PRL) predict future MRI activity beyond the 2024 McDonald criteria.
METHODS
We retrospectively included...
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Magnetic resonance imaging (MRI)-based prediction of multiple sclerosis (MS) progression depends on how imaging data are prepared, represented, modelled, and evaluated. This systematic review synthesized artificial intelligence (AI) methods across the MRI-to-prediction pipeline. PubMed, Scopus, Web of Science, and Goog...
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