MRI continues to be the foundation of multiple sclerosis (MS) diagnosis and management. The latest innovations in technology have paved the way for earlier diagnosis, more informed treatment selection, better means of evaluating the disease course, and personalized therapeutic responses. This review summarizes the most recent developments in advanced MRI for MS, highlighting biomarkers that were newly added in the 2024 revisions of the McDonald criteria, describing the ongoing importance of established imaging measures, reviewing the applications of artificial intelligence in clinical practice, and suggesting future directions. Special emphasis is placed on the official adoption of the optic nerve as a fifth site of dissemination in space, as well as on the central vein sign and paramagnetic rim lesions as key supporting evidence in MS. Additionally, ongoing limitations and challenges in integrating these markers into clinical practice across both academic and community settings are identified. The overall goal is to improve diagnosis and prognostication in MS through imaging approaches that have higher contrast resolution and are more quantitative and biologically informed.
N. Michaelson, Sittaya Buathong, C. Treaba et al.· Radiology· 0 citations
BACKGROUND AND PURPOSE
Neurodegeneration is a key component of clinical disability in multiple sclerosis (MS). However, the underlying mechanism of localized gray matter (GM) atrophy in MS remains unknown. More recently, a network-based etiology has been postulated, which may be associated with clinical progression. The goal of this study was to determine whether GM microstructural abnormalities are organized across an atrophy-prone network.
MATERIALS AND METHODS
We leveraged high-gradient diffusion MRI (dMRI) to probe GM mesoscopically by using the SANDI (Soma and Neurite Density Imaging) biophysical modeling approach. The intra-soma signal fraction (fis) was computed, which is a putative biomarker of GM cytoarchitecture. Regions of interest (ROIs) defined by nodes in the Atrophy-based Functional Network (AFN) were used to sample the individual fis map. Group-wise comparisons of the nodal and aggregate fis were assessed using Mann-Whitney U tests, and the multivariate fis (principal component 1; PC1) using independent samples t-tests, with false discovery rate (FDR) correction. Association of PC1 with the Expanded Disability Status Scale (EDSS) score was assessed using partial Spearman's rank-order correlation, controlling for age and sex. The same approach was applied to examine relationships across all nodal pairs.
RESULTS
Participants included 38 MS (M/F: 11/27; age: 44 ± 11 years; EDSS: median 2.25, range: 1 - 7.5; disease duration: median 8.5 [IQR: 4.0, 14.0] years) and 35 age- and sex-matched healthy controls (HC; M/F: 15/20, p = 0.32; age: 39 ± 15 years; p = 0.13). fis was decreased in MS for the aggregate average and PC1 of all AFN nodes. Correlation of the EDSS and PC1 further showed that fis decreases as disease severity worsens (ρ = -0.44, p < 0.05). FDR-corrected covariance analysis exhibited medium-to-large effect sizes, with surviving correlations having ρ ≥ 0.39.
CONCLUSION
Decreased fis in atrophy-prone GM of MS correlated with disease severity. Further, GM microstructural covariance suggests neuronal loss may relate in part to network effects. Network-based microstructural measures may therefore inform future development of quantitative methods for monitoring disease progression in MS.
Florence L. Chiang, Eva A. Krijnen, Diana A. Hobbs et al.· AJNR. American journal of ne...· 0 citations
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