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Abstract Objective In multiple sclerosis chronic demyelination is associated with axonal loss, and ultimately contributes to irreversible progressive disability. Enhancing remyelination may slow, or even reverse, disability. We recently trialled bexarotene versus placebo in 49 people with multiple sclerosis. While the primary MRI outcome was negative, there was converging neurophysiological and MRI evidence of efficacy. Multiple factors influence lesion remyelination. In this study we undertook a systematic exploratory analysis to determine whether treatment response – measured by change in magnetisation transfer ratio – is influenced by location (tissue type and proximity to CSF) or the degree of abnormality (using baseline magnetisation transfer ratio and T1 values). Methods We examined treatment effects at the whole lesion level, the lesion component level (core, rim and perilesional tissues) and at the individual lesion voxel level. Results At the whole lesion level, significant treatment effects were seen in GM but not WM lesions. Voxel‐level analyses detected significant treatment effects in WM lesion voxels with the lowest baseline MTR, and uncovered gradients of treatment effect in both WM and CGM lesional voxels, suggesting that treatment effects were lower near CSF spaces. Finally, larger treatment effects were seen in the outer and surrounding components of GM lesions compared to inner cores. Interpretation Remyelination varies markedly within and between lesions. The greater remyelinating effect in GM lesions is congruent with neuropathological observations. For future remyelination trials, whole GM lesion measures require less complex post‐processing compared to WM lesions (which require voxel level analyses) and markedly reduce sample sizes.

Abstract Background Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system with an increasing worldwide prevalence. Since 1993, more than 15 disease-modifying immunotherapies (DMTs) have been licenced and have shown moderate efficacy in clinical trials. Based on the heterogeneity of the disease and the partial effectiveness of therapies, a personalised medicine approach would be valuable taking individual prognosis and suitability of a chosen therapy into account to gain the best possible treatment effect. The primary objective of this review is to assess the differential treatment effects of all approved DMTs in subgroups of adults with clinically isolated syndrome or relapsing forms of MS. We will analyse possible treatment effect modifiers (TEM) defined by baseline demographic characteristics (gender, age), and diagnostic (i.e. MRI measures) and clinical (i.e. relapses, disability level) measures of MS disease activity. Methods We will include all published and accessible unpublished primary and secondary analyses of randomised controlled trials (RCTs) with a follow-up of at least 12 months investigating the efficacy of at least one approved DMT, with placebo or other approved DMTs as control intervention(s) in subgroups of trial participants. As the primary outcome, we will address disability as defined by the Expanded Disability Status Scale or multiple sclerosis functional composite scores followed by relapse frequency, quality of life measures, and side effects. MRI data will be analysed as secondary outcomes. MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL and major trial registers will be searched for suitable studies. Titles and abstracts and full texts will be screened by two persons independently using Covidence. The risk of bias will be analysed based on the Cochrane “Risk of Bias 2” tool, and the certainty of evidence will be assessed using GRADE. Treatment effects will be reported as rate ratio or odds ratio. Primary analyses will follow the intention-to-treat principle. Meta-analyses will be carried out using random-effects models. Discussion Given that individual patient data from clinical studies are often not available, the review will allow to analyse the evidence on TEM in MS immunotherapy and thus support clinical decision making in individual cases. Systematic review registration PROSPERO CRD42021279665 .

Multiple sclerosis is a heterogeneous progressive disease. Here, the authors use an unsupervised machine learning algorithm to determine multiple sclerosis subtypes, progression, and response to potential therapeutic treatments based on neuroimaging data.

BackgroundPeople with multiple sclerosis (pwMS) lack sufficient magnetic resonance imaging (MRI) knowledge to truly participate in frequently occurring MRI-related therapy decisions. An evidence-based patient information (EBPI) about MRI is currently lacking.ObjectiveThe aim of this study was to develop an evidence-based online education program about limitations and benefits of MRI for pwMS. Ultimately, our goal was to improve MRI risk-knowledge, empower pwMS, and promote shared decision-making.MethodsThe program's contents were based on literature research and a previous pilot study. It was revised following 2 evaluation rounds with pwMS, MRI experts and expert patients. In a pilot study, n = 92 pwMS received access to the program for 4 weeks. User experiences and acceptance, MRI knowledge (MRI-RIKNO 2.0 questionnaire) and emotions and attitudes toward MRI (MRI-EMA questionnaire) were assessed. Results were compared to a previous survey population of n = 508 pwMS without access to the program.ResultsParticipants rated the program as easy to understand, interesting, relevant, recommendable, and encouraging. In comparison to pwMS without access to the program, MRI risk-knowledge and perceived MRI competence were higher.ConclusionSatisfaction with the program and good MRI-risk knowledge after usage demonstrates the need and applicability of EBPI about MRI in MS.

Background: Slowly expanding lesions (SELs) are MRI markers of chronic active lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in magnetization transfer ratio (MTR) are pathologically correlated with myelin and axonal loss. While all associated with progressive MS, the relationship between these lesion’s metrics and clinical outcomes in relapse-onset MS has not been widely investigated. Objectives: To explore the relationship of SELs with T1-hypointense black holes, and longitudinal T1 intensity contrast ratio and MTR, their correlation to brain volume, and their contribution to MS disability in relapse-onset patients. Methods: 135 patients with relapsing-remitting MS (RRMS) were studied with clinical assessments and brain MRI (T2/FLAIR and T1-weighted scans at 1.5/3 T) at baseline and two subsequent follow-ups; a subset of 83 patients also had MTR acquisitions. Early-onset patients were defined when the baseline disease duration was ≤ 5 years (n = 85). SELs were identified using deformation field maps from the manually segmented baseline T2 lesions and differentiated from the non-SELs. Persisting black holes (PBHs) were defined as a subset of T2 lesions with a signal below a patient-specific grey matter T1 intensity in a semi-quantitative manner. SELs, PBH counts, and brain volume were computed, and their associations were assessed through Spearman and Pearson correlation. Clusters of patients according to low (up to 2), intermediate (3 to 10), or high (more than 10) SEL counts were determined with a Gaussian generalised mixture model. Mixed-effects and logistic regression models assessed volumes, T1 and MTR within SELs, and their correlation with Expanded Disability Status Scale (EDSS) and confirmed disability progression (CDP). Results: Mean age at study onset was 35.5 years (73% female), disease duration 5.5 years and mean time to last follow-up 6.5 years (range 1 to 12.5); median baseline EDSS 1.5 (range 0 to 5.5) and a mean EDSS change of 0.31 units at final follow-up. Among 4007 T2 lesions, 27% were classified as SELs and 10% as PBHs. Most patients (n = 65) belonged to the cluster with an intermediate SEL count (3 to 10 SELs). The percentage of PBHs was higher in SELs than non-SELs (up to 61% vs 44%, p

In subjects with multiple sclerosis (MS), pathology is more frequent near the inner and outer surfaces of the brain. Here, we sought to explore if in subjects with primary progressive MS (PPMS) cortical lesion load is selectively associated with the severity of periventricular normal appearing white matter (NAWM) damage, as assessed with diffusion weighted imaging.To this aim, twenty-four subjects with PPMS and twenty healthy controls were included in the study. Using diffusion data, skeletonized mean diffusivity (MD) NAWM maps were computed excluding WM lesions and a 2mm-thick peri-lesional rim. The supra-tentorial voxels between 2 and 6mm of distance from the lateral ventricles were included in the periventricular NAWM mask while the voxels between 6 and 10mm from the lateral ventricles were included in the deep NAWM mask; mean MD values were then computed separately for these two masks. Lastly, cortical lesions were assessed on phase-sensitive inversion recovery (PSIR) images and cortical thickness was quantified on volumetric T1 images.Our main result was the observation in the PPMS group of a significant correlation between periventricular NAWM MD values and cortical lesion load, with a greater cortical lesion burden being associated with more abnormal periventricular NAWM MD. Conversely, there was no correlation between cortical lesion load and deep NAWM MD values or periventricular WM lesions.Our data thus suggest that a common – and relatively selective - factor plays a role in the development of both cortical lesion and periventricular NAWM abnormalities in PPMS. Keywords: Multiple sclerosis, MRI

Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, R2 = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R2 = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R2 = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R2 = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R2 = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R2 = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R2 = 0.33, p < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline.

Understanding the clinico-radiological paradox is important in the search for more sensitive and specific surrogates of relapses and disability progression (such that they can be used to inform treatment choices in individual people with multiple sclerosis) and to gain a better understanding of the pathophysiological basis of disability in multiple sclerosis (to identify and assess key therapeutic targets). In this brief review, we will consider themes and issues underlying the clinico-radiological paradox and recent advances in its resolution.

Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI.78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals.There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p