BACKGROUND:The central vein sign (CVS) is a neuroimaging biomarker in multiple sclerosis (MS) with high diagnostic specificity. CVS is best detected with high-quality susceptibility-sensitive MRI sequences. For concurrent detection of lesions and veins, FLAIR* was developed as a post-processing method to provide contrast for T2 hyperintense lesions (FLAIR) and paramagnetic hypointense veins (T2*-weighted). Occasionally, CVS-like features have been noted on FLAIR, but the reliability of this finding is unknown. OBJECTIVE:To compare the central FLAIR hypointensity to FLAIR* CVS. METHODS:Scans from the CentrAl Vein Sign in MS (CAVS-MS) pilot study were included for the analysis. A blinded rater assessed all lesions for CVS on 3-tesla post-contrast FLAIR*. A second blinded rater assessed the same lesions for central hypointensity on FLAIR images alone. Counts were compared between methods. The same approach was applied for a subset with available non-contrast FLAIR* lesion ratings. RESULTS:With post-contrast FLAIR* CVS as the standard (n= 92; 1737 lesions), central FLAIR hypointensity demonstrated concordance of 64%, with sensitivity of 34% (95% CI, 30-37%) and specificity of 83% (95% CI, 81-85%). With non-contrast FLAIR* CVS as the standard (n= 38; 768 lesions), FLAIR demonstrated sensitivity of 40% (95% CI, 33-47%) and specificity of 85% (95% CI, 82-88%). Select 6 (≥6 central hypointense lesions) FLAIR was 59% accurate for a diagnosis of MS, with a lower specificity (63% vs. 90%, p= 0.008) in comparison to post-contrast FLAIR*. CONCLUSIONS:Assessment of CVS on FLAIR alone is unreliable and requires susceptibility-sensitive sequences to be clinically useful.

Background and ObjectivesThe 2024 McDonald criteria allow diagnosis of multiple sclerosis (MS) in individuals presenting with symptoms not specific for MS or incidental imaging findings suggestive of demyelination when supported by biomarker evidence, reflecting a shift toward diagnostic definitions increasingly grounded in biological mechanisms of disease. The diagnostic yield of these criteria in such populations has not been evaluated in multicenter cohorts. We aimed to determine the proportion of individuals with nonspecific or incidental imaging presentations who meet the 2024 McDonald criteria and describe the contribution of central vein sign and CSF oligoclonal bands (OCBs) to diagnostic classification.MethodsThis cross-sectional post hoc analysis used data from the Central Vein Sign in Multiple Sclerosis study, a multicenter observational cohort. Adults aged 18-65 years referred for diagnostic evaluation of possible MS were adjudicated by an expert panel. This analysis focused on participants with symptoms not specific for MS or incidental imaging findings suggestive of demyelination. Dissemination in space (DIS) and dissemination in time (DIT) were assessed using 2017 MRI criteria. Fulfillment of the 2024 McDonald criteria at baseline-the primary outcome-was determined using the Select-6 CVS and CSF OCBs. Select-6 assessment was available for all participants, whereas OCB data were available for a subset based on prior clinical evaluation.ResultsOf 420 participants enrolled, 191 (45%) presented with either nonspecific symptoms (n = 166) or incidental imaging findings (n = 25). The mean age was 42 years, and 78% were female. Thirty-six (19%) met the 2024 McDonald criteria at baseline, including 28 (17%) in the nonspecific symptom cohort and 8 (32%) in the incidental imaging cohort. Among 51 participants meeting 2017 DIS, 22 (43%) were Select-6 positive, 17 (33%) had positive OCBs, and 4 (8%) met 2017 DIT. Nonspecific sensory symptoms, visual disturbances, and subacute cognitive decline were most associated with a diagnosis of MS.DiscussionApplication of the 2024 McDonald criteria identified nearly one-fifth of individuals without typical presentations as meeting diagnostic criteria for MS at baseline. Biomarker incorporation-particularly the CVS-accounted for a substantial proportion of diagnostic yield. Interpretation is limited by availability of CSF data and absence of longitudinal follow-up.

Background: Compared to the potent efficacy of autologous hematopoietic cell transplantation (AutoHCT) on multiple sclerosis (MS) lesion activity, benefit on disability progression is less clear. Paramagnetic rim lesions (PRLs) are imaging biomarkers associated with progression.Objectives: Evaluate effect of AutoHCT on PRLs using 7T magnetic resonance imaging (MRI).Methods: A single rater evaluated PRLs before/after AutoHCT on 7T MRI at an MS referral center.Results: Seven participants were included with mean age 38.9 years and median disease duration 9 years. Median PRL count pre-transplantation was 2. Post-AutoHCT (median 15 months in 5 participants) none of the PRLs resolved.Conclusion: These results provide low-level evidence that PRLs do not resolve following AutoHCT.

BACKGROUND:Posterior reversible encephalopathy syndrome (PRES) and reversible cerebral vasoconstriction syndrome (RCVS) are cerebrovascular dysregulation syndromes, and an overlapping spectrum may exist. We aimed to assess the frequency and features of PRES and RCVS overlaps. METHODS:We retrospectively included patients diagnosed with PRES or RCVS from our tertiary center during 2008-2018. Subgroups of PRES with vasoconstriction and RCVS with resolving vasogenic brain edema were defined as the overlap group. Inter-group comparisons were performed for clinical, radiological, and laboratory features. RESULTS:Of 360 patients (mean age 48 years, 73% female), 242 were diagnosed with PRES, 83 with RCVS, and 35 patients had overlapping features. In the overlap group, ischemic infarcts (31%) and intraparenchymal hemorrhage (34%) were more frequent than in isolated RCVS (15%, p = 0.03, and 11%, p < 0.01) or isolated PRES (12% and 13%, p-values <0.01). Subarachnoid hemorrhage was more common in overlap (17%) than in isolated PRES (5%, p = 0.006), but similar to isolated RCVS (25%, p = 0.337). Distal vascular segments were most involved (>50%) by vasoconstriction in RCVS and overlap cases. Neutrophil-to-lymphocyte ratio was higher in overlap (7.4) than in RCVS (2.7, p = 0.02), but similar to PRES (7.4). Most patients had a favorable discharge disposition (home or acute rehabilitation). There was one death (1%) with RCVS, one with overlap (3%), and 17 (7%) with PRES. CONCLUSIONS:Although more distinct clinical and radiological features exist in typical RCVS and PRES, an overlapping presentation is not uncommon. Overlap may be associated with more ischemic and hemorrhagic complications, but mostly resembles the parent condition.

BACKGROUND:Fatigue is commonly experienced amongst persons with multiple sclerosis (PwMS), decreasing quality of life and increasing the economic burden of care. Several pharmacologic treatments have been studied in randomized clinical trials (RCTs) for fatigue in MS, with conflicting results. METHODS:We performed a systematic search for RCTs through PubMed and CENTRAL to determine the efficacy and tolerability of amantadine, modafinil, methylphenidate, and 4-aminopyridine as treatments for fatigue in adults with MS in comparison to placebo or other interventions. Outcomes were fatigue severity as measured by Fatigue Severity Scale (FSS), Modified Fatigue Impact Scale (MFIS), or Visual Analog Scale, and frequency of discontinuation due to side effects. Forest plots were generated (random effects model), standardized mean differences (SMD) were used for continuous outcomes, and risk ratio was calculated for the dichotomous outcome. The risk of bias was assessed with the Cochrane risk-of-bias tool, and GRADEpro GDT was used to summarize the evidence. RESULTS:Of 259 screened studies, 16 met the inclusion criteria for this review. SMD showed a change of -0.26 (95 % CI, -0.54, 0.01) in the direction of medications, representing a decrease of 0.29 in FSS or 3.90 in MFIS (minimally important difference is 0.45 for FSS and 4 for MFIS). The pooled risk ratio for discontinuation was 2.11 (95 % CI, 1.19, 3.77), favoring controls. Most studies were without substantial risk of bias, but the certainty of evidence was low. CONCLUSION:The studied medications have minimal to no efficacy and an uncertain clinical significance in reducing fatigue in PwMS.

Artificial intelligence (AI) in multiple sclerosis (MS) is an area of growing importance of growing importance. We review the historical context, current applications, and future prospects of AI and machine learning (ML) in MS. The review highlights AI's potential to address critical challenges in MS management, including early and accurate diagnosis, individualized treatment strategies, prognostication, and efficient patient monitoring. By leveraging large datasets and high-dimensional data, AI promises profound insights and augments clinical decision-making processes. Additionally, the manuscript covers potential limitations and challenges facing AI use in MS clinical practice and research.

AimsTo describe the 12-month effectiveness, persistence, tolerability, and safety of ofatumumab (OMB), a highly effective disease-modifying therapy (DMT) for relapsing multiple sclerosis (MS), in a real-world MS population.Patients & methodsElectronic medical records of patients starting OMB from October 2020 to August 2022 at two comprehensive MS centers were reviewed. Demographics and disease characteristics and 6- and 12-month clinical, patient-reported, and radiologic outcome measures were analyzed.ResultsA total of 175 patients started OMB with mean age 44.9 (SD 10.4) and disease duration 13.6 (SD 9.6) years. The cohort was 74% female, included 81% White and 13% Black American patients, and consisted of 80% relapsing-remitting MS or clinically isolated syndrome. Most (87%) had prior DMT exposure with 38% switching from high efficacy DMT. Over 12 months, 9.7% discontinued OMB (mean 117 days, SD 99.2), with tolerability issues being the most common reason. Thirty-nine (22%) had relapses in the year before starting OMB. By 12 months, only 1 relapse had occurred after approximately 4 months post-treatment initiation.DiscussionThis real-world study demonstrated that OMB is highly effective with robust persistence and good safety and tolerability by 12-month follow-up. Further analyses are planned to examine longer-term outcomes.

OBJECTIVES:To examine volumetric magnetic resonance imaging (vMRI) in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), compared to multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and healthy controls (HC). METHODS:Standardized vMRI in MOGAD were compared to age, sex, and disease duration matched MS (5:1), and non-matched NMOSD and HC, in mixed linear models with time and group interactions. Disability assessments included; patient determined disease steps (PDDS), manual dexterity (MDT), walking speed (WST), processing speed (PST), and contrast sensitivity tests (CST). Correlations between vMRI and disability in MOGAD were examined. RESULTS:A total of 293 patients were included; 32 MOGAD, 160 MS, 49 NMOSD, and 52 HC. MOGAD had a faster rate of volume loss in all brain regions compared to HC (p < 0.05). At baseline, MOGAD had preserved thalamic (0.000507, p = 0.005), caudate (0.000287, p = 0.004), and putamen (0.000341, p = 0.007) fractions than MS. Longitudinally, MOGAD had increased lateral ventricle fraction (LVF) (-0.000645, p = 0.032), but less hippocampal (0.000031, p = 0.044) and upper cervical cord area (UCCA) loss (1.482887, p = 0.005), compared to NMOSD. MOGAD had increased LVF (0.00529, p < 0.001), but less UCCA loss (0.538656, p = 0.042) longitudinally compared to MS. Among MOGAD, UCCA was associated with PDDS (-0.72, p = 0.004) and CST (0.60, p = 0.014). Whole brain fraction (WBF) was associated with PDDS (-0.66, p = 0.01) and PST (0.52, p = 0.019). LVF was associated with PDDS (0.78, p < 0.001). INTERPRETATION:MOGAD showed longitudinal brain volume loss compared to HC. Deep gray matter was relatively preserved compared to MS, while MS and NMOSD had greater UCCA loss, indicating regional differences in atrophy. Despite less overall atrophy, volume loss in MOGAD was associated with disability. ANN NEUROL 2025;98:1044-1056.

BACKGROUND:Cognitive impairment (CI) in people with MS (pwMS) has complex pathophysiology. Neuropsychological testing (NPT) can be helpful, but interpretation may be challenging for clinicians. Thalamic atrophy (TA) has shown correlation for both neurodegeneration and CI. OBJECTIVE:Leverage machine learning methods to link CI and longitudinal neuroimaging biomarkers. METHODS:Retrospective review of adult pwMS with NPT and ≥2 brain MRIs. Quantitative MRI regional change rates were calculated using mixed effects models. Participants were divided into training and validation cohorts. K-means clustering was done based on first and second NPT principal components (PC1 and PC2). MRI change rates were compared between clusters. RESULTS:112 participants were included (mean age 48 years, 71 % female, 80 % relapsing remitting). Processing speed and memory were the major contributors to PC1. We identified two clusters based on PC1, one with significantly more TA in both training and validation cohorts (p = 0.035; p = 0.002) and similar rates of change in all other quantitative MRI measures. The most important contributors to PC1 included measures of processing speed (SDMT/WAIS Coding) and memory (List Learning/BVMT immediate and delayed recall). CONCLUSIONS:This clustering method identified a profile of NPT results strongly linked to and possibly driven by TA. These results confirm validity of previously established findings using more advanced analyses in addition to offering novel insights into NPT dimensionality reduction.

BACKGROUND: Cognitive impairment (CI) is common in multiple sclerosis (MS). Processing speed (PS) is often affected, making it an ideal target for monitoring CI. This study aims to evaluate the association between disease-modifying therapy (DMT) use and intensity and longitudinal changes in Processing Speed Test (PST) scores for individuals with MS. METHODS: A retrospective analysis of individual PST scores at a single MS center was conducted. Individuals with 2 or more PST assessments were included. Scores on the PST were compared longitudinally between those who had been on a DMT for 2 or more years and those who had been off a DMT for 2 or more years and between those on high-efficacy DMTs and those on low-/moderate-efficacy DMTs. A linear regression model was approximated to evaluate the rate of cognitive change over time. A propensity score adjustment was conducted using a multivariable logistic regression. RESULTS: The cohort was 642 individuals, 539 on DMT and 103 off DMT. Median age and disease duration was 49.7 (IQR 42.4-57.9) and 16.6 years (IQR 9.3-23.0) in the DMT group, and 58.9 (IQR 52.2-65.3) and 20.0 years (IQR 14.1-31.4) in the non-DMT group. Both cohorts were predominantly female (75% DMT, 79.6% non-DMT), with a mean of 4 assessments (IQR 3-5), and an average monitoring duration of 1.9 years (1.2-2.4) in the DMT group, and 1.8 years (1.4-2.4) in the non-DMT group. After adjusting for multiple factors, DMT status and intensity were not found to be significant predictors of longitudinal PST change. CONCLUSIONS: Neither DMT status nor intensity was a significant predictor of cognitive processing speed over a period of approximately 2 years. Future prospective studies are needed to further support these findings.

Background and Objectives Longitudinal outcome studies in leucine-rich glioma inactivated-1 (LGI-1) immunoglobulin G (IgG) autoimmune encephalitis (AE) are needed to inform clinical management and prognostication. This study aims to evaluate longitudinal predictors of disability and disease severity in LGI-1-IgG AE. Methods This retrospective observational study of patients with LGI-1-IgG AE was conducted between 2013-2022. Disability and disease severity were defined by scores on the modified Rankin Scale (mRS) and the clinical assessment scale in AE (CASE), respectively. Demographic variables, clinical/paraclinical data, brain MRI, and Montreal Cognitive Assessment (MOCA) scores were examined as predictors of mRS and CASE scores in logistic and linear regression models, respectively. Results Thirty patients (60% male, median age = 68.5; interquartile range (IQR) = 63.0–75.0) were included, with a median follow-up time of 19.1 months (IQR = 5.3–47.1) The majority developed seizures (29, [97%]) and/or cognitive impairment (30, [100%]) and received acute (27, [90%]) and maintenance (23 [77%]) immunotherapy. The median initial MOCA was 23/30 (IQR = 21.0–25.0). Baseline mRS (median = 2.0, IQR = 2.0–3.0) and CASE (mean = 4.3, SD = 3.7) correlated with one another (r = 0.58, p < 0.001) and with initial MOCA score (mRS r = –0.60, p = 0.012; CASE r = –0.56, p = 0.021) After 12 months from symptom onset, mRS (OR = 0.88, [95% CI = 0.82–0.94], p < 0.001) and CASE (β = −0.03, [SE = 0.01], p < 0.001) improved significantly. Lower initial MOCA score (OR = 0.68, 95% CI = 0.47–0.98, p = 0.041) and temporal lobe(s) T2 hyperintensity (OR = 16.50, 95% CI = 2.29–119.16, p = 0.006) were associated with higher mRS longitudinally. At last follow-up, most patients had persistent memory dysfunction (25, [83%]) while few had ongoing seizure activity (3, [10%]). Discussion Overall, there was a high degree of correlation between mRS and CASE scores in patients with LGI-1-IgG AE, with both scores improving significantly after 12 months. Memory dysfunction and psychiatric disturbance were the most prevalent longitudinal symptoms. Cognitive impairment and temporal lobe T2 hyperintensity at baseline were both associated with greater disability at long-term follow-up, underscoring these as important determinants of disability outcomes in LGI-1-IgG AE.

Background Diagnosis of multiple sclerosis (MS) frequently relies on MRI dissemination in time (DIT) and space (DIS), as codified in 2017 McDonald criteria (McD 2017). The central vein sign (CVS) is a proposed MS diagnostic biomarker, but its optimal incorporation into McD 2017 has not been extensively studied. Objective Evaluate the diagnostic performance of several methods incorporating CVS into McD 2017 radiological DIS criteria. Methods Data were obtained from the CAVS-MS Pilot, a cross-sectional, international multi-center study conducted by the North American Imaging in MS Cooperative (NAIMS) that recruited adults referred for suspicion/diagnosis of demyelinating disease. Diagnostic performance of methods incorporating CVS into McD 2017 radiological DIS were evaluated by comparing sensitivity, specificity, and accuracy. Results 78 participants (37 MS, 41 others) were included. For MS diagnosis, sensitivity, specificity, and accuracy of DIS based on brain imaging (DIS-B) alone was 92%, 69%, and 78%. Requiring at least one lesion with CVS in any brain location in addition to DIS-B increased specificity (sensitivity 92%, specificity 81%, accuracy 86%). Presence of 2 deep white matter lesions with CVS as an additional topography for DIS-B had higher sensitivity (sensitivity 97%, specificity 59%, accuracy 77%). Conclusions Incorporation of CVS in McD 2017 DIS criteria can be used to improve diagnostic accuracy. Validation in additional prospective studies is needed.

Background Effective communication between providers and people with multiple sclerosis (pwMS) is essential. Objectives To determine the level of concordance between provider- and pwMS-reported disease course. Methods Patient encounters from December 2015 through April 2020 were retrospectively reviewed for MS disease course self-reported by the patient and separately documented by the provider at each visit. The proportion of agreement was compared across disease course Cohen's kappa, and subsequently stratified by sex, race, and level education. Results Across 1335 encounters, the proportion of disease course agreement varied. Compared with RRMS, there was statistically significant difference across all other disease courses. Overall concordance between providers and pwMS was 64 % with a Cohen's kappa of 0.312. Concordance was higher amongst female patients, black patients, and patients with a higher level of education (>14 years). Conclusion Overall agreement on MS disease course amongst patients and providers was suboptimal. A concerted effort to understand these discrepancies is needed.

BACKGROUND:The diagnosis of multiple sclerosis (MS) relies heavily on neuroimaging with magnetic resonance imaging (MRI) and exclusion of mimics. This can be a challenging task due to radiological overlap in several disorders and may require ancillary testing or longitudinal follow up. One of the most common radiological MS mimickers is non-specific white matter disease (NSWMD). We aimed to develop and evaluate models leveraging machine learning algorithms to help distinguish MS and NSWMD.METHODS:All adult patients who underwent MRI brain using a demyelinating protocol with available electronic medical records between 2015 and 2019 at Cleveland Clinic affiliated facilities were included. Diagnosis of MS and NSWMD were assessed from clinical documentation. Those with a diagnosis of MS and NSWMD were matched using total T2 lesion volume (T2LV) and used to train models with logistic regression and convolutional neural networks (CNN). Performance metrices were reported for each model.RESULTS:A total of 250 NSWMD MRI scans were identified, and 250 unique MS MRI scans were matched on T2LV. Cross validated logistic regression model was able to use 20 variables (including spinal cord area, regional volumes, and fractions) to predict MS compared to NSWMD with 68.0% accuracy while the CNN model was able to classify MS compared to NSWMD in two independent validation and testing cohorts with 77% and 78% accuracy on average.CONCLUSION:Automated methods can be used to differentiate MS compared to NSWMD. These methods can be used to supplement currently available diagnostic tools for patients being evaluated for MS.

Currently, there are four monoclonal antibodies (mAbs) that target the cluster of differentiation (CD) 20 receptor available to treat multiple sclerosis (MS): rituximab, ocrelizumab, ofatumumab, and ublituximab. B-cell depletion therapy has changed the therapeutic landscape of MS through robust efficacy on clinical manifestations and MRI lesion activity, and the currently available anti-CD20 mAb therapies for use in MS are a cornerstone of highly effective disease-modifying treatment. Ocrelizumab is currently the only therapy with regulatory approval for primary progressive MS. There are currently few data regarding the relative efficacy of these therapies, though several clinical trials are ongoing. Safety concerns applicable to this class of therapeutics relate primarily to immunogenicity and mechanism of action, and include infusion-related or injection-related reactions, development of hypogammaglobulinemia (leading to increased infection and malignancy risk), and decreased vaccine response. Exploration of alternative dose/dosing schedules might be an effective strategy for mitigating these risks. Future development of biosimilar medications might make these therapies more readily available. Although anti-CD20 mAb therapies have led to significant improvements in disease outcomes, CNS-penetrant therapies are still needed to more effectively address the compartmentalized inflammation thought to play an important role in disability progression.