Multiple sclerosis and related disorders最新文献

{"title":"Psychometric validation of PROMIS-Fatigue-MS-8a and MSIS-29v2 questionnaires in relapsing multiple sclerosis participants enrolled in a phase 2 trial of frexalimab","authors":"Patrick Vermersch ,&nbsp;Lita Araujo ,&nbsp;Samuel Gourlain ,&nbsp;Natalia Hakimi-Hawken ,&nbsp;Stephane Saubadu ,&nbsp;Philippe Truffinet ,&nbsp;Benoit Arnould ,&nbsp;Jerome Msihid","doi":"10.1016/j.msard.2026.107090","DOIUrl":"10.1016/j.msard.2026.107090","url":null,"abstract":"<div><h3>Background</h3><div>There are limited psychometric studies conducted using the Patient-Reported Outcomes Measurement Information System Adult Short Form-Fatigue-Multiple Sclerosis 8a (PROMIS-Fatigue-MS-8a) and Multiple Sclerosis Impact Scale-29 version 2 (MSIS-29v2) questionnaires.</div></div><div><h3>Methods</h3><div>Data were collected from a phase 2 trial (NCT04879628) investigating frexalimab in adults with relapsing multiple sclerosis (RMS). Reliability, convergent validity, construct validity, and sensitivity to change were assessed on PROMIS-Fatigue-MS-8a and MSIS-29v2 using Cronbach’s alpha coefficient, intraclass correlation coefficient, Spearman’s or polyserial correlation coefficients, analysis of variance, and analysis of covariance, respectively. Analyses were conducted using baseline and Week 12 data from pooled treatment arms.</div></div><div><h3>Results</h3><div>Item-to-item correlations were acceptable (0.4–0.9) for most of the items for both patient-reported outcomes (PROs) at baseline and Week 12. Internal consistency was excellent (Cronbach’s alpha &gt;0.90) for both PROs at baseline and Week 12. Additionally, good test–retest reliability was observed for PROMIS-Fatigue-MS-8a and the physical and psychological domains of MSIS-29v2. Convergent validity was supported by high correlations (<em>r</em>&gt;0.50) between the PROMIS-Fatigue-MS-8a T-score and the MSIS-29v2 and the Patient Global Impression of Severity (PGIS)-Fatigue at baseline and Week 12. Construct validity was supported by significant differences between groups defined by the PGIS-Fatigue scores at baseline and Week 12 for both PROs (<em>p</em>&lt;0.0001). Sensitivity to change was demonstrated by statistically significant differences in the mean change from baseline at Week 12 among groups defined by the PGIS-Fatigue and the Patient Global Impression of Change-Fatigue.</div></div><div><h3>Conclusions</h3><div>PROMIS-Fatigue-MS-8a and MSIS-29v2 are valid and reliable measures for evaluating treatment benefits in clinical trials of RMS.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107090"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147355807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-invasive Assessment of Glymphatic System Function in Patients with Anti-LGI1 Encephalitis","authors":"Ziyao Liu ,&nbsp;Lizhang Han ,&nbsp;Ruiqi Li ,&nbsp;Houyuan Zhu ,&nbsp;Jianping Qiao ,&nbsp;Jiaxiang Xin ,&nbsp;Dandan Zhang ,&nbsp;Linlin Zhai ,&nbsp;Xinjuan Jin ,&nbsp;Jingli Shan ,&nbsp;Shengjun Wang ,&nbsp;Anning Li","doi":"10.1016/j.msard.2026.107053","DOIUrl":"10.1016/j.msard.2026.107053","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Cognitive impairment is a core deficit in anti-LGI1 encephalitis, yet its underlying mechanisms remain incompletely understood. The glymphatic system (GS), a brain waste clearance pathway, is implicated in cognitive dysfunction in other neuroinflammatory conditions. However, its role in anti-LGI1 encephalitis is unknown. We hypothesized that GS dysfunction is a key mechanism contributing to cognitive deficits in this disease. This study aimed to investigate GS function using diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) and other MRI indices, and evaluate its association with hippocampal/amygdala volumes and cognition.</div></div><div><h3>Materials and Methods</h3><div>This prospective study enrolled 42 healthy controls (HCs) and 40 patients with a confirmed diagnosis of anti-LGI1 encephalitis who underwent brain MRI and neurocognitive assessment. Clinical and neuropsychological data were collected, including the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Modified Rankin Scale (mRS), and Clinical Assessment Scale for Autoimmune Encephalitis (CASE). Patients were stratified into three cognitive subgroups based on MoCA scores: LGI1-NCI (no cognitive impairment, MoCA ≥ 26), LGI1-MCI (mild cognitive impairment, MoCA 18–25), and LGI1-SCI (moderate-to-severe cognitive impairment, MoCA &lt; 18). Imaging-derived biomarkers included the DTI-ALPS index, hippocampal and amygdala volumes extracted from 3D T1-weighted images, perivascular space (PVS) volume fraction, and free water fraction with in white matter (FW-WM).</div></div><div><h3>Results</h3><div>Key imaging biomarkers showed significant differences between patients and HCs. Specifically, the DTI-ALPS index was significantly decreased in patients (1.483 vs. 1.671, p_FDR= 0.011), whereas the FW-WM was significantly increased (0.210 vs. 0.174, p_FDR=0.007). Subgroup analysis demonstrated a progressive decline in the DTI-ALPS index (LGI1-SCI: 1.3813 vs. HCs: 1.6706, p_FDR=0.004) and concomitant elevation in FW-WM (LGI1-SCI: 0.2258 vs. HCs: 0.1743, p_FDR=0.001) associated with increasing cognitive impairment severity. Unilateral hippocampal atrophy was also observed, with a significantly reduced volumes in the left hippocampus (2.942 vs. 3.216 cm³, p_FDR=0.049).</div></div><div><h3>Conclusion</h3><div>We observed glymphatic dysfunction and left hippocampal atrophy in anti-LGI1 encephalitis, with both features showing trends of greater severity in patients with more pronounced cognitive impairment. Longitudinal observations indicate that recovery of these pathological features lags behind clinical improvement, suggesting independent underlying mechanisms.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107053"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147372938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk of postpartum disease activity with subcutaneous versus intravenous Natalizumab in pregnant women with multiple sclerosis","authors":"Vito AG Ricigliano ,&nbsp;Doriana Landi ,&nbsp;Marine Boudot de la Motte ,&nbsp;Jonathan Ciron ,&nbsp;Bertrand Bourre ,&nbsp;Olivier Casez ,&nbsp;Silvia Bartolomeo ,&nbsp;Giangaetano D'Aleo ,&nbsp;Roberta Fantozzi ,&nbsp;Matteo Foschi ,&nbsp;Francesca Napoli ,&nbsp;Caroline Papeix ,&nbsp;Girolama Alessandra Marfia ,&nbsp;Elisabeth Maillart","doi":"10.1016/j.msard.2026.107086","DOIUrl":"10.1016/j.msard.2026.107086","url":null,"abstract":"<div><h3>Background</h3><div>Intravenous (IV) Natalizumab (NTZ) extended-interval dosing (EID) in women with multiple sclerosis (WwMS) is safe and effective in controlling disease activity during pregnancy. Recently, a subcutaneous (SC) form of the drug has become available.</div></div><div><h3>Objectives</h3><div>To assess clinical/radiological relapses in postpartum comparing IV and SC NTZ EID in two groups of pregnant WwMS.</div></div><div><h3>Methods</h3><div>We retrospectively collected data on pregnancies across French and Italian MS centers. We assessed clinical/radiological activity in postpartum, accounting for the number of administrations during pregnancy and the duration of NTZ washout. Fisher’s exact test, followed by multivariable logistic regression to adjust for confounders, were used to compare outcomes by administration route. Group differences in the odds of disease activity were expressed as odds ratios (OR).</div></div><div><h3>Results</h3><div>56 pregnancies were identified (35IV, 21SC). Relapses were rare and not different between groups (p=0.88). Postpartum radiological activity was observed in 10/21 WwMS with SC NTZ (47.6%), versus 5/35 with IV NTZ (14,3%) (p=0.012; OR=5.32[CI:1.41-20.06]). Notably, 50% of all reactivations with SC NTZ occurred with washout between 10 and 12 weeks.</div></div><div><h3>Conclusions</h3><div>Our study suggests a higher risk of postpartum radiological activity in pregnant WmMS treated with SC NTZ EID, prompting for adaptation of the administration schedule to control disease reactivation.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107086"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147321812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Randomized controlled trial of a remotely-delivered exercise training program in older adults with multiple sclerosis: Secondary effects on cognition, symptoms, and quality of life","authors":"Peixuan Zheng ,&nbsp;Sydney R. DeJonge ,&nbsp;Noah G. DuBose ,&nbsp;Ariel Kidwell-Chandler ,&nbsp;Trevor B. Martin ,&nbsp;Trinh L.T. Huynh ,&nbsp;Robert W. Motl","doi":"10.1016/j.msard.2026.107105","DOIUrl":"10.1016/j.msard.2026.107105","url":null,"abstract":"<div><h3>Background</h3><div>Older adults with multiple sclerosis (MS) experience co-occurring effects of aging and disease progression, resulting in worsening cognition, symptoms, and quality of life (QOL). There is limited research examining approaches for improving those outcomes in older adults with MS.</div></div><div><h3>Objectives</h3><div>We examined the efficacy of a 16-week home-based exercise training program for improving secondary study outcomes of cognition, symptoms, and QOL in older adults with MS.</div></div><div><h3>Methods</h3><div>This phase-Ib, randomized controlled trial (RCT) included 51 participants (60.5±6.6 years, 78% females) who were randomized into exercise training (aerobic and resistance) or active control (stretching) conditions. Participants completed laboratory assessments before and after the 16-week programs. Cognitive function was measured using the NIH Toolbox Cognitive Battery. Symptoms of fatigue, depression, anxiety, and pain were assessed using the Fatigue Severity Scale, Modified Fatigue Impact Scale, Hospital Anxiety and Depression Scale, and Short-form McGill Pain Questionnaire, respectively. QOL was measured by the 29-item Multiple Sclerosis Impact Scale and the 36-Item Short Form Health Survey.</div></div><div><h3>Results</h3><div>Forty-one participants (80.4 %) completed the conditions, with outcome data obtained from 20 exercise and 16 control participants. There were statistically significant improvements in executive function, processing speed, fatigue, and health-related QOL in the exercise group (<em>p</em> &lt; 0.05, <em>d</em> = 0.48–0.66). No significant changes were observed in the control group (<em>p</em>&gt;0.05).</div></div><div><h3>Conclusions</h3><div>We provide preliminary evidence on the benefits of exercise training for improving cognition, reducing fatigue impact, and enhancing QOL in older adults with MS who had moderate disability.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107105"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147355940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of laughter yoga on fatigue, sleep quality and psychological well-being in people with multiple sclerosis: A randomized controlled trial","authors":"Nurgül Kaplan ,&nbsp;Mehtap Tan ,&nbsp;Dürdane Aksoy","doi":"10.1016/j.msard.2026.107098","DOIUrl":"10.1016/j.msard.2026.107098","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Symptoms such as fatigue, sleep disturbances, and impaired psychological well-being are common in individuals Multiple Sclerosis (MS). However, studies on the use of laughter yoga, a non-invasive intervention method, are very limited in the literature. The aim of this study was to evaluate the effects of laughter yoga on fatigue, sleep quality and psychological well-being in individuals with MS.</div></div><div><h3>Materials and methods</h3><div>In this randomized controlled trial, 42 people with MS were randomly assigned to intervention or control group. The intervention group received a total of 12 sessions of laughter yoga. Descriptive Information Form, Fatigue Severity Scale (FSS), Pittsburgh Sleep Quality Index (PSQI) and Psychological Well-Being Scale (PWBS) were used to collect data.</div></div><div><h3>Results</h3><div>Laughter yoga was associated with improvements in fatigue and sleep outcomes. Fatigue severity decreased substantially in the intervention group (Cohen’s d = 2.785), with no meaningful change observed in the control group. Sleep quality improved in the intervention group, as indicated by reduced Pittsburgh Sleep Quality Index scores (p &lt; 0.001, d = 2.921). Psychological well-being increased within the intervention group (d = -1.505); however, the between-group effect at post-test was small (d = 0.485).</div></div><div><h3>Conclusion</h3><div>Laughter yoga showed statistically significant results in terms of decreasing fatigue level, increasing sleep quality and psychological well-being in individuals with MS. The findings suggest that laughter yoga is a low-cost and effective complementary psycho-social intervention that can be used in clinical settings within the scope of nursing practice. This intervention offers an evidence-based approach that can be integrated into nursing care to manage fatigue and sleep problems and improve psychological well-being in individuals with MS. For the generalizability of the effects of laughter yoga, studies with larger samples are needed.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107098"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147326771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Voice analysis as a digital biomarker: A machine learning approach for automated multiple sclerosis classification","authors":"Jonathan Delgado Hernández ,&nbsp;Moisés Betancort Montesinos ,&nbsp;Tatiana Romero Arias ,&nbsp;Miguel Ángel Hernández Pérez","doi":"10.1016/j.msard.2026.107109","DOIUrl":"10.1016/j.msard.2026.107109","url":null,"abstract":"<div><h3>Background/Objectives</h3><div>Voice analysis is a non-invasive tool that can capture subtle motor impairments in Multiple Sclerosis (MS). The objective of this study was to develop and validate a machine learning (ML) framework for the automated classification of MS through acoustic voice analysis.</div></div><div><h3>Methods</h3><div>A cohort of 300 gender-balanced participants (200 with MS and 100 healthy controls) provided sustained vocal recordings. Fifteen acoustic features were extracted. An elastic network model first identified the most relevant parameters from the development cohort (n = 200), which were then used to train five supervised ML classifiers. During the variable selection and ML model training phase, the sample was divided into an 80/20 split and cross-validation was used to minimize overfitting. The best-performing model was subsequently validated in an independent, unknown clinical cohort (n = 100).</div></div><div><h3>Results</h3><div>The Random Forest model demonstrated robust performance, which was confirmed in the independent validation (ROC AUC = 0.85 [95% CI=0.76-0.93] and balanced accuracy = 0.80), showing strong discriminative ability independent of sample prevalence.</div></div><div><h3>Conclusion</h3><div>Voice analysis combined with ML presents a non-invasive, low-cost, and effective method for MS discrimination, offering significant potential as a classification support tool.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107109"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147355925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chronic lesion expansion as an imaging biomarker in multiple sclerosis","authors":"Michael T G Hayes ,&nbsp;Heidi N Beadnall ,&nbsp;Daniel Merlo ,&nbsp;Mastura Monif ,&nbsp;Samuel Klistorner ,&nbsp;Chao Zhu ,&nbsp;Anneke van der Walt ,&nbsp;Helmut Butzkueven","doi":"10.1016/j.msard.2026.107093","DOIUrl":"10.1016/j.msard.2026.107093","url":null,"abstract":"<div><div>The pathophysiological processes that drive disability progression in multiple sclerosis (MS) are not adequately captured by clinically available imaging biomarkers. Slowly expanding lesions (SELs) are a novel magnetic resonance imaging (MRI) biomarker proposed to reflect histopathologically defined chronic active lesions, which are associated with disease progression. SELs are identified through complex MRI analysis pipelines that measure volume changes in chronic MS lesions across serial MRI scans. This review provides a comprehensive overview of SELs, covering their proposed histopathological correlates, associations with clinical outcomes and response to disease-modifying therapies (DMTs). A distinguishing aim of this review is to provide the reader with a clear understanding of different SEL analysis techniques, particularly the two most established automated approaches, including their respective strengths and limitations. Each technique is compatible with conventional clinical MRI sequences, making clinical translation feasible. Current DMTs have modest effects on SELs, paralleling their limited efficacy in progressive MS. SELs may become a key outcome measure in clinical trials of DMTs for progressive MS. However, further research is needed to ascertain the optimal parameters for identifying clinically meaningful chronic lesion expansion with each analysis technique, and to clarify which SEL measures are most strongly associated with disability progression.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107093"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147317776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Poincaré feature-based classification of electroencephalography signals for multiple sclerosis diagnosis","authors":"Umut Aslan,&nbsp;Mehmet Feyzi Akşahin","doi":"10.1016/j.msard.2026.107092","DOIUrl":"10.1016/j.msard.2026.107092","url":null,"abstract":"<div><h3>Background</h3><div>As one of the most widespread neurodegenerative disorders, Multiple Sclerosis (MS) is a progressive neuroinflammatory disorder affecting millions of individuals worldwide. Although magnetic resonance imaging (MRI) techniques are commonly employed for diagnosis, there is an increasing emphasis on electroencephalogram (EEG) signal processing to diagnose neurodegenerative disorders.</div></div><div><h3>Methods</h3><div>This study explores the use of Poincaré plot–derived features from EEG signals to differentiate MS patients from healthy individuals. EEG recordings from 50 subjects (25 MS, 25 Healthy controls) have been analyzed. EEG data were segmented into epochs, and four quantitative Poincaré features were extracted from each segment. These features were used as inputs to various classifiers, including traditional machine learning methods, k-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), and ensemble models, and deep learning architectures such as Multilayer Perceptron (MLP), Convolutional Neural Network combined with Long Short-Term Memory (CNN+LSTM), and LSTM combined with Gated Recurrent Units (LSTM+GRU). Additionally, sub-frequency bands of EEG signals were analyzed separately to evaluate the discriminative potential of each band.</div></div><div><h3>Results</h3><div>The results demonstrated that Poincaré-based features effectively distinguished MS patients from healthy individuals. This yielded accuracies, sensitivities, and specificities of 99.8%, 100%, and 99.7%, respectively. Moreover, classification based on the Beta band consistently exhibited the highest discriminative power in differentiating MS patients. However, given the limited sample size, these results should be interpreted as preliminary and warrant further validation.</div></div><div><h3>Conclusions</h3><div>The results indicate that EEG-based Poincaré feature analysis offers a promising, low-cost, and noninvasive approach for assisting in MS diagnosis. While the observed classification performance is encouraging, larger and more diverse datasets, along with rigorous validation strategies, are required to confirm the robustness and clinical applicability of the proposed approach. Integrating this method with clinical workflows may enhance diagnostic accuracy and provide new insights into MS-related alterations in brain dynamics.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107092"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147308246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct microstructural white matter alterations in demyelinating diseases: Insights from myelin- and axon-sensitive MRI","authors":"Yasunobu Hoshino ,&nbsp;Akifumi Hagiwara ,&nbsp;Yuji Tomizawa ,&nbsp;Naohisa Hara ,&nbsp;Moto Nakaya ,&nbsp;Junko Kikuta ,&nbsp;Satoru Kamio ,&nbsp;Hanna Okada ,&nbsp;Koji Kamagata ,&nbsp;Shigeki Aoki ,&nbsp;Nobutaka Hattori","doi":"10.1016/j.msard.2026.107078","DOIUrl":"10.1016/j.msard.2026.107078","url":null,"abstract":"<div><h3>Objectives</h3><div>We aimed to compare microstructural white matter alterations in multiple sclerosis (MS), anti–aquaporin-4 antibody-positive neuromyelitis optica spectrum disorders (AQP4-NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) using advanced quantitative MRI.</div></div><div><h3>Methods</h3><div>This retrospective study included 84 participants (24 MS, 18 AQP4-NMOSD, 20 MOGAD, and 22 healthy controls). Quantitative MR relaxometry and multi-shell diffusion-weighted imaging were acquired at 3 T to derive myelin volume fraction (MVF), axonal volume fraction, g-ratio, and diffusion tensor metrics. Normal-appearing white matter (NAWM) was analyzed in all patients, and plaque-based analyses were performed in patients with focal white matter lesions (20 MS, 8 AQP4-NMOSD, 8 MOGAD). Diagnostic performance was assessed using receiver operating characteristic (ROC) analyses.</div></div><div><h3>Results</h3><div>In NAWM, MS showed significantly lower fractional anisotropy than MOGAD or controls (P &lt; 0.05), and AQP4-NMOSD exhibited lower MVF than MOGAD (P &lt; 0.05). Among patients with lesions, plaques in MS had significantly lower MVF and higher g-ratio than those in AQP4-NMOSD (P &lt; 0.0001) and MOGAD (P &lt; 0.05). Plaques in AQP4-NMOSD showed a lower g-ratio than MOGAD (P &lt; 0.01). Univariate ROC analyses revealed that plaque g-ratio distinguished AQP4-NMOSD from MS (AUC 0.92 [95%CI, 0.82–1.00], sensitivity 100.0%, specificity 75.0%) and from MS + MOGAD (AUC 0.88 [0.77–0.99], sensitivity 100.0%, specificity 75.0%). A multivariate model combining NAWM and plaque metrics further improved discrimination (AUC 0.95 [0.88–1.00], sensitivity 75.0%, specificity 95.0%, and AUC 0.91 [0.81–1.00], sensitivity 50.0%, specificity 92.9%).</div></div><div><h3>Conclusion</h3><div>Quantitative MRI metrics—especially MVF and g-ratio—demonstrate distinct microstructural profiles among MS, AQP4-NMOSD, and MOGAD, enabling improved disease differentiation.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107078"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147308259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered network recruitment in multiple sclerosis patients during resting state","authors":"Annika Lüttjohann ,&nbsp;Saskia Räuber ,&nbsp;Melanie Korsen ,&nbsp;Alice G. Willison ,&nbsp;Saskia Elben ,&nbsp;Christina B. Schroeter ,&nbsp;Tobias Ruck ,&nbsp;Philipp Albrecht ,&nbsp;Marc Pawlitzki ,&nbsp;Albrecht Stroh ,&nbsp;Nico Melzer ,&nbsp;Thomas Budde ,&nbsp;Sven G. Meuth","doi":"10.1016/j.msard.2026.107111","DOIUrl":"10.1016/j.msard.2026.107111","url":null,"abstract":"<div><h3>Background</h3><div>Electroencephalography (EEG) allows a versatile recording of neuronal activity in neurological disorders. Signal analytical techniques like time-frequency analysis (TFA) can uncover latent information in the EEG of patients. Classically, EEG and TFA analysis relies on predefined frequency bands. Cluster-based permutation statistics provides an unbiased statistical comparison of high dimensional neurophysiological data, stabilizing the measured effect size and increasing the probability of uncovering the main effect present.</div></div><div><h3>Methods</h3><div>Resting state surface EEG recordings from 51 Multiple Sclerosis (MS) and 51 control patients were analyzed using TFA and compared by cluster-based permutation statistics. We further correlated results with disease characteristics, retinal nerve fiber layer (RNFL) thickness assessed by optical coherence tomography, evoked potentials (EPs), and neuropsychological data.</div></div><div><h3>Results</h3><div>We detected increased power in the low and high beta frequency bands in MS compared to control patients in a subset of recording sites. Spectral power in the high beta band of resting state EEG recorded at O1 negatively correlated with the RNFL thickness. Furthermore, differences in low and high beta power were dependent on the EP score of MS patients.</div></div><div><h3>Conclusion</h3><div>Our results suggest a more desynchronized EEG activity in MS patients compared to controls, correlating with clinical markers of disease severity. The findings indicate differential brain network recruitment that may be the result of compensatory mechanisms and the basis for clinical impairment in MS.</div></div>","PeriodicalId":18958,"journal":{"name":"Multiple sclerosis and related disorders","volume":"109 ","pages":"Article 107111"},"PeriodicalIF":2.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147378079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}