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The requirement to demonstrate dissemination in time (DIT) in order to diagnose multiple sclerosis (MS) has been enshrined in the literature since earliest efforts to establish diagnostic critera. However, various diagnostic criteria over the years, including the 2017 McDonald criteria, have inconsistently utilized this concept. This Viewpoint contends that current criteria for DIT are inadequate and sometimes inappropriate. It recommends continuing to consider DIT in the diagnosis of MS, but advocates utilizing all available information with high specificity for the disease, including the presence of large numbers of typical lesions, to make the diagnosis. This approach enables early initiation of disease-modifying treatment in situations with a favorable risk-benefit ratio. [ABSTRACT FROM AUTHOR]

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry–academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapseindependent disease pathology [ABSTRACT FROM AUTHOR]

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry–academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.

Background: Multiple sclerosis (MS) is an inflammatory demyelinating disease with neurodegenerative features causing risk for neurologic irreversible disability over time. Examination of normal-appearing white matter (NAWM) changes in MS by proton magnetic resonance spectroscopy (1H-MRS), may detect diffuse white matter pathology that is associated with neurodegeneration., Methods: In this observational study of in total twenty-six patients with MS, starting treatment with dimethyl fumarate (DMF), we measured the absolute concentration of metabolites in periventricular NAWM using 1H-MRS at baseline and after one and three years of treatment. Metabolite concentrations were analyzed both cross-sectionally, in relation to 10 controls and longitudinally in relation to disease activity., Results: Patients with MS had higher concentrations of myo-inositol (mIns) in NAWM at baseline compared with controls (mean 5.98 ± 1.37 (SD) and 4.32 ± 1.16 (SD), p<0.01, independent samples t-test). The disease duration was inversely correlated with concentrations of total N-acetylaspartate and N-acetylaspartylglutamate (tNA) (r = -0.62, p<0.01) in NAWM as well as positively to the ratio of mIns and tNA (r = 0.51, p = 0.03). Metabolite concentrations during one-year (n = 19) and three-years (n = 11) follow-up were generally stable. The dropouts were caused by treatment switch after one year, mainly due to new MRI activity. Cross-sectional analyses showed that there was an inverse correlation between concentrations of tNA and mIns at both baseline and at 1 and 3-years follow-up (r = -0.44 to -0.65, p = 0.04 to 0.004). Metabolite concentrations were stable during 1-year follow-up independently of disease activity., Conclusions: Higher concentrations of the astrogliosis marker mIns in MS compared to controls, the inverse relation between MS disease duration and the neuroaxonal integrity marker tNA, as well as the consistent inverse relation between these two metabolites during follow-up, showed that non-lesional white matter pathology is present in this cohort of MS patients in early disease stages. However, metabolite concentrations during follow-up were generally stable and did not reflect differences in disease activity among patients., Competing Interests: AT, KS, YL and PL report no competing interests. JM has received honoraria for Advisory boards for Sanofi Genzyme and Merck, and lecture honorarium from Merck., (Copyright: © 2024 Tisell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

A few decades ago, women diagnosed with multiple sclerosis were discouraged from becoming pregnant. However, with new knowledge about the disease and treatments, this recommendation has changed, and it is pregnancy after the diagnosis of the disease is no longer contraindicated, with family planning being essential in this process. This review aims to provide a comprehensive overview of the family planning process for people with multiple sclerosis., Competing Interests: The authors have no conflict of interest to declare., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit (https://creativecommons.org/licenses/by/4.0/).)

Background: The long-term disease trajectory of people living with multiple sclerosis (MS) can be improved by initiating efficacious treatment early. More quantitative evidence is needed on factors that affect a patient's risk of disability worsening or possibility of improvement to inform timely treatment decisions., Methods: We developed a multistate model to quantify the influence of demographic, clinical, and imaging factors on disability worsening and disability improvement simultaneously across the disability spectrum as measured by the Expanded Disability Status Scale (EDSS). We used clinical trial data from the Novartis-Oxford MS database including ~130,000 EDSS assessments from ~8000 patients, spanning all MS phenotypes., Results: Higher brain volume was positively associated with disability improvement at all disability levels (hazard ratio (HR) = 1.09-1.19; 95% credible interval (CI) = 1.02-1.27). Higher T2 lesion volume was negatively associated with disability improvement up to EDSS 6 (HR = 0.80-0.89; 95% CI = 0.75-0.94). Older age, time since first symptoms, and the number of relapses in the past year were confirmed as predictors of future disability worsening., Conclusions: Brain damage was identified as the most consistent factor limiting the patient's probability for improvements from the earliest stages and across the whole course of MS. Protecting brain integrity early in MS should have greater weight in clinical decision-making., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: F.H. is currently employee of Exact Sciences, which was not involved in the study. D.L.A. has received personal compensation for serving as a Consultant for Alexion, Biogen, Celgene, Eli Lilly, EMD Serono, Frequency Therapeutics, Genentech, Merck, Novartis, Roche, Sanofi, and Shionogi, and holds an equity interest in NeuroRx. T.E.N received consulting fees from Perspectum Ltd. H.W. has received honoraria for acting as a member of scientific advisory boards for Biogen, Evgen, Genzyme, MedDay Pharmaceuticals, Merck Serono, Novartis, Roche Pharma AG, and Sanofi-Aventis, as well as speaker honoraria and travel support from Alexion, Biogen, Cognomed, F. Hoffmann-La Roche Ltd., Gemeinnützige Hertie-Stiftung, Merck Serono, Novartis, Roche Pharma AG, Genzyme, Teva, and WebMD Global. H.W is acting as a paid consultant for AbbVie, Actelion, Biogen, IGES, Johnson & Johnson, Novartis, Roche, Sanofi-Aventis, and the Swiss Multiple Sclerosis Society. His research is funded by the German Ministry for Education and Research (BMBF), Deutsche Forschungsgemeinschaft (DFG), Else Kröner Fresenius Foundation, Fresenius Foundation, the European Union, Hertie Foundation, NRW Ministry of Education and Research, Interdisciplinary Center for Clinical Studies (IZKF) Muenster and RE Children’s Foundation, Biogen, GlaxoSmithKline GmbH, Roche Pharma AG, and Sanofi-Genzyme. R.A.B. has served as a consultant for Astra Zeneca, Biogen, EMD Serono, Genzyme, Genentech, Novartis, and VielaBio. He receives research support from Biogen, Genentech, and Novartis. D.A.H., A.O., J.Č., G.G., W.S., M-C.M., P.A., and B.C.K. are employees of Novartis. H.G., Y.S., S.G., S.C.P., and T.E.N. are current employees of the Big Data Institute (Oxford, UK) which received funding from Novartis to collaborate on AI in Medicine including the work presented here.

Multiple sclerosis (MS) is a demyelinating neurological disorder with a highly heterogeneous clinical presentation and course of progression. Disease-modifying therapies are the only available treatment, as there is no known cure for the disease. Careful selection of suitable therapies is necessary, as they can be accompanied by serious risks and adverse effects such as infection. Magnetic resonance imaging (MRI) plays a central role in the diagnosis and management of MS, though MRI lesions have displayed only moderate associations with MS clinical outcomes, known as the clinico-radiological paradox. With the advent of machine learning (ML) in healthcare, the predictive power of MRI can be improved by leveraging both traditional and advanced ML algorithms capable of analyzing increasingly complex patterns within neuroimaging data. The purpose of this review was to examine the application of MRI-based ML for prediction of MS disease progression. Studies were divided into five main categories: predicting the conversion of clinically isolated syndrome to MS, cognitive outcome, EDSS-related disability, motor disability and disease activity. The performance of ML models is discussed along with highlighting the influential MRI-derived biomarkers. Overall, MRI-based ML presents a promising avenue for MS prognosis. However, integration of imaging biomarkers with other multimodal patient data shows great potential for advancing personalized healthcare approaches in MS., (© 2024. The Author(s).)

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is an immune-mediated demyelinating disease that is challenging to differentiate from multiple sclerosis (MS), as the clinical phenotypes overlap, and people with MOGAD can fulfil the current MRI-based diagnostic criteria for MS. In addition, the MOG antibody assays that are an essential component of MOGAD diagnosis are not standardized. Accurate diagnosis of MOGAD is crucial because the treatments and long-term prognosis differ from those for MS. This Expert Recommendation summarizes the outcomes from a Magnetic Resonance Imaging in MS workshop held in Oxford, UK in May 2022, in which MS and MOGAD experts reflected on the pathology and clinical features of these disorders, the contributions of MRI to their diagnosis and the clinical use of the MOG antibody assay. We also critically reviewed the literature to assess the validity of distinctive imaging features in the current MS and MOGAD criteria. We conclude that dedicated orbital and spinal cord imaging (with axial slices) can inform MOGAD diagnosis and also illuminate differential diagnoses. We provide practical guidance to neurologists and neuroradiologists on how to navigate the current MOGAD and MS criteria. We suggest a strategy that includes useful imaging discriminators on standard clinical MRI and discuss imaging features detected by non-conventional MRI sequences that demonstrate promise in differentiating these two disorders., (© 2024. Springer Nature Limited.)

Objectives: Optic neuritis is a common clinical presentation in patients suffering from multiple sclerosis (MS). Even though optic neuritis is not part of the MS diagnostic criteria, the diagnosis and consideration of differential diagnoses are important in clinical routine. For the evaluation of the optic nerves with MRI, T2-weighted images with fat suppression, known as short tau inversion recovery sequences (STIR), are often used. Besides that, double inversion recovery (DIR) sequences are being used increasingly in MS patients, especially to determine cortical lesions. The Aim of this study was to evaluate the 3D-DIR for the detection of lesions in the optic nerves in MS patients., Methods: MR examinations of 45 MS-patients containing both STIR and DIR images were independently assessed by two neuroradiologic experienced radiologists, blinded to clinical data. A third neuroradiologic, an experienced radiologist, evaluated the images together, also considering clinical data. These results were considered ground truth and statistically compared to the results of the single readings. To objectify our findings, ROI measurements of affected and unaffected optic nerve segments were made, and a contrast ratio (CR) was calculated., Result: DIR images are statistically equivalent to STIR images concerning the detection of lesions in the optic nerve (p < 0.001). The sensitivity of DIR images (84.7 %) and STIR images (77 %), as well as the specificity (92.2 % and 91.2 %), are comparable. The interrater reliability was substantial for both sequences (κ = 0,73) as well as separated for the STIR images (κ = 0.744) and the DIR images (κ = 0.707). The objective analysis revealed significantly higher CRs in DIR images (p < 0.001)., Conclusion: 3D DIR images showed similar sensitivity and specificity for detecting optic nerve lesions in comparison to dedicated 2D images of the optic nerve. When 3D DIR images are part of the routine scan protocol for evaluating MS patients, additional 2D imaging of the optic nerve is no longer necessary., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: Thalamic tissue damage in multiple sclerosis (MS) follows a 'surface-in' gradient from the ventricular surface. The clinical consequences of this gradient are not completely understood. Using quantitative gradient-recalled echo (qGRE) MRI, we evaluated a periventricular thalamic gradient of tissue integrity in MS and its relationship with clinical variables., Methods: Structural and qGRE MRI scans were acquired for a cohort of MS patients and healthy controls (HC). qGRE-derived R2t* values were used as a measure of tissue integrity. Thalamic segmentations were divided into 1-mm concentric bands radiating from the ventricular surface, excluding the CSF-adjacent band. Median R2t* values within these bands were used to calculate the periventricular thalamic gradient., Results: We included 44 MS patients and 17 HC. R2t* increased slightly with distance from the ventricular surface in HC. MS patients had a steeper periventricular thalamic gradient compared to HC (mean slope 0.55 vs. 0.36; p < 0.001), which correlated with longer disease duration (β = 0.001 /year; p = 0.027) and higher Expanded Disability Status Scale (EDSS) score (β = 0.07 /EDSS point; p = 0.019). Left and right thalamus were symmetrically affected., Conclusions: We detected an increased thalamic gradient in MS in vivo using qGRE MRI, which correlated with disease duration and greater clinical disability. These findings further support the 'surface-in' pathology hypothesis in MS and suggest a CSF-mediated process given symmetric bi-thalamic involvement., Competing Interests: Declaration of competing interest JRC has received grant support from the National MS Society and consulting honoraria from EMD Serono, Genentech, Janssen Pharmaceuticals, and Novartis. AHC has received consulting honoraria from Biogen, Bristol Myers Squibb, EMD Serono, and Genentech/F. Hoffman-La Roche, Horizon, Janssen, Novartis, Octave, and TG Therapeutics. MRB has received consulting honoraria from Bristol Myers Squibb, EMD Serono, Novartis, and TG Therapeutics., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: In multiple sclerosis (MS), imaging biomarkers play a crucial role in characterizing the disease at the time of diagnosis. MRI and optical coherence tomography (OCT) provide readily available biomarkers that may help to define the patient's clinical profile. However, the evaluation of cortical and paramagnetic rim lesions (CL, PRL), as well as retinal atrophy, is not routinely performed in clinic., Objective: To identify the most significant MRI and OCT biomarkers associated with early clinical disability in MS., Methods: Brain, spinal cord (SC) MRI, and OCT scans were acquired from 45 patients at MS diagnosis to obtain: brain PRL and non-PRL, CL, SC lesion volumes and counts, brain volumetric metrics, SC C2-C3 cross-sectional area, and retinal layer thickness. Regression models assessed relationships with physical disability (Expanded Disability Status Scale [EDSS]) and cognitive performance (Brief International Cognitive Assessment for Multiple Sclerosis [BICAMS])., Results: In a stepwise regression (R 2  = 0.526), PRL (β = 0.001, p = 0.023) and SC lesion volumes (β = 0.001, p = 0.017) were the most significant predictors of EDSS, while CL volume and age were strongly associated with BICAMS scores. Moreover, in a model where PRL and non-PRL were pooled, only the contribution of SC lesion volume was retained in EDSS prediction. OCT measures did not show associations with disability at the onset., Conclusion: At MS onset, PRL and SC lesions exhibit the strongest association with physical disability, while CL strongly contribute to cognitive performance. Incorporating the evaluation of PRL and CL into the initial MS patient assessment could help define their clinical profile, thus supporting the treatment choice., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Since data is limited on radiologically isolated syndrome (RIS) subjects in certain regions like the Middle East, we aimed to further explore the replicability and generalizability of previously suggested predictors among a cohort of Iranian RIS subjects and report the long-term clinically definite MS (CDMS) conversion rate in this cohort., Methods: We conducted a prospective 10-year cohort on our RIS participants, during which we collected the MRI, paraclinical, and demographic data of the subjects, and identified those who converted to CDMS., Results: Out of 35 participants, 10 (28.5 %) developed CDMS during an average of 5.58 ± 3.08 years (range: 4 months to 10.33 years). OCB positivity was the only definitive predictor for conversion to CDMS in this cohort (P-value = 0.006), but other previously reported risk factors such as spinal cord lesions or age lacked statistical significance (P-values > 0.05). We also reported the median survival time as 114 months, the proportion surviving after 14 months as 96.9 % ± 3.1 %, and the overall conversion rate as 0.05 cases per year., Conclusion: Our results highlight OCB as an important predictive factor of clinical conversion in RIS. The prominence of OCB suggests a need for routine CSF analysis in RIS subjects and could guide clinicians in deciding which RIS subjects benefit from DMTs., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Neurodegenerative disorders, including Multiple Sclerosis (MS), are heterogenous disorders which affect the myelin sheath of the central nervous system (CNS). Magnetic Resonance Imaging (MRI) provides a non-invasive method for studying, diagnosing, and monitoring disease progression. As an emerging research area, many studies have attempted to connect MR metrics to underlying pathophysiological presentations of heterogenous neurodegeneration. Most commonly, small animal models are used, including Experimental Autoimmune Encephalomyelitis (EAE), Theiler's Murine Encephalomyelitis (TMEV), and toxin models including cuprizone (CPZ), lysolecithin, and ethidium bromide (EtBr). A contrast and comparison of these models is presented, with focus on the cuprizone model, followed by a review of literature studying neurodegeneration using MRI and the cuprizone model. Conventional MRI methods including T 1 Weighted (T 1 W) and T 2 Weighted (T 2 W) Imaging are mentioned. Quantitative MRI methods which are sensitive to diffusion, magnetization transfer, susceptibility, relaxation, and chemical composition are discussed in relation to studying the CPZ model. Overall, additional studies are needed to improve both the sensitivity and specificity of MRI metrics for underlying pathophysiology of neurodegeneration and the relationships in attempts to clear the clinico-radiological paradox. We therefore propose a multiparametric approach for the investigation of MR metrics for underlying pathophysiology., (© 2024. The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).)

Background and Purpose: Quantitative T1 mapping can be an essential tool for assessing tissue injury in multiple sclerosis (MS). We introduce T1-REQUIRE, a method that converts a single high-resolution anatomical 3D T1-weighted Turbo Field Echo (3DT1TFE) scan into a parametric T1 map that could be used for quantitative assessment of tissue damage. We present the accuracy and feasibility of this method in MS., Methods: 14 subjects with relapsing-remitting MS and 10 healthy subjects were examined. T1 maps were generated from 3DT1TFE images using T1-REQUIRE, which estimates T1 values using MR signal equations and internal tissue reference T1 values. Estimated T1 of lesions, white, and gray matter regions were compared with reference Inversion-Recovery Fast Field Echo T1 values and analyzed via correlation and Bland-Altman (BA) statistics., Results: 159 T1-weighted (T1W) hypointense MS lesions and 288 gray matter regions were examined. T1 values for MS lesions showed a Pearson's correlation of r = 0.81 (p < 0.000), R 2  = 0.65, and Bias = 4.18%. BA statistics showed a mean difference of -53.95 ms and limits of agreement (LOA) of -344.20 and 236.30 ms. Non-lesional normal-appearing white matter had a correlation coefficient of r = 0.82 (p < 0.000), R 2  = 0.67, Bias = 8.78%, mean difference of 73.87 ms, and LOA of -55.67 and 203.41 ms., Conclusions: We demonstrate the feasibility of retroactively derived high-resolution T1 maps from routinely acquired anatomical images, which could be used to quantify tissue pathology in MS. The results of this study will set the stage for testing this method in larger clinical studies for examining MS disease activity and progression., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Progression independent of relapse activity (PIRA) has been recently proposed in multiple sclerosis (MS) as a model identifying a continuous silent progression of disability without the manifestation of new clinical and magnetic resonance imaging (MRI) events that contribute to MS worsening. Despite evidence suggesting that clinical MS manifestations often affect cognitive functioning and the importance of neuropsychological monitoring over time, attention to silent cognitive progression is lacking, and the PIRA concept does not include a measure of cognitive function. In this personal viewpoint, we highlight the need to include cognition in the PIRA model to have a more comprehensive understanding of clinical progression in patients with MS., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: S.Z. has nothing to disclose. M.G. has nothing to disclose. T.A.F. received research support from the European Committee for Treatment and Research in Multiple Sclerosis, and received consulting fees for Click Therapeutics. M.C. received speaker honoraria from Biogen, Bristol Myers Squibb, Merck Serono, Novartis and Roche, and received research support from the Progressive MS Alliance and Italian Minister of Health and Biogen, Bristol Myers Squibb, Merck Serono, Novartis and Roche. R.H.B.B. received research support from Bristol Meyers Squibb, consultant fees from Bristol Meyers Squibb, Roche and Sanofi; speaking fees from Bristol Meyers Squibb and EMD Serono; and royalties from Psychological Assessment Resources.

Objective: We investigated the effects of adding regions to current dissemination in space (DIS) criteria for multiple sclerosis (MS)., Methods: Participants underwent brain, optic nerve, and spinal cord MRI. Baseline DIS was assessed by 2017 McDonald criteria and versions including optic nerve, temporal lobe, or corpus callosum as a fifth region (requiring 2/5), a version with all regions (requiring 3/7) and optic nerve variations requiring 3/5 and 4/5 regions. Performance was evaluated against MS diagnosis (2017 McDonald criteria) during follow-up., Results: Eighty-four participants were recruited (53F, 32.8 ± 7.1 years). 2017 McDonald DIS criteria were 87% sensitive (95% CI: 76-94), 73% specific (50-89), and 83% accurate (74-91) in identifying MS. Modified criteria with optic nerve improved sensitivity to 98% (91-100), with specificity 33% (13-59) and accuracy 84% (74-91). Criteria including temporal lobe showed sensitivity 94% (84-98), specificity 50% (28-72), and accuracy 82% (72-90); criteria including corpus callosum showed sensitivity 90% (80-96), specificity 68% (45-86), and accuracy 85% (75-91). Criteria adding all three regions (3/7 required) had sensitivity 95% (87-99), specificity 55% (32-76), and accuracy 85% (75-91). When requiring 3/5 regions (optic nerve as the fifth), sensitivity was 82% (70-91), specificity 77% (55-92), and accuracy 81% (71-89); with 4/5 regions, sensitivity was 56% (43-69), specificity 95% (77-100), and accuracy 67% (56-77)., Interpretation: Optic nerve inclusion increased sensitivity while lowering specificity. Increasing required regions in optic nerve criteria increased specificity and decreased sensitivity. Results suggest considering the optic nerve for DIS. An option of 3/5 or 4/5 regions preserved specificity, and criteria adding all three regions had highest accuracy., (© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Background and Objectives: Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals., Methods: This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models., Results: Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age ( p < 0.001, b = -5.111 × 10 -5 ), lower disability ( p = 0.04, b = -2.352 × 10 -5 ), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS ( p = 0.015, b = -6.686 × 10 -4 )., Discussion: χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

microRNAs (miRNAs) are promising biomarkers for many diseases, including multiple sclerosis (MS). The neurofilament light chain (NfL) is a biomarker that can detect axonal damage in different neurological diseases. The objective of this study was to evaluate the association of the expression profile of pre-selected miRNAs and NfL levels with clinical and radiological variables in MS patients. We conducted a 1-year longitudinal prospective study in MS patients with different clinical forms. We measured clinical disability using the expanded disability status scale (EDSS), the magnetic resonance imaging (MRI) volumetry baseline, and cognitive functioning using the processing speed test (PST) at baseline and 1 year later. Selected serum miRNAs and serum NfL (sNfL) levels were quantified. Seventy-three patients were recruited. MiR-126.3p correlated with EDSS and cognitive status at baseline and miR-126.3p and miR-9p correlated with cognitive deterioration at 1 year. Correlations with regional brain volumes were observed between miR-126.3p and the cortical gray matter, cerebellum, putamen, and pallidum; miR-146a.5p with the cerebellum and pallidum; miR-29b.3p with white matter and the pallidum; miR-138.5p with the pallidum; and miR-9.5p with the thalamus. sNfL was correlated with miR-9.5p. miR-146a.5p was also associated with the MS phenotype. These data justify future studies to further explore the utility of miRNAs (mirR-126.3p, miR-146.5p, and miR.9-5p) and sNfL levels as biomarkers of MS.

Segmentation of multiple sclerosis (MS) lesions on brain MRI scans is crucial for diagnosis, disease and treatment monitoring but is a time-consuming task. Despite several automated algorithms have been proposed, there is still no consensus on the most effective method. Here, we applied a consensus-based framework to improve lesion segmentation on T1-weighted and FLAIR scans. The framework is designed to combine publicly available state-of-the-art deep learning models, by running multiple segmentation tasks before merging the outputs of each algorithm. To assess the effectiveness of the approach, we applied it to MRI datasets from two different centers, including a private and a public dataset, with 131 and 30 MS patients respectively, with manually segmented lesion masks available. No further training was performed for any of the included algorithms. Overlap and detection scores were improved, with Dice increasing by 4-8% and precision by 3-4% respectively for the private and public dataset. High agreement was obtained between estimated and true lesion load (ρ = 0.92 and ρ = 0.97) and count (ρ = 0.83 and ρ = 0.94). Overall, this framework ensures accurate and reliable results, exploiting complementary features and overcoming some of the limitations of individual algorithms., (© 2024. The Author(s).)

Background: Mirror movements (MM) are commonly caused by a defect of interhemispheric pathways also affected in multiple sclerosis (MS), particularly the corpus callosum. We investigated the prevalence of MM in MS in relation to functional and morphological callosal fiber integrity by transcranial magnetic stimulation (TMS), magnetic resonance imaging (MRI), as well as fatigue., Methods: In 21 patients with relapsing-remitting MS and 19 healthy controls, MM were assessed and graded (Woods and Teuber scale: MM 1-4) using a bedside test. Fatigue was evaluated using the Fatigue Scale for Motor and Cognitive Functions (FSMC) questionnaire. TMS measured ipsilateral silent period latency and duration. MRI assessed callosal atrophy by measuring the normalized corpus callosum area (nCCA), corpus callosum index (CCI), and lesion volume., Results: MS patients had significantly more often and pronounced MM compared to healthy controls (p = 0.0002) and nCCA was significantly lower (p = 0.045) in MRI studies. Patients with higher MM scores (MM > 1 vs. MM 0/1) showed significantly more fatigue (higher FSMC sum score, p = 0.04, motor score, p = 0.01). In TMS and MRI studies, no significant differences were found between patients with MM 0/1 and those with MM > 1 (ipsilateral silent period measurements, CCA, CCI and lesion volume)., Conclusions: MM are common in MS and can easily be detected through bedside testing. As MM are associated with fatigue, they might indicate fatigue in MS. It is possible that other cerebral structures, in addition to the corpus callosum, may contribute to the origin of MM in MS., (© 2024. The Author(s).)

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis and have implications for non-relapsing biological progression. In recent years, the discovery of innovative MRI and PET-derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with multiple sclerosis, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted and T2-weighted scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a consensus statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this consensus statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com. Elements of this work were written by employees of the US Government.)

Background: Leukocyte telomere length (LTL) shortens with age and may be related to multiple sclerosis (MS)., Objective: We hypothesize that chronologically young people with MS (pwMS) with short LTL behave similarly to older MS subjects., Methods: Prospective 2-year study including two cohorts of young (18-35 years) and elderly (⩾50 years) pwMS with similar disease duration. Physical and cognitive evaluation, 3 T brain magnetic resonance imaging (MRI) and retinal nerve fiber layer (RNFL) measurement by optical coherence tomography were performed. LTL was measured by quantitative polymerase chain reaction assay., Results: Around 105 patients were included, 57 young and 48 elderly. LTL was shorter in older patients (0.61 versus 0.57, p = 0.0081) and in males (female, 0.60; male, 0.59; p = 0.01335). For every 10-year increase in age, LTL was 0.02 U shorter. In elderly, LTL correlated with disease duration ( p = 0.05), smoking ( p = 0.03), Expanded Disability Status Scale (EDSS; p = 0.004), 9HPT ( p = 0.00007), high-efficacy therapies ( p = 0.001), brain lesion volume (BLV) ( p = 0.011), and number of T2 lesions ( p = 0.01). In young patients, LTL did not correlate with clinical or radiological variables. For every 0.1 U shorter LTL, gray matter volume decreased 1.75 cm 3 and white matter volume 1.78 cm 3 ., Conclusion: LTL correlated with disability and BLV in elderly. Besides LTL shortening, other variables should be considered as mechanisms of neurodegeneration that might be involved in aging pwMS., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Choroid plexus (ChP) enlargement is an emerging radiological biomarker in multiple sclerosis (MS)., Objectives: This study aims to assess ChP volume in a large cohort of patients with radiologically isolated syndrome (RIS) versus healthy controls (HC) and explore its relationship with other brain volumes, disease activity, and biological markers., Methods: RIS individuals were included retrospectively and compared with HC. ChPs were automatically segmented using an in-house automated algorithm and manually corrected., Results: A total of 124 patients fulfilled the 2023 RIS criteria, and 55 HCs were included. We confirmed that ChPs are enlarged in RIS versus HC (mean (±SD) normalized ChP volume: 17.24 (±4.95) and 11.61 (±3.58), respectively, p < 0.001). Larger ChPs were associated with more periventricular lesions (ρ = 0.26; r 2 = 0.27; p = 0.005 for the correlation with lesion volume, and ρ = 0.2; r 2 = 0.21; p = 0.002 for the correlation with lesion number) and lower thalamic volume (ρ = -0.38; r 2 = 0.44; p < 0.001), but not with lesions in other brain regions. Conversely, ChP volume did not correlate with biological markers. No significant difference in ChP volume was observed between subjects who presented or did not have a clinical event or between those with or without imaging disease activity., Conclusions: This study provides evidence that ChP volume is higher in RIS and is associated with measures reflecting periventricular pathology but does not correlate with biological, radiological, or clinical markers of disease activity., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: C.L.-C. received a Neuromod Institute grant for her PhD.VAGR reports fees for traveling from Novartis, Merck, Biogen, and Roche, speaker’s honoraria from Novartis, Sandoz, Merck, Biogen, Roche, consulting fees from Biogen, Merck, Novartis, Janssen, M3 Global Research, and Atheneum Partners, all outside of the submitted work.L. M. has no conflict of interest.E. T. received consulting and lecturing fees, travel grants, or unconditional research support from the following pharmaceutical companies: Actelion, Biogen, BMS, Janssen, Merck, Novartis, Roche, and Teva Pharma.P. L. has no financial conflicts related to this work.C. L. has received speaker or consulting fees from Biogen, Merck, Novartis, Sanofi, and Roche and a research grant (to the institution) from Biogen.H. Z. has no disclosure related to this work. HZ received consulting fees from ALEXION, HORIZON THERAPEUTICS, ROCHE, BIOGEN IDEC, SANOFI, JANSSEN, and research support from ROCHE and NOVARTIS.F. D.D. has no financial conflicts related to this work.E. L.P. has no financial conflicts related to this work.A. S. has no financial conflicts related to this work and has received research grants from The Turkish Multiple Sclerosis Society, The Scientific and Technological Research Council Of Turkiye, and Istanbul University-Cerrahpasa Research Support Funds. He has received consultancy fees from Roche Ltd, Merck-Serono, Biogen Idec/Gen Pharma of Turkiye, Sanofi-Genzyme, Novartis, and Alexion and received honoraria for lectures from Sanofi-Genzyme, Novartis, Roche Ltd., and Teva—registration coverage for attending scientific congresses or symposia from Sanofi-Genzyme and Alexion.M. C. has no conflict of interest.A. YP. has no financial conflicts related to this work.C. J.A. has no conflict of interest with this work.D. T.O. received personal compensation for consulting and advisory services from Biogen, Eisai, EMD Serono, Genentech, Genzyme/Sanofi, Moderna, RVL Pharmaceuticals, Inc., Zenas BioPharma, and research support from EMD Serono/Merck and Novartis. D.T.O. has issued national and international patents and pending patents related to other developed technologies. D.T.O. received royalties for intellectual property licensed by The Board of Regents of The University of Texas System and is also the Founder of Revert Health Inc.B. S. has received personal speaker fees from Janssen, Biogen, Novartis, Merck, and Sanofi, as well as research support (to the institution) from Merck, Roche, and Novartis.C. L-F. has no conflict of interest.

Background: Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy., Objectives: The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS., Methods: Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months., Results: Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status., Discussion: Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article:Karlo Toljan: Training grant: National MS Society (FP-2207-39855).Lynn Daboul: Research support: NIH Medical Research Scholars Program.Praneeta Raza: Nothing to disclose.Melissa L. Martin: Nothing to disclose.Quy Cao: Nothing to disclose.Carly M. O’Donnell: Nothing to disclose.Paulo Rodrigues: Employed by and holds options of QMENTA.John Derbyshire: Nothing to disclose.Christina J. Azevedo: Research support: National Multiple Sclerosis Society, National Institutes of Health. Consulting: Genentech, EMD Serono, Alexion Pharmaceuticals, Sanofi Genzyme, Horizon Therapeutics.Amit Bar-Or: Consulting: Accure, Atara Biotherapeutics, Biogen, Bristol Myers Squibb, GlaxoSmithKline, Gossamer, Janssen, AstraZeneca, EMD Serono, Novartis, Genentech, Sanofi. Research support: Biogen, Genentech, EMD Serono, Novartis.Eduardo Caverzasi: Nothing to disclose.Peter A Calabresi: Research support: Genentech. Advisory board: Lilly, Novartis, Idorsia, and Project Efflux.Bruce A. C. Cree: Consulting: Atara, Autobahn, Avotres, Biogen, Boston Pharma, EMD Serono, Gossamer Bio, Hexal/Sandoz, Horizon, Immunic AG, Kyverna, Neuron23, Novartis, Sanofi, and TG Therapeutics; research support from Genentech.Leorah Freeman: Advisory board: Genentech, Novartis, Celgene. Consulting: EMD Serono, Celgene, Biogen. Program sponsorship: Biogen, EMD Serono.Roland G. Henry: Consulting: Neurona, Roche, Novartis, Sanofi, QIA, Celgene/BMS, Atara, Medday, Boston Pharma. Research support: Roche, Atara.Erin E Longbrake: Consulting: Genentech, Sanofi, Alexion, Biogen, EMD Serono, Bristol Myers Squibb.Jiwon Oh: Research support: Biogen, Roche, EMD Serono. Consulting: EMD Serono, Sanofi, Biogen, Roche, Celgene, Novartis.Nico Papinutto: Research support: Race to Erase MS Foundation.Daniel Pelletier: Consulting: Sanofi, Roche, Novartis.Rohini D. Samudralwar: Advisory board: Biogen, EMD Serono, Sanofi. Consulting: EMD Serono, Biogen.Matthew K. Schindler: Nothing to disclose.Elias S. Sotirchos: Consulting for Alexion, Viela Bio, Horizon Therapeutics, Genentech, Ad Scientiam. Honoraria: Alexion, Viela Bio, Biogen.Nancy L. Sicotte: Research support: NIH, National MS Society, Patient Centered Outcomes Research Institute, Race to Erase MS Foundation, Biogen.Andrew J. Solomon: Advisory board: Genentech, Biogen, Alexion, Celgene, Greenwich Biosciences, TG Therapeutics. Consulting: Octave Bioscience. Non-promotional speaking: EMD Serono. Research support: Bristol Myers Squibb, Sanofi, Biogen, Novartis, Janssen, Genentech. Trainee funding: Biogen.Russell T. Shinohara: Consulting: Octave Bioscience. Research support: NIH, National MS Society.Daniel S. Reich: Supported by Intramural Research Program of NINDS. Research support: Abata, Sanofi.Pascal Sati: Research support: NIH, National MS Society, Erwin Rautenberg Foundation.Daniel Ontaneda: Research support: NIH, National MS Society, Patient Centered Outcomes Research Institute, Race to Erase MS Foundation, Bristol Myers Squibb, Genentech, Sanofi, Novartis. Consulting: Biogen, Bristol Myers Squibb, Genentech, Sanofi, Janssen, Novartis, Pipeline Therapeutics, and Merck.

Purpose: Multiple Sclerosis (MS) is a common autoimmune disease of the central nervous system. MRI plays a crucial role in diagnosing as well as in disease and treatment monitoring. Therefore, evaluation of cerebral MRI of MS patients is part of daily clinical routine. A growing number of companies offer commercial software to support the reporting with automated lesion detection. Aim of this study was to evaluate the effect of such a software with AI supported lesion detection to the radiologic reporting., Method: Four radiologist each counted MS-lesions in MRI examinations of 50 patients separated by the locations periventricular, cortical/juxtacortical, infrantentorial and unspecific white matter. After at least six weeks they repeated the evaluation, this time using the AI based software mdbrain for lesion detection. In both settings the required time was documented. Further the radiologists evaluated follow-up MRI of 50 MS-patients concerning new and enlarging lesions in the same manner., Results: To determine the lesion-load the average reporting time decreased from 286.85 sec to 196.34 sec (p > 0.001). For the evaluation of the follow-up images the reporting time dropped from 196.17 sec to 120.87 sec (p < 0.001). The interrater reliabilities showed no significant differences for the determination of lesion-load (0.83 without vs. 0.8 with software support) and for the detection of new/enlarged lesions (0.92 without vs. 0.82 with software support)., Conclusion: For the evaluation of MR images of MS patients, an AI-based support for image-interpretation can significantly decreases reporting times., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though MS lesion detection has been studied, limited attention has been paid to clinical analysis and computational risk factor prediction. Artificial intelligence (AI) techniques and Machine Learning (ML) methods offer accurate and effective alternatives to mapping MS progression. However, there are challenges in accessing clinical data and interdisciplinary collaboration. By analyzing 103 papers, we recognize the trends, strengths and weaknesses of AI, ML, and statistical methods applied to MS diagnosis. AI/ML-based approaches are suggested to identify MS risk factors, select significant MS features, and improve the diagnostic accuracy, such as Rule-based Fuzzy Logic (RBFL), Adaptive Fuzzy Inference System (ANFIS), Artificial Neural Network methods (ANN), Support Vector Machine (SVM), and Bayesian Networks (BNs). Meanwhile, applications of the Expanded Disability Status Scale (EDSS) and Magnetic Resonance Imaging (MRI) can enhance MS diagnostic accuracy. By examining established risk factors like obesity, smoking, and education, some research tackled the issue of disease progression. The performance metrics varied across different aspects of MS studies: Diagnosis: Sensitivity ranged from 60 % to 98 %, specificity from 60 % to 98 %, and accuracy from 61 % to 97 %. Prediction: Sensitivity ranged from 76 % to 98 %, specificity from 65 % to 98 %, and accuracy from 62 % to 99 %. Segmentation: Accuracy ranged up to 96.7 %. Classification: Sensitivity ranged from 78 % to 97.34 %, specificity from 65 % to 99.32 %, and accuracy from 71 % to 97.94 %. Furthermore, the literature shows that combining techniques can improve efficiency, exploiting their strengths for better overall performance., Competing Interests: Declaration of competing interest The authors have no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: QSM provides insight into healthy brain aging and neuropathologies such as multiple sclerosis (MS), traumatic brain injuries, brain tumors, and neurodegenerative diseases. Phase data for QSM are usually acquired from 3D gradient-echo (3D GRE) scans with long acquisition times that are detrimental to patient comfort and susceptible to patient motion. This is particularly true for scans requiring whole-brain coverage and submillimeter resolutions. In this work, we use a multishot 3D echo plannar imaging (3D EPI) sequence with shot-selective 2D CAIPIRIHANA to acquire high-resolution, whole-brain data for QSM with minimal distortion and blurring., Methods: To test clinical viability, the 3D EPI sequence was used to image a cohort of MS patients at 1-mm isotropic resolution at 3 T. Additionally, 3D EPI data of healthy subjects were acquired at 1-mm, 0.78-mm, and 0.65-mm isotropic resolution with varying echo train lengths (ETLs) and compared with a reference 3D GRE acquisition., Results: The appearance of the susceptibility maps and the susceptibility values for segmented regions of interest were comparable between 3D EPI and 3D GRE acquisitions for both healthy and MS participants. Additionally, all lesions visible in the MS patients on the 3D GRE susceptibility maps were also visible on the 3D EPI susceptibility maps. The interplay among acquisition time, resolution, echo train length, and the effect of distortion on the calculated susceptibility maps was investigated., Conclusion: We demonstrate that the 3D EPI sequence is capable of rapidly acquiring submillimeter resolutions and providing high-quality, clinically relevant susceptibility maps., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: The clinical spectrum and diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) has evolved in the setting of an optimized anti-MOG-IgG cell-based assay and expert consensus. The McDonald criteria for MS have been revised multiple times to improve the accuracy and specificity of diagnosis on a framework based on clinical presentation, MRI findings, and CSF results. While the uses of MS and MOGAD diagnostic criteria are helpful for typical cases, such utility for patients with overlapping clinical, laboratorial, and imaging features is unknown, posing diagnostic and management uncertainties., Objectives: To report a multicenter cohort of patients with overlapping phenotypic features of MOGAD and MS and evaluate the application of new MOGAD diagnostic criteria., Methods: A collaborative retrospective cohort study was performed to identify patients with both positive serum anti-MOG-IgG and fulfillment of the MS revised 2017 McDonald criteria. Clinical and radiographic features of patients fulfilling inclusion criteria were reviewed longitudinally, including relapses, repeated MRI, and MOG-IgG testing in detail to allow the panel of expert opinion to assign to each case. The International MOGAD Panel proposed criteria were applied at onset and last follow-up to each case and compared to the expert author diagnosis assignment based on presentation, clinical and imaging features, and response to treatment., Results: Ten of 225 (4%) MOG-IgG seropositive cases met study inclusion criteria [seven of 10 were female; age at initial event: eight adults (mean age 26.8 years), two adolescents (mean age 14.5 years)]. AQP4-IgG was negative for all. Apart from serum titers of MOG-IgG, distinguishing clinical and radiographic features [i.e., clinical severity of the initial demyelinating event, radiographic features (optic nerve/spine/brain), and presence/absence of lesion normalization on serial scans] led to consensus of three separate classifications differing by degrees of shared features of MOGAD and MS. Patients were classified by expert panel into (1) Classic MOGAD even with MS-like, well-defined brain lesions, when severe events and most T2 lesions normalized (n = 5; MOG-IgG titers 1:100, 1:20, 1:160, 1:40, 1:200); (2) Classic RRMS included cases thought to have likely false positive or clinically irrelevant MOG-IgG, due to mild clinical events and no radiographic normalization of well-defined MS-like lesions (n = 3; MOG titers 1:20, 1:100, 1:40); (3) MOGAD and MS overlapping phenotype was defined by those with a combination of mild and severe clinical events, partial T2 lesion normalization, both well- and ill-defined lesions (n = 2; MOG titers 1:20, 1:100). The application of the International MOGAD Panel criteria categorized five patients (50%) in agreement with expert assignment. One additional patient was classified in agreement to assignment when MOGAD criteria were applied after serial MOG-IgG titers testing., Discussion: While the International MOGAD Panel diagnostic criteria have helped with accuracy for the diagnosis of this condition, in a group of patients seropositive for MOG-IgG with overlapping clinical and imaging features of RRMS criteria review may lead to increased accuracy. Serial serologies, repeated imaging, close attention to clinical course, and response to therapy are possible variables to consider for further refinement of MOGAD diagnostic criteria., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Objectives: Retinal optical coherence tomography (OCT) provides promising prognostic imaging biomarkers for future disease activity in multiple sclerosis (MS). However, raw OCT-derived measures have multiple dependencies, supporting the need for establishing reference values adjusted for possible confounders. The purpose of this study was to investigate the capacity for age-adjusted z scores of OCT-derived measures to prognosticate future disease activity and disability worsening in people with MS (PwMS)., Methods: We established age-adjusted OCT reference data using generalized additive models for location, scale, and shape for peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell-inner plexiform layer (GCIP) thicknesses, involving 910 and 423 healthy eyes, respectively. Next, we transformed the retinal layer thickness of PwMS from 3 published studies into age-adjusted z scores (pRNFL-z and GCIP-z) based on the reference data. Finally, we investigated the association of pRNFL-z or GCIP-z as predictors with future confirmed disability worsening (Expanded Disability Status Scale score increase) or disease activity (failing of the no evidence of disease activity [NEDA-3] criteria) as outcomes. Cox proportional hazards models or logistic regression analyses were applied according to the original studies. Optimal cutoffs were identified using the Akaike information criterion as well as location with the log-rank and likelihood-ratio tests., Results: In the first cohort (n = 863), 172 PwMS (24%) had disability worsening over a median observational period of 2.0 (interquartile range [IQR]:1.0-3.0) years. Low pRNFL-z (≤-2.04) were associated with an increased risk of disability worsening (adjusted hazard ratio (aHR) [95% CI] = 2.08 [1.47-2.95], p = 3.82e -5 ). In the second cohort (n = 170), logistic regression analyses revealed that lower pRNFL-z showed a higher likelihood for disability accumulation at the two-year follow-up (reciprocal odds ratio [95% CI] = 1.51[1.06-2.15], p = 0.03). In the third cohort (n = 78), 46 PwMS (59%) did not maintain the NEDA-3 status over a median follow-up of 2.0 (IQR: 1.9-2.1) years. PwMS with low GCIP-z (≤-1.03) had a higher risk of showing disease activity (aHR [95% CI] = 2.14 [1.03-4.43], p = 0.04). Compared with raw values with arbitrary cutoffs, applying the z score approach with optimal cutoffs showed better performance in discrimination and calibration (higher Harrell's concordance index and lower integrated Brier score)., Discussion: In conclusion, our work demonstrated reference cohort-based z scores that account for age, a major driver for disease progression in MS, to be a promising approach for creating OCT-derived measures useable across devices and toward individualized prognostication.

Spinal cord (SC) atrophy obtained from structural magnetic resonance imaging has gained relevance as an indicator of neurodegeneration in various neurological disorders. The common method to assess SC atrophy is by comparing numerical differences of the cross-sectional spinal cord area (CSA) between time points. However, this indirect approach leads to considerable variability in the obtained results. Studies showed that this limitation can be overcome by using a registration-based technique. The present study introduces the Structural Image Evaluation using Normalization of Atrophy on the Spinal Cord (SIENA-SC), which is an adapted version of the original SIENA method, designed to directly calculate the percentage of SC volume change over time from clinical brain MRI acquired with an extended field of view to cover the superior part of the cervical SC. In this work, we compared SIENA-SC with the Generalized Boundary Shift Integral (GBSI) and the CSA change. On a scan-rescan dataset, SIENA-SC was shown to have the lowest measurement error than the other two methods. When comparing a group of 190 Healthy Controls with a group of 65 Multiple Sclerosis patients, SIENA-SC provided significantly higher yearly rates of atrophy in patients than in controls and a lower sample size when measured for treatment effect sizes of 50%, 30% and 10%. Our findings indicate that SIENA-SC is a robust, reproducible, and sensitive approach for assessing longitudinal changes in spinal cord volume, providing neuroscientists with an accessible and automated tool able to reduce the need for manual intervention and minimize variability in measurements., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Nicola De Stefano reports financial support was provided by National Recovery and Resilience Plan (PNRR), and also relationship with Biogen, Merck, Novartis, Sanofi, Roche, Teva, FISM that includes: consulting or advisory, funding grants, speaking and lecture fees, and travel reimbursement. Rosa Cortese reports a relationship with Roche, Merck Serono, Janssen, Novartis, Sanofi that includes: speaking and lecture fees and travel reimbursement. Ferran Prados reports a relationship with National Institute for Health and Care Research (NIHR) Biomedical Research Centres (BRC) at University College London (UCL) that includes: employment, funding grants, speaking and lecture fees, and travel reimbursement. Massimiliano Calabrese reports a relationship with Roche, Sanofi Genzyme, Merck Serono, Biogen Idec, Teva, and Novartis Pharma that includes: consulting or advisory, funding grants, speaking and lecture fees, and travel reimbursement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Competing Interests: Declaration of competing interest The author has no conflicts of interest to declare.

Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good-to-excellent test-retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co-expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co-expression, and is associated with serotonergic system-related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Susceptibility source separation, or χ-separation, estimates diamagnetic (χ dia ) and paramagnetic susceptibility (χ para ) signals in the brain using local field and R2' (= R2* - R2) maps. Recently proposed R2*-based χ-separation methods allow for χ-separation using only multi-echo gradient echo (ME-GRE) data, eliminating the need for additional data acquisition for R2 mapping. Although this approach reduces scan time and enhances clinical utility, the impact of missing R2 information remains a subject of exploration. In this study, we evaluate the viability of two previously proposed R2*-based χ-separation methods as alternatives to their R2'-based counterparts: model-based R2*-χ-separation versus χ-separation and deep learning-based χ-sepnet-R2* versus χ-sepnet-R2'. Their performances are assessed in individuals with multiple sclerosis (MS), comparing them with their corresponding R2'-based counterparts (i.e., R2*-χ-separation vs. χ-separation and χ-sepnet-R2* vs. χ-sepnet-R2'). The evaluations encompass qualitative visual assessments by experienced neuroradiologists and quantitative analyses, including region of interest analyses and linear regression analyses. Qualitatively, R2*-χ-separation tends to report higher χ para and χ dia values compared with χ-separation, leading to less distinct lesion contrasts, while χ-sepnet-R2* closely aligns with χ-sepnet-R2'. Quantitative analysis reveals a robust correlation between both R2*-based methods and their R2'-based counterparts (r ≥ 0.88). Specifically, in the whole-brain voxels, χ-sepnet-R2* exhibits higher correlation and better linearity than R2*-χ-separation (χ dia /χ para from R2*-χ-separation: r = 0.88/0.90, slope = 0.79/0.86; χ dia /χ para from χ-sepnet-R2*: r = 0.90/0.92, slope = 0.99/0.97). In MS lesions, both R2*-based methods display comparable correlation and linearity (χ dia /χ para from R2*-χ-separation: r = 0.90/0.91, slope = 0.98/0.91; χ dia /χ para from χ-sepnet-R2*: r = 0.88/0.88, slope = 0.91/0.95). Notably, χ-sepnet-R2* demonstrates negligible offsets, whereas R2*-χ-separation exhibits relatively large offsets (0.02 ppm in the whole brain and 0.01 ppm in the MS lesions), potentially indicating the false presence of myelin or iron in MS lesions. Overall, both R2*-based χ-separation methods demonstrated their viability as alternatives to their R2'-based counterparts. χ-sepnet-R2* showed better alignment with its R2'-based counterpart with minimal susceptibility offsets, compared with R2*-χ-separation that reported higher χ para and χ dia values compared with R2'-based χ-separation., (© 2024 John Wiley & Sons Ltd.)

Purpose: Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are two major demyelinating diseases affecting the central nervous system (CNS). The objective of this study is to evaluate the prevalence of pontine trigeminal nerve lesions in patients diagnosed with MS and NMOSD using MRI., Methods: This retrospective study included patients diagnosed with MS or NMOSD between July 2018 and July 2023. MS patients were clinically diagnosed using the 2017 McDonald criteria, while NMOSD patients were those who met the 2015 International Panel for NMO Diagnosis (IPND) criteria and were positive for Aquaporin-4 Antibody (AQP4-Ab)., Results: The study included a total of 90 patients, with 45 diagnosed with MS and another 45 with NMOSD. Pontine trigeminal nerve lesions were observed in both MS and NMOSD, but were more prevalent in MS patients (20 % vs. 2 %, p = 0.008). Root entry zone (REZ) lesions were found in 4 of 45 MS patients, accounting for 9 % (95 % CI: 3 %-17 %), and were absent in the NMOSD group; however, there was no significant difference between the two groups (p = 0.12). Of the MS patients with pontine trigeminal nerve lesions, 6 out of 9 (63 %; 95 % CI, 36 %-98 %) exhibited bilateral lesions, which was significantly more prevalent compared to the NMOSD group (13 % vs. 0 %, p = 0.03)., Conclusions: The presence of pontine trigeminal nerve lesions, particularly when bilateral, are significantly more prevalent in MS patients than in those with NMOSD, suggesting their utility as a distinctive marker and potential diagnostic indicator specifically for MS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression., Objective: To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS., Methods: In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates., Results: In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12., Conclusion: Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools., (© 2024. The Author(s).)

In this study, we describe a comprehensive 3D magnetic resonance imaging (MRI) protocol designed to assess major tissue and fluid components in the brain. The protocol comprises four different sequences: 1) magnetization transfer prepared Cones (MT-Cones) for two-pool MT modeling to quantify macromolecular content; 2) short-TR adiabatic inversion-recovery prepared Cones (STAIR-Cones) for myelin water imaging; 3) proton-density weighted Cones (PDw-Cones) for total water imaging; and 4) highly T 2 weighted Cones (T 2 w-Cones) for free water imaging. By integrating these techniques, we successfully mapped key brain components-namely macromolecules, myelin water, intra/extracellular water, and free water-in ten healthy volunteers and five patients with multiple sclerosis (MS) using a 3T clinical scanner. Brain macromolecular proton fraction (MMPF), myelin water proton fraction (MWPF), intra/extracellular water proton fraction (IEWPF), and free water proton fraction (FWPF) values were generated in white matter (WM), grey matter (GM), and MS lesions. Excellent repeatability of the protocol was demonstrated with high intra-class correlation coefficient (ICC) values. In MS patients, the MMPF and MWPF values of the lesions and normal-appearing WM (NAWM) were significantly lower than those in normal WM (NWM) in healthy volunteers. Moreover, we observed significantly higher FWPF values in MS lesions compared to those in NWM and NAWM regions. This study demonstrates the capability of our technique to volumetrically map major brain components. The technique may have particular value in providing a comprehensive assessment of neuroinflammatory and neurodegenerative diseases of the brain., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background and Objectives: In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes., Methods: We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue., Results and Conclusions: Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions., (© 2024. The Author(s).)

Background and Purpose: We aimed to characterize hypothalamic involvement in myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) and compare it with neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS)., Methods: A retrospective study was performed to identify hypothalamic lesions in patients diagnosed with MOGAD, NMOSD, or MS from January 2013 to May 2020. The demographic, clinical, and radiological features were recorded. Hypothalamic dysfunction and prognosis were assessed through physical examination, biochemical testing, sleep monitoring, and magnetic resonance imaging., Results: Hypothalamic lesions were observed in seven of 96 patients (7.3%) with MOGAD, 34 of 536 (6.3%) with NMOSD, and 16 of 356 (4.5%) with MS (p = 0.407). The time from disease onset to development of hypothalamic lesions was shortest in MOGAD (12 months). The frequency of bilateral hypothalamic lesions was the lowest in MOGAD (p = 0.008). The rate of hypothalamic dysfunction in MOGAD was 28.6%, which was lower than that in NMOSD (70.6%) but greater than that in MS patients (18.8%; p = 0.095 and p = 0.349, respectively). Hypothalamic dysfunction in MOGAD manifests as hypothalamic-pituitary-adrenal axis dysfunction and hypersomnia. The proportion of complete regression of hypothalamic lesions in MOGAD (100%) was much greater than that in NMOSD (41.7%) and MS patients (18.2%; p = 0.007 and p = 0.001, respectively). An improvement in hypothalamic dysfunction was observed in all MOGAD patients after immunotherapy., Conclusions: MOGAD patients have a relatively high incidence of asymptomatic hypothalamic lesions. The overall prognosis of patients with hypothalamic involvement is good in MOGAD, as the lesions completely resolve, and dysfunction improves after immunotherapy., (© 2024 The Author(s). European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Background: Multiple sclerosis (MS) is an autoimmune demyelinating disease of the central nervous system with neuroaxonal damage. It is the principal driver of non-traumatic disability in young adults. Visual symptoms are common and optic neuritis (ON) may be the revealing feature in up to 30% of cases. Structural optical coherence tomography (OCT) represents a biomarker of central nervous system neurodegeneration in MS. OCT-angiography (OCT-A) is a noninvasive tool allowing the study of retinal vasculature and the detection of microvascular damage in neuro-retinal diseases. In this study, we aimed to assess structural and microvascular retinal changes in patients with MS with and without ON and to correlate the findings with visual function and MS disability., Methods: We conducted a cross-sectional study including patients diagnosed with MS according to the 2017 McDonald criteria. All patients underwent complete neurological examination with evaluation of the Expanded Disability Status Scale (EDSS) and the Multiple Sclerosis Severity Score (MSSS) and an ophthalmological examination including OCT and OCT-A. Patients were compared with age- and sex-matched healthy subjects. The primary endpoints were assessment of retinal nerve fiber layer (RNFL) thickness, ganglion cell layer (GCL+), and ganglion cell complex (GCL++) thicknesses on OCT. Vascular densities in the superficial capillary plexus (SCP), deep capillary plexus (DCP), and choriocapillaris (CC) were assessed on OCT-A, as well as central avascular zone (CAZ) parameters, lacunarity and fractal dimension., Results: A total of 160 MS eyes with and without a previous history of ON and 64 age- and gender-matched healthy eyes were analyzed. Among 160 eyes with MS, 69 had a history of ON. We observed a decrease in RNFL and GCL++ thickness in all 12 quadrants in MS patients when compared to healthy controls. Multivariate analysis by linear regression noted a significant correlation for temporal GCL++ and inferonasal RNFL thickness that were decreased in the MS group. A greater decrease in retinal layers thickness was identified in MS patients with a history of ON. On OCT-A, vascular density in (SCP) was significantly reduced in the MS group (P<0.002). A significant correlation between RNFL thickness and retinal vascular density was found but only in less than half of the hourly quadrants. A significant correlation was noted between visual acuity and CC density (P<0.0001). We also noted an inverse correlation between EDSS scores and CC density (P=0.02 and r=-0.275) and between MSSS and RNFL/GCL++ thicknesses., Conclusions: RNFL and GCL++ layers were thinner in MS patients with a history of ON and were reversely correlated with disease severity. Moreover, retinal vascular changes were observed in MS even in eyes without ON, and CC was reversely correlated with visual function and current disability. Thus, structural OCT coupled with OCT-A could represent a noninvasive and dynamic biomarker of MS severity and progression., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

We describe the case of a 73-year-old woman presenting with headaches, confusion, and vision disturbances. Brain MRI showed a large T2-hyperintense lesion in the right temporo-occipital region with vasogenic edema and leptomeningeal enhancement. A leptomeningeal biopsy was performed, which led to a definitive diagnosis.

This study compared brain glucose metabolism using FDG-PET in the caudate nucleus, putamen, globus pallidus, thalamus, and dorsolateral prefrontal cortex (DLPFC) among patients with Long COVID, patients with fatigue, people with multiple sclerosis (PwMS) patients with fatigue, and COVID recovered controls. PwMS exhibited greater hypometabolism compared to long COVID patients with fatigue and the COVID recovered control group in all studied brain areas except the globus pallidus (effect size range 0.7-1.5). The results showed no significant differences in glucose metabolism between patients with Long COVID and the COVID recovered control group in these regions. These findings suggest that long COVID fatigue may involve non-CNS systems, neurotransmitter imbalances, or psychological factors not captured by FDG-PET, while MS-related fatigue is associated with more severe frontal-striatal circuit dysfunction due to demyelination and neurodegeneration. Symmetrical standardized uptake values (SUVs) between hemispheres in all groups imply that fatigue in these conditions may be related to global or network-level alterations rather than hemisphere-specific changes. Future studies should employ fine-grained analysis methods, explore other brain regions, and control for confounding factors to better understand the pathophysiology of fatigue in MS and long COVID. Longitudinal studies tracking brain glucose metabolism in patients with Long COVID could provide insights into the evolution of metabolic patterns as the condition progresses., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The early identification of individuals with radiologically isolated syndrome (RIS) who are at an elevated risk of progressing to multiple sclerosis (MS) is essential for making informed treatment decisions. This study aimed to evaluate the predictive potential of multifocal Visual Evoked Potentials (mfVEP) measures in individuals with RIS with respect to their conversion to MS. A prospective observational cohort study was conducted, involving 21 individuals with RIS recruited from a MS center. Baseline assessments, including mfVEP, magnetic resonance imaging (MRI), and clinical examinations, were performed, and participants were longitudinally followed for up to 24 months. The primary outcome measures were the conversion to MS. Over a clinical follow-up period of 24 months, five individuals (5/21) with RIS progressed to MS. MfVEP amplitude responses (interocular and monocular probability analysis) demonstrated abnormal cluster visual field defects in 47.6% of RIS eyes at baseline, whereas multifocal VEP latency analysis showed significant delays in 38.4%. A reduction in interocular amplitude [OR = 0.036, (95% CI 0.003-0.503); P = 0.014], monocular amplitude [OR = 0.083, (95% CI 0.007-0.982); P = 0.048], and a prolonged interocular latency [OR = 0.095, (95% CI 0.009-0.972); P = 0.047] were associated with a higher relative risk of clinical conversion at the 2-year follow-up. Multifocal VEP may serve as a novel and independent risk factor for predicting the conversion to MS in individuals with Radiologically Isolated Syndrome., (© 2024. The Author(s).)

Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely utilized to investigate plasticity mechanisms and functional reorganization in multiple sclerosis (MS). Among many resting state (RS) networks, a significant role is played by the salience network (SN, ventral attention network). Previous reports have demonstrated the involvement of osteopontin (OPN) in the pathogenesis of MS, which acts as a proinflammatory cytokine ultimately leading to neurodegeneration. Concentration of serum OPN was related to MRI findings 10.22±2.84 years later in 44 patients with MS. Local and interhemispheric correlations (LCOR, IHC), ROI-to-ROI and seed-based connectivity analyses were performed using serum OPN levels as independent variable along with age and gender as nuisance variables. We found significant associations between OPN levels and local correlation in right and left clusters encompassing the central opercular- and insular cortices (p-FDR = 0.0018 and p-FDR = 0.0205, respectively). Moreover, a significant association was identified between OPN concentration and interhemispheric correlation between central opercular- and insular cortices (p-FDR = 0.00015). Significant positive associations were found between OPN concentration and functional connectivity (FC) within the SN (FC strength between the anterior insula ventral division and 3 other insular regions, F(2,13) = 7.84, p-FDR = 0.0117). Seed-based connectivity analysis using the seven nodes of the SN resulted in several positive and inverse associations with OPN level. Serum OPN level may predict FC alterations within the SN in 10 years., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kakucs et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Damage or microstructural alterations of the white matter can cause dysfunction of the intrinsic neural networks in a condition termed as white matter disease (WMD). Frequently detected on brain computed tomography and magnetic resonance imaging scans, WMD is commonly presented in inflammatory demyelinating diseases like multiple sclerosis (MS) and vascular diseases such as cerebral small vessel disease (CSVD). Prevention of MS and CSVD progression requires early treatments with drastically different medications and approaches, as such, early and accurate diagnosis of WMD, derived from vascular or demyelinating etiologies, is of paramount importance. However, the clinical and imaging similarities between MS, especially during the early stage, and CSVD, pose a significant dilemma in differentiating these two conditions. In this review, we attempt to summarize and contrast the distinguishing features of MS and CSVD for aiding accurate diagnosis to ensure timely corresponding management in the early stages of MS and CSVD., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Although 7 T MRI research has contributed much to our understanding of multiple sclerosis (MS) pathology, most prior data has come from small, single-center studies with varying methods. In order to truly know if such findings have widespread applicability, multicenter methods and studies are needed. To address this, members of the North American Imaging in MS (NAIMS) Cooperative worked together to create a multicenter collaborative study of 7 T MRI in MS. In this manuscript, we describe the methods we have developed for the purpose of pooling together a large, retrospective dataset of 7 T MRIs acquired in multiple MS studies at five institutions. To date, this group has contributed five-hundred and twenty-eight 7 T MRI scans from 350 individuals with MS to a common data repository, with plans to continue to increase this sample size in the coming years. We have developed unified methods for image processing for data harmonization and lesion identification/segmentation. We report here our initial observations on intersite differences in acquisition, which includes site/device differences in brain coverage and image quality. We also report on the development of our methods and training of image evaluators, which resulted in median Dice Similarity Coefficients for trained raters' annotation of cortical and deep gray matter lesions, paramagnetic rim lesions, and meningeal enhancement between 0.73 and 0.82 compared to final consensus masks. We expect this publication to act as a resource for other investigators aiming to combine multicenter 7 T MRI datasets for the study of MS, in addition to providing a methodological reference for all future analysis projects to stem from the development of this dataset., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

The optic nerve is frequently involved in multiple sclerosis (MS). However, MRI of the optic nerve is considered optional in the differential diagnosis of optic neuropathy symptoms either at presentation or in established MS. In addition, unlike spinal cord imaging in comparable scenarios, no role is currently recommended for optic nerve MRI in patients presenting with optic neuritis for its confirmation, to plan therapeutic strategy, within the MS diagnostic framework, nor for the detection of subclinical activity in established MS. In this article, evidence related to these 3 aspects will be summarized and gaps in knowledge will be highlighted, including (1) the acquisition challenges and novel sequences that assess pathologic changes within the anterior visual pathways; (2) the clinical implications of quantitative magnetic resonance studies of the optic nerve, focusing on atrophy measures, magnetization transfer, and diffusion tensor imaging; and (3) the relevant clinical studies performed to date. Finally, an algorithm for the application of optic nerve MRI will be proposed to guide future studies aimed at addressing our knowledge gaps.

Background and Purpose: MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This study aimed to identify in vivo distinct MS lesion types using quantitative susceptibility mapping and susceptibility mapping-weighted imaging and to characterize them through T1-relaxometry, myelin mapping, and diffusion MR imaging. The spatial distribution of lesion phenotypes in relation to ventricular CSF was investigated., Materials and Methods: MS lesions of 53 individuals were categorized into iso- or hypointense lesions, hyperintense lesions, and paramagnetic rim lesions, on the basis of their appearance on quantitative susceptibility mapping alone, according to published criteria, and with the additional support of susceptibility mapping-weighted imaging. Susceptibility values, T1-relaxation times, myelin and free water fractions, intracellular volume fraction, and the orientation dispersion index were compared among lesion phenotypes. The distance of the geometric center of each lesion from the ventricular CSF was calculated., Results: Eight hundred ninety-six MS lesions underwent the categorization process using quantitative susceptibility mapping and susceptibility mapping-weighted imaging. The novel use of susceptibility mapping-weighted images, which revealed additional microvasculature details, led us to re-allocate several lesions to different categories, resulting in a 35.6% decrease in the number of paramagnetic rim lesions, a 22.5% decrease in hyperintense lesions, and a 17.2% increase in iso- or hypointense lesions, with respect to the categorization based on quantitative susceptibility mapping only. The outcome of the categorization based on the joint use of quantitative susceptibility mapping and susceptibility mapping-weighted imaging was that 44.4% of lesions were iso- or hypointense lesions, 47.9% were hyperintense lesions, and 7.7% were paramagnetic rim lesions. A worsening gradient was observed from iso- or hypointense lesions to hyperintense lesions to paramagnetic rim lesions in T1-relaxation times, myelin water fraction, free water fraction, and intracellular volume fraction. Paramagnetic rim lesions were located closer to ventricular CSF than iso- or hypointense lesions. The volume of hyperintense lesions was associated with a more severe disease course., Conclusions: Quantitative susceptibility mapping and susceptibility mapping-weighted imaging allow in vivo classification of MS lesions into different phenotypes, characterized by different levels of axonal and myelin loss and spatial distribution. Hyperintense lesions and paramagnetic rim lesions, which have the most severe microstructural damage, were more often observed in the periventricular WM and were associated with a more severe disease course., (© 2024 by American Journal of Neuroradiology.)

Spinal cord MRI plays an important role in the diagnosis and prognosis of multiple sclerosis (MS) and related disorders. The ANATOMICAL, pathologic, imaging and prognostic consideriations for the spinal cord for MS and the most important other demyelinating disorders, neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein-associated disease, are reviewed. Finally, differential diagnostic considerations of spinal cord MRI in MS and related disorders are discussed., Competing Interests: Disclosure None., (Copyright © 2024 Elsevier Inc. All rights reserved.)