Cognitive Impairment in Multiple Sclerosis: Past, Present, and Future

Cognitive impairment in multiple sclerosis (MS) is common and can have negative effects on quality of life. The clinical presentation can be more subtle and insidious. Thus, cognitive impairment is often underrecognized by both persons with MS (PwMS) and clinicians, leading to underestimation disability due to MS. Recent evidence supports that relapses affect cognition in a similar pattern to other physical relapse symptoms and may be the only symptom of a relapse. Regular screening using validated tests for PwMS will improve the care provided and quality of life of PwMS.

Routine MR Imaging Protocol and Standardization in Central Nervous System Demyelinating Diseases

Standardized MR imaging protocols are important for the diagnosis and monitoring of patients with multiple sclerosis (MS) and the appropriate use of MR imaging in routine clinical practice. Advances in using MR imaging to establish an earlier diagnosis of MS, safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MR imaging for diagnostic, prognostic, and monitoring purposes suggest a changing role of MR imaging for the management and care of MS patients. The MR imaging protocol emphasizes 3 dimensional acquisitions for optimal comparison over time.

Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging

Multiple sclerosis (MS) is increasingly understood not only as a white matter disease but also involving both the deep and cortical gray matter (GM). GM pathology in people with MS (pwMS) includes the presence of lesions, leptomeningeal inflammation, atrophy, altered iron concentration, and microstructural changes. Studies using 7T and 3T MR imaging with optimized protocols established that GM damage is a principal driver of disease progression in pwMS. Future work is needed to incorporate the assessment of these GM imaging biomarkers into the clinical workup of pwMS and the assessment of treatment efficacy.

Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis

BACKGROUND AND OBJECTIVES

The diagnosis of multiple sclerosis (MS) can be challenging in clinical practice because MS presentation can be atypical and mimicked by other diseases. We evaluated the diagnostic performance, alone or in combination, of the central vein sign (CVS), paramagnetic rim lesion (PRL), and cortical lesion (CL), as well as their association with clinical outcomes.

METHODS

In this multicenter observational study, we first conducted a cross-sectional analysis of the CVS (proportion of CVS-positive lesions or simplified determination of CVS in 3/6 lesions-Select3*/Select6*), PRL, and CL in MS and non-MS cases on 3T-MRI brain images, including 3D T2-FLAIR, T2*-echo-planar imaging magnitude and phase, double inversion recovery, and magnetization prepared rapid gradient echo image sequences. Then, we longitudinally analyzed the progression independent of relapse and MRI activity (PIRA) in MS cases over the 2 years after study entry. Receiver operating characteristic curves were used to test diagnostic performance and regression models to predict diagnosis and clinical outcomes.

RESULTS

The presence of ≥41% CVS-positive lesions/≥1 CL/≥1 PRL (optimal cutoffs) had 96%/90%/93% specificity, 97%/84%/60% sensitivity, and 0.99/0.90/0.77 area under the curve (AUC), respectively, to distinguish MS (n = 185) from non-MS (n = 100) cases. The Select3*/Select6* algorithms showed 93%/95% specificity, 97%/89% sensitivity, and 0.95/0.92 AUC. The combination of CVS, CL, and PRL improved the diagnostic performance, especially when Select3*/Select6* were used (93%/94% specificity, 98%/96% sensitivity, 0.99/0.98 AUC; p = 0.002/p < 0.001). In MS cases (n = 185), both CL and PRL were associated with higher MS disability and severity. Longitudinal analysis (n = 61) showed that MS cases with >4 PRL at baseline were more likely to experience PIRA at 2-year follow-up (odds ratio 17.0, 95% confidence interval: 2.1-138.5; p = 0.008), whereas no association was observed between other baseline MRI measures and PIRA, including the number of CL.

DISCUSSION

The combination of CVS, CL, and PRL can improve MS differential diagnosis. CL and PRL also correlated with clinical measures of poor prognosis, with PRL being a predictor of disability accrual independent of clinical/MRI activity.

Determinants and Biomarkers of Progression Independent of Relapses in Multiple Sclerosis

Clinical, pathological, and imaging evidence in multiple sclerosis (MS) suggests that a smoldering inflammatory activity is present from the earliest stages of the disease and underlies the progression of disability, which proceeds relentlessly and independently of clinical and radiological relapses (PIRA). The complex system of pathological events driving "chronic" worsening is likely linked with the early accumulation of compartmentalized inflammation within the central nervous system as well as insufficient repair phenomena and mitochondrial failure. These mechanisms are partially lesion-independent and differ from those causing clinical relapses and the formation of new focal demyelinating lesions; they lead to neuroaxonal dysfunction and death, myelin loss, glia alterations, and finally, a neuronal network dysfunction outweighing central nervous system (CNS) compensatory mechanisms. This review aims to provide an overview of the state of the art of neuropathological, immunological, and imaging knowledge about the mechanisms underlying the smoldering disease activity, focusing on possible early biomarkers and their translation into clinical practice. ANN NEUROL 2024;96:1-20.

Correlation between cognitive changes and neuroradiological changes over time in multiple sclerosis: a systematic review and meta-analysis

BACKGROUND

While many studies have examined relationships of neuroimaging variables to cognitive measures in multiple sclerosis (MS), longitudinal studies are lacking. The relationship of cognitive changes to neuroradiological changes in MS is thus incompletely understood. The present study systematically reviews all studies reporting a relationship between MRI changes and cognitive changes after at least one year of follow-up.

METHOD

An extensive and methodical search of online databases was conducted to identify qualified studies until August 2023. Among various cognitive tests and magnetic resonance imaging (MRI) measures, Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), verbal fluency, T2 lesion volume (T2LV), white matter lesion volume (WML), and grey matter volume (GMV) qualified for inclusion in a meta-analysis investigating the association of cognitive changes to neuroradiological changes.

RESULTS

We identified 35 studies that explored the link between MRI changes and changes in cognitive outcomes. Of these, twenty studies (57.14%) investigated the association between SDMT/PASAT and MRI metrics. Eleven studies (31.42%) focused on the relationship between MRI metrics and verbal learning and memory, while ten studies (28.57%) reported associations with visuospatial learning and memory. Furthermore, eight studies (22.85%) analyzed the correlation between verbal fluency and MRI measures. Only 5 were eligible for inclusion in the meta-analysis. The meta-analysis evaluated correlations between SDMT/PASAT and GMV (rs = 0.67, 95% CI 0.44-0.91), and verbal fluency and T2LV (rs = 0.35, 95% CI 0.09-0.60).

CONCLUSION

In this rigorously conducted systematic review, we found a significant association of cognitive changes, specifically SDMT/PASAT and verbal fluency, to changes in T2LV and atrophy in individuals with MS. Findings should be interpreted cautiously due to the limited amount of high-quality research, small sample sizes, and variability in study methodologies.

Reconciling lesions, relapses and smouldering associated worsening: A unifying model for multiple sclerosis pathogenesis

The failure of relapses and white matter lesions to properly explain long-term disability and progression in multiple sclerosis is compounded by its artificial separation into relapsing remitting, secondary progressive, and primary progressive pigeonholes. The well-known epidemiological disconnection between relapses and long-term disability progression has been rediscovered as "progression independent of relapse activity", i.e. smouldering multiple sclerosis. This smouldering associated worsening proceeds despite early and prolonged use of disease modification therapies, even those that are highly effective at preventing relapses and new/enhancing white matter lesions on MRI. We recognise that smouldering associated worsening and relapse/lesion associated worsening coexist, to varying extents. The extent of cortical demyelination has been shown to correlate significantly with the severity of diffuse injury in normal appearing white matter (post mortem histopathologically (r = 0.55; P = 0.001), and in vivo with MRI (r = -0.6874; P = 0.0006)) and does so independently of white matter lesion burden. Axon loss in the normal appearing white matter explains disability in multiple sclerosis better than focal white matter lesions do. Smouldering associated worsening typically manifests as a length-dependent central axonopathy. We propose a unifying model for multiple sclerosis pathogenesis, wherein accumulation of cortical lesion burden predisposes associated normal appearing white matter to diffuse injury, whilst also intensifying damage within white matter lesions. Our novel two-hit hypothesis implicates cortical disease as a culprit for smouldering multiple sclerosis, abetted by active focal inflammation in the white matter (and vice versa). Substantiation of the two-hit hypothesis would advance the importance of specific therapeutic intervention for (and monitoring of) cortical/meningeal inflammation in people with multiple sclerosis.

Digital Pathology Identifies Associations between Tissue Inflammatory Biomarkers and Multiple Sclerosis Outcomes

BACKGROUND

Multiple sclerosis (MS) is a clinically heterogeneous disease underpinned by inflammatory, demyelinating and neurodegenerative processes, the extent of which varies between individuals and over the course of the disease. Recognising the clinicopathological features that most strongly associate with disease outcomes will inform future efforts at patient phenotyping.

AIMS

We used a digital pathology workflow, involving high-resolution image acquisition of immunostained slides and opensource software for quantification, to investigate the relationship between clinical and neuropathological features in an autopsy cohort of progressive MS.

METHODS

Sequential sections of frontal, cingulate and occipital cortex, thalamus, brain stem (pons) and cerebellum including dentate nucleus (n = 35 progressive MS, females = 28, males = 7; age died = 53.5 years; range 38-98 years) were immunostained for myelin (anti-MOG), neurons (anti-HuC/D) and microglia/macrophages (anti-HLA). The extent of demyelination, neurodegeneration, the presence of active and/or chronic active lesions and quantification of brain and leptomeningeal inflammation was captured by digital pathology.

RESULTS

Digital analysis of tissue sections revealed the variable extent of pathology that characterises progressive MS. Microglia/macrophage activation, if found at a higher level in a single block, was typically elevated across all sampled blocks. Compartmentalised (perivascular/leptomeningeal) inflammation was associated with age-related measures of disease severity and an earlier death.

CONCLUSION

Digital pathology identified prognostically important clinicopathological correlations in MS. This methodology can be used to prioritise the principal pathological processes that need to be captured by future MS biomarkers.

Advanced MRI Techniques: Diagnosis and Follow-Up of Multiple Sclerosis

Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing-remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.

Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI

OBJECTIVES

Compelling evidence indicates a significant involvement of cortical lesions in the progressive phase of multiple sclerosis (MS), significantly contributing to late-stage disability. Despite the promise of ultra-high-field magnetic resonance imaging (MRI) in detecting cortical lesions, current evidence falls short in providing insights into the existence of such lesions during the early stages of MS or their underlying cause. This study delineated, at the early stage of MS, (1) the prevalence and spatial distribution of cortical lesions identified by 7 T MRI, (2) their relationship with white matter lesions, and (3) their clinical implications.

MATERIALS AND METHODS

Twenty individuals with early-stage relapsing-remitting MS (disease duration <1 year) underwent a 7 T MRI session involving T1-weighted MP2RAGE, T2*-weighted multiGRE, and T2-weighted FLAIR sequences for cortical and white matter segmentation. Disability assessments included the Expanded Disability Status Scale, the Multiple Sclerosis Functional Composite, and an extensive evaluation of cognitive function.

RESULTS

Cortical lesions were detected in 15 of 20 patients (75%). MP2RAGE revealed a total of 190 intracortical lesions (median, 4 lesions/case [range, 0-44]) and 216 leukocortical lesions (median, 2 lesions/case [range, 0-75]). Although the number of white matter lesions correlated with the total number of leukocortical lesions (r = 0.91, P < 0.001), no correlation was observed between the number of white matter or leukocortical lesions and the number of intracortical lesions. Furthermore, the number of leukocortical lesions but not intracortical or white-matter lesions was significantly correlated with cognitive impairment (r = 0.63, P = 0.04, corrected for multiple comparisons).

CONCLUSIONS

This study highlights the notable prevalence of cortical lesions at the early stage of MS identified by 7 T MRI. There may be a potential divergence in the underlying pathophysiological mechanisms driving distinct lesion types, notably between intracortical lesions and white matter/leukocortical lesions. Moreover, during the early disease phase, leukocortical lesions more effectively accounted for cognitive deficits.

Contribution of new and chronic cortical lesions to disability accrual in multiple sclerosis

Cortical lesions are common in multiple sclerosis and are associated with disability and progressive disease. We asked whether cortical lesions continue to form in people with stable white matter lesions and whether the association of cortical lesions with worsening disability relates to pre-existing or new cortical lesions. Fifty adults with multiple sclerosis and no new white matter lesions in the year prior to enrolment (33 relapsing-remitting and 17 progressive) and a comparison group of nine adults who had formed at least one new white matter lesion in the year prior to enrolment (active relapsing-remitting) were evaluated annually with 7 tesla (T) brain MRI and 3T brain and spine MRI for 2 years, with clinical assessments for 3 years. Cortical lesions and paramagnetic rim lesions were identified on 7T images. Seven total cortical lesions formed in 3/30 individuals in the stable relapsing-remitting group (median 0, range 0-5), four total cortical lesions formed in 4/17 individuals in the progressive group (median 0, range 0-1), and 16 cortical lesions formed in 5/9 individuals in the active relapsing-remitting group (median 1, range 0-10, stable relapsing-remitting versus progressive versus active relapsing-remitting P = 0.006). New cortical lesions were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Individuals with at least three paramagnetic rim lesions had a greater increase in cortical lesion volume over time (median 16 µl, range -61 to 215 versus median 1 µl, range -24 to 184, P = 0.007), but change in lesion volume was not associated with disability change. Baseline cortical lesion volume was higher in people with worsening disability (median 1010 µl, range 13-9888 versus median 267 µl, range 0-3539, P = 0.001, adjusted for age and sex) and in individuals with relapsing-remitting multiple sclerosis who subsequently transitioned to secondary progressive multiple sclerosis (median 2183 µl, range 270-9888 versus median 321 µl, range 0-6392 in those who remained relapsing-remitting, P = 0.01, adjusted for age and sex). Baseline white matter lesion volume was not associated with worsening disability or transition from relapsing-remitting to secondary progressive multiple sclerosis. Cortical lesion formation is rare in people with stable white matter lesions, even in those with worsening disability. Cortical but not white matter lesion burden predicts disability worsening, suggesting that disability progression is related to long-term effects of cortical lesions that form early in the disease, rather than to ongoing cortical lesion formation.

LST-AI: A deep learning ensemble for accurate MS lesion segmentation

Automated segmentation of brain white matter lesions is crucial for both clinical assessment and scientific research in multiple sclerosis (MS). Over a decade ago, we introduced an engineered lesion segmentation tool, LST. While recent lesion segmentation approaches have leveraged artificial intelligence (AI), they often remain proprietary and difficult to adopt. As an open-source tool, we present LST-AI, an advanced deep learning-based extension of LST that consists of an ensemble of three 3D U-Nets. LST-AI explicitly addresses the imbalance between white matter (WM) lesions and non-lesioned WM. It employs a composite loss function incorporating binary cross-entropy and Tversky loss to improve segmentation of the highly heterogeneous MS lesions. We train the network ensemble on 491 MS pairs of T1-weighted and FLAIR images, collected in-house from a 3T MRI scanner, and expert neuroradiologists manually segmented the utilized lesion maps for training. LST-AI also includes a lesion location annotation tool, labeling lesions as periventricular, infratentorial, and juxtacortical according to the 2017 McDonald criteria, and, additionally, as subcortical. We conduct evaluations on 103 test cases consisting of publicly available data using the Anima segmentation validation tools and compare LST-AI with several publicly available lesion segmentation models. Our empirical analysis shows that LST-AI achieves superior performance compared to existing methods. Its Dice and F1 scores exceeded 0.62, outperforming LST, SAMSEG (Sequence Adaptive Multimodal SEGmentation), and the popular nnUNet framework, which all scored below 0.56. Notably, LST-AI demonstrated exceptional performance on the MSSEG-1 challenge dataset, an international WM lesion segmentation challenge, with a Dice score of 0.65 and an F1 score of 0.63-surpassing all other competing models at the time of the challenge. With increasing lesion volume, the lesion detection rate rapidly increased with a detection rate of >75% for lesions with a volume between 10 mm3 and 100 mm3. Given its higher segmentation performance, we recommend that research groups currently using LST transition to LST-AI. To facilitate broad adoption, we are releasing LST-AI as an open-source model, available as a command-line tool, dockerized container, or Python script, enabling diverse applications across multiple platforms.

A novel imaging marker of cortical "cellularity" in multiple sclerosis patients

Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model ("soma and neurite density imaging (SANDI)") to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (fsoma)-a marker of cellularity-in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI fsoma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI fsoma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI fsoma in the outer part of the cortex compared to relapsing-remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing-remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI fsoma and serum neurofilament light chain-a biomarker of inflammatory axonal damage-suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI fsoma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients.

Predictors of multiple sclerosis progression: A systematic review of conventional magnetic resonance imaging studies

INTRODUCTION

Multiple Sclerosis (MS) is a chronic neurodegenerative disorder that affects the central nervous system (CNS) and results in progressive clinical disability and cognitive decline. Currently, there are no specific imaging parameters available for the prediction of longitudinal disability in MS patients. Magnetic resonance imaging (MRI) has linked imaging anomalies to clinical and cognitive deficits in MS. In this study, we aimed to evaluate the effectiveness of MRI in predicting disability, clinical progression, and cognitive decline in MS.

METHODS

In this study, according to PRISMA guidelines, we comprehensively searched the Web of Science, PubMed, and Embase databases to identify pertinent articles that employed conventional MRI in the context of Relapsing-Remitting and progressive forms of MS. Following a rigorous screening process, studies that met the predefined inclusion criteria were selected for data extraction and evaluated for potential sources of bias.

RESULTS

A total of 3028 records were retrieved from database searching. After a rigorous screening, 53 records met the criteria and were included in this study. Lesions and alterations in CNS structures like white matter, gray matter, corpus callosum, thalamus, and spinal cord, may be used to anticipate disability progression. Several prognostic factors associated with the progression of MS, including presence of cortical lesions, changes in gray matter volume, whole brain atrophy, the corpus callosum index, alterations in thalamic volume, and lesions or alterations in cross-sectional area of the spinal cord. For cognitive impairment in MS patients, reliable predictors include cortical gray matter volume, brain atrophy, lesion characteristics (T2-lesion load, temporal, frontal, and cerebellar lesions), white matter lesion volume, thalamic volume, and corpus callosum density.

CONCLUSION

This study indicates that MRI can be used to predict the cognitive decline, disability progression, and disease progression in MS patients over time.

LST-AI: a Deep Learning Ensemble for Accurate MS Lesion Segmentation

Automated segmentation of brain white matter lesions is crucial for both clinical assessment and scientific research in multiple sclerosis (MS). Over a decade ago, we introduced an engineered lesion segmentation tool, LST. While recent lesion segmentation approaches have leveraged artificial intelligence (AI), they often remain proprietary and difficult to adopt. As an open-source tool, we present LST-AI, an advanced deep learning-based extension of LST that consists of an ensemble of three 3D-UNets. LST-AI explicitly addresses the imbalance between white matter (WM) lesions and non-lesioned WM. It employs a composite loss function incorporating binary cross-entropy and Tversky loss to improve segmentation of the highly heterogeneous MS lesions. We train the network ensemble on 491 MS pairs of T1w and FLAIR images, collected in-house from a 3T MRI scanner, and expert neuroradiologists manually segmented the utilized lesion maps for training. LST-AI additionally includes a lesion location annotation tool, labeling lesion location according to the 2017 McDonald criteria (periventricular, infratentorial, juxtacortical, subcortical). We conduct evaluations on 103 test cases consisting of publicly available data using the Anima segmentation validation tools and compare LST-AI with several publicly available lesion segmentation models. Our empirical analysis shows that LST-AI achieves superior performance compared to existing methods. Its Dice and F1 scores exceeded 0.62, outperforming LST, SAMSEG (Sequence Adaptive Multimodal SEGmentation), and the popular nnUNet framework, which all scored below 0.56. Notably, LST-AI demonstrated exceptional performance on the MSSEG-1 challenge dataset, an international WM lesion segmentation challenge, with a Dice score of 0.65 and an F1 score of 0.63-surpassing all other competing models at the time of the challenge. With increasing lesion volume, the lesion detection rate rapidly increased with a detection rate of >75% for lesions with a volume between 10mm3 and 100mm3. Given its higher segmentation performance, we recommend that research groups currently using LST transition to LST-AI. To facilitate broad adoption, we are releasing LST-AI as an open-source model, available as a command-line tool, dockerized container, or Python script, enabling diverse applications across multiple platforms.

Prognostic relevance of MRI in early relapsing multiple sclerosis: ready to guide treatment decision making?

Magnetic resonance imaging (MRI) of the brain and spinal cord plays a crucial role in the diagnosis and monitoring of multiple sclerosis (MS). There is conclusive evidence that brain and spinal cord MRI findings in early disease stages also provide relevant insight into individual prognosis. This includes prediction of disease activity and disease progression, the accumulation of long-term disability and the conversion to secondary progressive MS. The extent to which these MRI findings should influence treatment decisions remains a subject of ongoing discussion. The aim of this review is to present and discuss the current knowledge and scientific evidence regarding the utility of MRI at early MS disease stages for prognostic classification of individual patients. In addition, we discuss the current evidence regarding the use of MRI in order to predict treatment response. Finally, we propose a potential approach as to how MRI data may be categorized and integrated into early clinical decision making.

Prevalence, Demographic, and Clinical Factors Associated With Cognitive Dysfunction in Patients With Neuromyelitis Optica Spectrum Disorder

BACKGROUND AND OBJECTIVES

Neuromyelitis optica spectrum disorder (NMOSD) is a chronic CNS demyelinating autoimmune disorder targeting the astrocyte antigen aquaporin-4 (AQP4), typically presenting with optic neuritis, transverse myelitis, and brain syndromes. Cognitive dysfunction (CD) in NMOSD is under-recognized and poorly understood. The purpose of this study was to evaluate the prevalence and clinical variables associated with CD in NMOSD.

METHODS

This observational retrospective study with longitudinal follow-up describes a clinical cohort seen in the Collaborative International Research in Clinical and Longitudinal Experience Study in NMOSD. Serial Montreal Cognitive Assessments (MoCAs) were performed upon enrollment and at 6-month intervals to evaluate longitudinal cognitive function relative to demographic and disease-related factors. We used 2-tailed t test, analysis of variance, the χ2 test, linear regression for univariable and adjusted analyses and simultaneous linear regression and mixed-effects model for multivariable analyses.

RESULTS

Thirty-four percent (75/219) of patients met criteria for CD (MoCA <26); 29% (64/219) showed mild dysfunction (MoCA 20-26/30), and 5% (11/219) showed moderate (MoCA <20/30) dysfunction. Patients with less neurologic disability and lower pain scores had higher MoCA scores (95% CI 0.24-0.65 and 95% CI 0.09-0.42, respectively). Patients with at least high school education scored higher on the MoCA (95% CI 2.2-5). When comparing patients dichotomized for CD, patients never on rituximab scored higher than patients only treated with rituximab (p < 0.029). There was no significant association between annualized relapse rate, age, sex, disease duration, AQP4 serostatus or brain lesions, and CD. CD was more pronounced among Black than White patients (95% CI -2.7 to -0.7). Multivariable analysis of serial MoCA did not indicate change (p = 0.715). Descriptive analysis of serial MoCA showed 30% (45/150) of patients with worsening MoCA performance had impaired language and verbal recall.

DISCUSSION

To our knowledge, this is the largest study of diverse cohort to investigate CD in patients with NMOSD. Our findings demonstrate 34% of patients with NMOSD experience mild-to-moderate CD, while 30% of patients demonstrated decline on serial testing. The substantial prevalence of CD in this pilot report highlights the need for improved and validated screening tools and comprehensive measures to investigate CD in NMOSD.

The elusive nature of the oligoclonal bands in multiple sclerosis

Intrathecal immunoglobulin G (IgG) and oligoclonal bands (OCBs) detected in both the brain and cerebrospinal fluid (CSF) are seminal features of multiple sclerosis (MS). The presence of OCBs correlates with elevated disease burden and severity and supports the diagnosis of MS. Despite numerous investigations into the potential viral and autoantigen targets, the precise antigenic specificity of OCBs has remained elusive. We have little knowledge of the nature regarding these oligoclonal IgG bands. Here, we present compelling evidence highlighting the key findings that both OCBs and intrathecal IgG antibodies are under genetic control and that OCBs originate from clonal B-cells in both the periphery and CNS. We propose that MS OCBs are IgG immune complexes composed of IgG1 and IgG3 antibodies and that the pathological role of OCB stems from the IgG effector functions of these complexes, leading to demyelination and axonal injuries. We present additional evidence regarding the nature of MS OCBs: (1) disease-modifying therapies have been shown to affect CSF OCB; (2) OCBs have also been detected in several neuroinfectious diseases; (3) Epstein-Barr virus (EBV) has been particularly linked with MS pathogenesis, and its association with OCB is an important area of study. Although OCBs are closely associated with MS, more meticulously planned research is necessary to clarify the precise role of OCB in MS, both in terms of disease pathogenesis and diagnosis.

Disease activity in primary progressive multiple sclerosis: a systematic review and meta-analysis

Background

Disease activity in multiple sclerosis (MS) is defined as presence of relapses, gadolinium enhancing lesions and/or new or enlarging lesions on MRI. It is associated with efficacy of immunomodulating therapies (IMTs) in primary progressive MS (PPMS). However, a thorough review on disease activity in PPMS is lacking. In relapsing remitting MS, the prevalence of activity decreases in more contemporary cohorts. For PPMS, this is unknown.

Aim

To review disease activity in PPMS cohorts and identify its predictors.

Methods

A systematic search in EMBASE, MEDLINE, Web of science Core Collection, COCHRANE CENTRAL register of trials, and GOOGLE SCHOLAR was performed. Keywords included PPMS, inflammation, and synonyms. We included original studies with predefined available data, extracted cohort characteristics and disease activity outcomes and performed meta-regression analyses.

Results

We included 34 articles describing 7,109 people with PPMS (pwPPMS). The weighted estimated proportion of pwPPMS with overall disease activity was 26.8% (95% CI 20.6-34.0%). A lower age at inclusion predicted higher disease activity (OR 0.91, p = 0.031). Radiological activity (31.9%) was more frequent than relapses (9.2%), and was predicted by longer follow-up duration (OR 1.27, p = 0.033). Year of publication was not correlated with disease activity.

Conclusion

Inflammatory disease activity is common in PPMS and has remained stable over the last decades. Age and follow-up duration predict disease activity, advocating prolonged monitoring of young pwPPMS to evaluate potential IMT benefits.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis

Background and objectives

Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL.

Methods

A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2.

Results

59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010μl, range 13-9888 vs median 267μl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183μl, range 270-9888 vs median 321μl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS.

Discussion

CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.

MRI to differentiate multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease

Differentiating multiple sclerosis (MS) from other relapsing inflammatory autoimmune diseases of the central nervous system such as neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is crucial in clinical practice. The differential diagnosis may be challenging but making the correct ultimate diagnosis is critical, since prognosis and treatments differ, and inappropriate therapy may promote disability. In the last two decades, significant advances have been made in MS, NMOSD, and MOGAD including new diagnostic criteria with better characterization of typical clinical symptoms and suggestive imaging (magnetic resonance imaging [MRI]) lesions. MRI is invaluable in making the ultimate diagnosis. An increasing amount of new evidence with respect to the specificity of observed lesions as well as the associated dynamic changes in the acute and follow-up phase in each condition has been reported in distinct studies recently published. Additionally, differences in brain (including the optic nerve) and spinal cord lesion patterns between MS, aquaporin4-antibody-positive NMOSD, and MOGAD have been described. We therefore present a narrative review on the most relevant findings in brain, spinal cord, and optic nerve lesions on conventional MRI for distinguishing adult patients with MS from NMOSD and MOGAD in clinical practice. In this context, cortical and central vein sign lesions, brain and spinal cord lesions characteristic of MS, NMOSD, and MOGAD, optic nerve involvement, role of MRI at follow-up, and new proposed diagnostic criteria to differentiate MS from NMOSD and MOGAD were discussed.

Functional and structural brain MRI changes associated with cognitive worsening in multiple sclerosis: a 3-year longitudinal study

BACKGROUND

Heterogeneous processes may contribute to cognitive impairment in multiple sclerosis (MS).

OBJECTIVE

To apply a longitudinal multiparametric MRI approach to identify mechanisms associated with cognitive worsening in MS patients.

METHODS

3 T brain functional and structural MRI scans were acquired at baseline and after a median follow-up of 3.4 years in 35 MS patients and 22 healthy controls (HC). Associations between cognitive worsening (reliable change index score < - 1.25 at the Rao's battery) and longitudinal changes in regional T2-hyperintense white matter (WM) lesions, diffusion tensor microstructural WM damage, gray matter (GM) atrophy and resting state (RS) functional connectivity (FC) were explored.

RESULTS

At follow-up, HC showed no clusters of significant microstructural WM damage progression, GM atrophy or changes in RS FC. At follow-up, 10 MS patients (29%) showed cognitive worsening. Compared to cognitively stable, cognitively worsened MS patients showed more severe GM atrophy of the right anterior cingulate cortex and bilateral supplementary motor area (p < 0.001). Cognitively worsened vs cognitively stable MS patients showed also decreased RS FC in the right hippocampus of the right working memory network and in the right insula of the default mode network. Increased RS FC in the left insula of the executive control network was found in the opposite comparison (p < 0.001). No significant regional accumulation of focal WM lesions nor microstructural WM abnormalities occurred in both patients' groups.

CONCLUSIONS

GM atrophy progression in cognitively relevant brain regions combined with functional impoverishment in networks involved in cognitive functions may represent the substrates underlying cognitive worsening in MS.

Measuring Pathology in Patients with Multiple Sclerosis Using Positron Emission Tomography

PURPOSE OF REVIEW

Multiple sclerosis is characterized by a diverse and complex pathology. Clinical relapses, the hallmark of the disease, are accompanied by focal white matter lesions with intense inflammatory and demyelinating activity. Prevention of these relapses has been the major focus of pharmaceutical development, and it is now possible to dramatically reduce this inflammatory activity. Unfortunately, disability accumulation persists for many people living with multiple sclerosis owing to ongoing damage within existing lesions, pathology outside of discrete lesions, and other yet unknown factors. Understanding this complex pathological cascade will be critical to stopping progressive multiple sclerosis. Positron emission tomography uses biochemically specific radioligands to quantitatively measure pathological processes with molecular specificity. This review examines recent advances in the understanding of multiple sclerosis facilitated by positron emission tomography and identifies future avenues to expand understanding and treatment options.

RECENT FINDINGS

An increasing number of radiotracers allow for the quantitative measurement of inflammatory abnormalities, de- and re-myelination, and metabolic disruption associated with multiple sclerosis. The studies have identified contributions of ongoing, smoldering inflammation to accumulating tissue injury and clinical worsening. Myelin studies have quantified the dynamics of myelin loss and recovery. Lastly, metabolic changes have been found to contribute to symptom worsening. The molecular specificity facilitated by positron emission tomography in people living with multiple sclerosis will critically inform efforts to modulate the pathology leading to progressive disability accumulation. Existing studies show the power of this approach applied to multiple sclerosis. This armamentarium of radioligands allows for new understanding of how the brain and spinal cord of people is impacted by multiple sclerosis.

Emerging imaging and liquid biomarkers in multiple sclerosis

The advent of highly effective disease modifying therapy has transformed the landscape of multiple sclerosis (MS) care over the last two decades. However, there remains a critical, unmet need for sensitive and specific biomarkers to aid in diagnosis, prognosis, treatment monitoring, and the development of new interventions, particularly for people with progressive disease. This review evaluates the current data for several emerging imaging and liquid biomarkers in people with MS. MRI findings such as the central vein sign and paramagnetic rim lesions may improve MS diagnostic accuracy and evaluation of therapy efficacy in progressive disease. Serum and cerebrospinal fluid levels of several neuroglial proteins, such as neurofilament light chain and glial fibrillary acidic protein, show potential to be sensitive biomarkers of pathologic processes such as neuro-axonal injury or glial-inflammation. Additional promising biomarkers, including optical coherence tomography, cytokines and chemokines, microRNAs, and extracellular vesicles/exosomes, are also reviewed, among others. Beyond their potential integration into MS clinical care and interventional trials, several of these biomarkers may be informative of MS pathogenesis and help elucidate novel targets for treatment strategies.

Depressive symptoms, anxiety and cognitive impairment: emerging evidence in multiple sclerosis

Neuropsychiatric abnormalities may be broadly divided in two categories: disorders of mood, affect, and behavior and abnormalities affecting cognition. Among these conditions, clinical depression, anxiety and neurocognitive disorders are the most common in multiple sclerosis (MS), with a substantial impact on patients' quality of life and adherence to treatments. Such manifestations may occur from the earliest phases of the disease but become more frequent in MS patients with a progressive disease course and more severe clinical disability. Although the pathogenesis of these neuropsychiatric manifestations has not been fully defined yet, brain structural and functional abnormalities, consistently observed with magnetic resonance imaging (MRI), together with genetic and immunologic factors, have been suggested to be key players. Even though the detrimental clinical impact of such manifestations in MS patients is a matter of crucial importance, at present, they are often overlooked in the clinical setting. Moreover, the efficacy of pharmacologic and non-pharmacologic approaches for their amelioration has been poorly investigated, with the majority of studies showing marginal or no beneficial effect of different therapeutic approaches, possibly due to the presence of multiple and heterogeneous underlying pathological mechanisms and intrinsic methodological limitations. A better evaluation of these manifestations in the clinical setting and improvements in the understanding of their pathophysiology may offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. This review provides an updated overview regarding the pathophysiology of the most common neuropsychiatric symptoms in MS, the clinical and MRI characteristics that have been associated with mood disorders (i.e., depression and anxiety) and cognitive impairment, and the treatment approaches currently available or under investigation.

Meningeal inflammation as a driver of cortical grey matter pathology and clinical progression in multiple sclerosis

Growing evidence from cerebrospinal fluid samples and post-mortem brain tissue from individuals with multiple sclerosis (MS) and rodent models indicates that the meninges have a key role in the inflammatory and neurodegenerative mechanisms underlying progressive MS pathology. The subarachnoid space and associated perivascular spaces between the membranes of the meninges are the access points for entry of lymphocytes, monocytes and macrophages into the brain parenchyma, and the main route for diffusion of inflammatory and cytotoxic molecules from the cerebrospinal fluid into the brain tissue. In addition, the meningeal spaces act as an exit route for CNS-derived antigens, immune cells and metabolites. A number of studies have demonstrated an association between chronic meningeal inflammation and a more severe clinical course of MS, suggesting that the build-up of immune cell aggregates in the meninges represents a rational target for therapeutic intervention. Therefore, understanding the precise cell and molecular mechanisms, timing and anatomical features involved in the compartmentalization of inflammation within the meningeal spaces in MS is vital. Here, we present a detailed review and discussion of the cellular, molecular and radiological evidence for a role of meningeal inflammation in MS, alongside the clinical and therapeutic implications.

Pre-training working memory/information processing capabilities and brain atrophy limit the improving effects of cognitive training

Background

Computerized training in persons with multiple sclerosis (PwMS) seems to enhance working memory (WM)/information processing (IP), but factors associated with the efficacy of the treatment have not been sufficiently explored. Objective: To identify clinical and radiological characteristics associated with positive WM/IP training responses.

Methods

Radiological and neuropsychological assessments were carried out on a sample of 35 PwMs who were divided into "WM/IP-impaired" and "WM/IP-preserved." All participants underwent adaptive n-back training for 10 days and were assessed post-training. Between-group differences ("WM/IP-impaired" vs. "WM/IP-preserved") in training-induced cognitive improvement were assessed and exploratory correlational/ regression-based methods were employed to assess the relationship between cognitive improvement and clinical and radiological variables.

Results

All PwMS exhibited WM/IP benefits after training, but those with preserved WM/IP functions showed greater positive effects as well as transfer effects to other WM/IP tests when compared to the impaired group. Additional analyses revealed that positive response to treatment was associated with WM/IP baseline capabilities and greater gray matter volume (GMVOL) in relevant areas such as the thalamus.

Conclusions

Restorative cognitive training is suitable to improve cognition in PwMS but its effective outcome differs depending on the baseline WM/IP capabilities and GMVOL.

Longitudinal Assessment of Multiple Sclerosis Lesion Load With Synthetic Magnetic Resonance Imaging-A Multicenter Validation Study

INTRODUCTION

Double inversion recovery (DIR) has been validated as a sensitive magnetic resonance imaging (MRI) contrast in multiple sclerosis (MS). Deep learning techniques can use basic input data to generate synthetic DIR (synthDIR) images that are on par with their acquired counterparts. As assessment of longitudinal MRI data is paramount in MS diagnostics, our study's purpose is to evaluate the utility of synthDIR longitudinal subtraction imaging for detection of disease progression in a multicenter data set of MS patients.

METHODS

We implemented a previously established generative adversarial network to synthesize DIR from input T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences for 214 MRI data sets from 74 patients and 5 different centers. One hundred and forty longitudinal subtraction maps of consecutive scans (follow-up scan-preceding scan) were generated for both acquired FLAIR and synthDIR. Two readers, blinded to the image origin, independently quantified newly formed lesions on the FLAIR and synthDIR subtraction maps, grouped into specific locations as outlined in the McDonald criteria.

RESULTS

Both readers detected significantly more newly formed MS-specific lesions in the longitudinal subtractions of synthDIR compared with acquired FLAIR (R1: 3.27 ± 0.60 vs 2.50 ± 0.69 [ P = 0.0016]; R2: 3.31 ± 0.81 vs 2.53 ± 0.72 [ P < 0.0001]). Relative gains in detectability were most pronounced in juxtacortical lesions (36% relative gain in lesion counts-pooled for both readers). In 5% of the scans, synthDIR subtraction maps helped to identify a disease progression missed on FLAIR subtraction maps.

CONCLUSIONS

Generative adversarial networks can generate high-contrast DIR images that may improve the longitudinal follow-up assessment in MS patients compared with standard sequences. By detecting more newly formed MS lesions and increasing the rates of detected disease activity, our methodology promises to improve clinical decision-making.

Evaluation of BAFF, APRIL and CD40L in Ocrelizumab-Treated pwMS and Infectious Risk

BACKGROUND

The anti-CD20 monoclonal antibody ocrelizumab has been widely employed in the treatment of people with multiple sclerosis (pwMS). However, its B-cell-depleting effect may induce a higher risk of infectious events and alterations in the secretion of B-cell-activating factors, such as BAFF, APRIL and CD40L.

METHODS

The aim of this study was to investigate plasma BAFF, APRIL and CD40L levels and their relationship with infectious risk in ocrelizumab-treated pwMS at baseline (T0), at 6 months (T6) and at 12 months (T12) after starting the treatment. As a control group, healthy donors (HD) were enrolled too.

RESULTS

A total of 38 pwMS and 26 HD were enrolled. At baseline, pwMS showed higher plasma BAFF (p < 0.0001), APRIL (p = 0.0223) and CD40L (p < 0.0001) levels compared to HD. Compared to T0, plasma BAFF levels were significantly increased at both T6 and T12 (p < 0.0001 and p < 0.0001, respectively). Whereas plasma APRIL and CD40L levels were decreased at T12 (p = 0.0003 and p < 0.0001, respectively). When stratifying pwMS according to the development of an infectious event during the 12-month follow-up period in two groups-with (14) and without an infectious event (24)-higher plasma BAFF levels were observed at all time-points; significantly, in the group with an infectious event compared to the group without an infectious event (T0: p < 0.0001, T6: p = 0.0056 and T12: p = 0.0400). Conclusions: BAFF may have a role as a marker of immune dysfunction and of infectious risk.

A vision of 14 T MR for fundamental and clinical science

OBJECTIVE

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

RESEARCH FIELDS

The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

CONCLUSIONS

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Quantitative magnetic resonance imaging biomarkers for cortical pathology in multiple sclerosis at 7 T

Substantial cortical gray matter tissue damage, which correlates with clinical disease severity, has been revealed in multiple sclerosis (MS) using advanced magnetic resonance imaging (MRI) methods at 3 T and the use of ultra-high field, as well as in histopathology studies. While clinical assessment mainly focuses on lesions using T 1 - and T 2 -weighted MRI, quantitative MRI (qMRI) methods are capable of uncovering subtle microstructural changes. The aim of this ultra-high field study is to extract possible future MR biomarkers for the quantitative evaluation of regional cortical pathology. Because of their sensitivity to iron, myelin, and in part specifically to cortical demyelination, T 1 , T 2 , R 2 * , and susceptibility mapping were performed including two novel susceptibility markers; in addition, cortical thickness as well as the volumes of 34 cortical regions were computed. Data were acquired in 20 patients and 16 age- and sex-matched healthy controls. In 18 cortical regions, large to very large effect sizes (Cohen's d ≥ 1) and statistically significant differences in qMRI values between patients and controls were revealed compared with only four regions when using more standard MR measures, namely, volume and cortical thickness. Moreover, a decrease in all susceptibility contrasts ( χ , χ + , χ - ) and R 2 * values indicates that the role of cortical demyelination might outweigh inflammatory processes in the form of iron accumulation in cortical MS pathology, and might also indicate iron loss. A significant association between susceptibility contrasts as well as R 2 * of the caudal middle frontal gyrus and disease duration was found (adjusted R² : 0.602, p = 0.0011). Quantitative MRI parameters might be more sensitive towards regional cortical pathology compared with the use of conventional markers only and therefore may play a role in early detection of tissue damage in MS in the future.

Recent Progress in the Identification of Early Transition Biomarkers from Relapsing-Remitting to Progressive Multiple Sclerosis

Despite extensive research into the pathophysiology of multiple sclerosis (MS) and recent developments in potent disease-modifying therapies (DMTs), two-thirds of relapsing-remitting MS patients transition to progressive MS (PMS). The main pathogenic mechanism in PMS is represented not by inflammation but by neurodegeneration, which leads to irreversible neurological disability. For this reason, this transition represents a critical factor for the long-term prognosis. Currently, the diagnosis of PMS can only be established retrospectively based on the progressive worsening of the disability over a period of at least 6 months. In some cases, the diagnosis of PMS is delayed for up to 3 years. With the approval of highly effective DMTs, some with proven effects on neurodegeneration, there is an urgent need for reliable biomarkers to identify this transition phase early and to select patients at a high risk of conversion to PMS. The purpose of this review is to discuss the progress made in the last decade in an attempt to find such a biomarker in the molecular field (serum and cerebrospinal fluid) between the magnetic resonance imaging parameters and optical coherence tomography measures.

Cortical lesions at diagnosis predict long-term cognitive impairment in multiple sclerosis: A 20-year study

BACKGROUND AND PURPOSE

Although cognitive impairment (CI) is frequent in multiple sclerosis (MS) patients, few studies (and with conflicting results) have evaluated early predictors of CI in the long term. We aimed at determining associations between early clinical/neuroradiological variables with reference to CI after 20 years of MS.

METHODS

We investigated in 170 MS patients the relationship between clinical/magnetic resonance imaging (MRI) data at diagnosis and cognitive status almost 20 years after MS onset. Among others, number and volume of both white matter lesions (WMLs) and cortical lesions (CLs) were evaluated at diagnosis and after 2 years. All MS patients were followed over time and underwent a comprehensive neuropsychological assessment at the end of study. Advanced statistical methods (unsupervised cluster analysis and random forest model) were conducted.

RESULTS

CI patients showed higher focal cortical pathology at diagnosis compared to cognitively normal subjects (p < 0.001). Volumes of both WMLs and CLs emerged as the MRI metrics most associated with long-term CI. Moreover, number of CLs (especially ≥3) was also strongly associated with long-term CI (≥3 CLs: odds ratio [OR] = 3.7, 95% confidence interval = 1.8-7.5, p < 0.001), more than number of WMLs; the optimal cutoff of three CLs (area under the curve = 0.67, specificity = 75%, sensitivity = 55%) was estimated according to the risk of developing CI.

CONCLUSIONS

These results highlight the impact of considering both white and gray matter focal damage from early MS stages. Given the low predictive value of WML number and the poor clinical applicability of lesion volume estimation in the daily clinical context, the evaluation of number of CLs could represent a reliable prognostic marker of CI.

Neurodegeneration in multiple sclerosis

Axonal loss in multiple sclerosis (MS) is a key component of disease progression and permanent neurologic disability. MS is a heterogeneous demyelinating and neurodegenerative disease of the central nervous system (CNS) with varying presentation, disease courses, and prognosis. Immunomodulatory therapies reduce the frequency and severity of inflammatory demyelinating events that are a hallmark of MS, but there is minimal therapy to treat progressive disease and there is no cure. Data from patients with MS, post-mortem histological analysis, and animal models of demyelinating disease have elucidated patterns of MS pathogenesis and underlying mechanisms of neurodegeneration. MRI and molecular biomarkers have been proposed to identify predictors of neurodegeneration and risk factors for disease progression. Early signs of axonal dysfunction have come to light including impaired mitochondrial trafficking, structural axonal changes, and synaptic alterations. With sustained inflammation as well as impaired remyelination, axons succumb to degeneration contributing to CNS atrophy and worsening of disease. These studies highlight the role of chronic demyelination in the CNS in perpetuating axonal loss, and the difficulty in promoting remyelination and repair amidst persistent inflammatory insult. Regenerative and neuroprotective strategies are essential to overcome this barrier, with early intervention being critical to rescue axonal integrity and function. The clinical and basic research studies discussed in this review have set the stage for identifying key propagators of neurodegeneration in MS, leading the way for neuroprotective therapeutic development. This article is categorized under: Immune System Diseases > Molecular and Cellular Physiology Neurological Diseases > Molecular and Cellular Physiology.

Making Visible the Invisible: Automatically Measured Global and Regional Brain Volume Is Associated with Cognitive Impairment and Fatigue in Multiple Sclerosis

In multiple sclerosis (MS), the transition from relapsing-remitting to the secondary-progressive phase is characterized by a progression independent of relapse activity (PIRA), resulting in physical disability accumulation and invisible symptoms, i.e., fatigue and cognitive impairment (CI). These symptoms are related to neurodegenerative processes and have been correlated with MRI measures of brain atrophy only at a group level; however, the application in clinical practice of atrophy-based measurements for single-patient evaluation is yet to be fully investigated. In the present study, we aimed to evaluate the association between brain atrophy, measured with easy-to-use automatic software, and the "invisible" MS symptoms of cognition and fatigue. A total of 69 MS patients were included in the study; cognitive impairment and fatigue (FSS) (in addition to neurological disability, EDSS) were assessed and correlated with brain volumes calculated using the automated software QyScore^® which is validated for single-patient use in the clinical setting. Results showed that the cognitive status was accurately reflected by measures of atrophy, with a sensitivity of up to 90%. CI patients showed a lower volume compared to cognitively normal patients in the whole brain (p = 0.017), gray matter (p = 0.042), insula (p = 0.035), cerebellum (p = 0.008), and limbic lobe (p = 0.049). FSS was associated with temporal lobe (r = -0.37, p = 0.013) and insular (r = -0.36, p = 0.019) volumes. The volumes of the same regions were also associated with EDSS. The global/regional atrophy results, assessed with automatic and easy-to-use software, correlated with cognitive and fatigue symptoms, thus supporting the clinical application in routine patient management.

Immunomodulators and immunosuppressants for progressive multiple sclerosis: a network meta‐analysis

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

We will perform a network meta‐analysis to assess the relative effectiveness and safety of immunomodulatory and immunosuppressive treatments for people with multiple sclerosis in progressive forms of the condition.

Association of spinal cord lesions with cognition in multiple sclerosis

Purpose: The effect of spinal cord involvement, which is closely related to physical disability and prognosis, on cognitive functions in multiple sclerosis. Materials and Methods: Twenty nine MS patients (2 clinically isolated syndrome, 23 relapsing and remitting MS, 2 secondary progressive MS, 2 primary progressive MS) were included in the study. Demographic characteristics, expanded disability status scale (EDSS) score, cognition assessed by brief repeatable battery of neuropsychological tests, brain and spinal cord T2 lesion number were evaluated. Results: Older age, later age of disease onset, education duration are the features affecting cognitive test results. Brain and spinal cord lesion numbers did not have any effect on cognitive tests. Patients with spinal cord lesions had higher EDSS compared to patients without, however there was no difference regarding cognitive test results between groups. Conclusion: Spinal cord lesions are associated with physical disability quantified by EDSS. Longitudinal studies with larger samples are needed to investigate the effect of presence and number of cord lesions as well as cervical cord atrophy on cognitive test results.

Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues

The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.

The role of the complement system in Multiple Sclerosis: A review

The complement system has been involved in the pathogenesis of multiple neuroinflammatory and neurodegenerative conditions. In this review, we evaluated the possible role of complement activation in multiple sclerosis (MS) with a focus in progressive MS, where the disease pathogenesis remains to be fully elucidated and treatment options are limited. The evidence for the involvement of the complement system in the white matter plaques and gray matter lesions of MS stems from immunohistochemical analysis of post-mortem MS brains, in vivo serum and cerebrospinal fluid biomarker studies, and animal models of Experimental Autoimmune Encephalomyelitis (EAE). Complement knock-out studies in these animal models have revealed that this system may have a “double-edge sword” effect in MS. On the one hand, complement proteins may aid in promoting the clearance of myelin degradation products and other debris through myeloid cell-mediated phagocytosis. On the other, its aberrant activation may lead to demyelination at the rim of progressive MS white matter lesions as well as synapse loss in the gray matter. The complement system may also interact with known risk factors of MS, including as Epstein Barr Virus (EBV) infection, and perpetuate the activation of CNS self-reactive B cell populations. With the mounting evidence for the involvement of complement in MS, the development of complement modulating therapies for this condition is appealing. Herein, we also reviewed the pharmacological complement inhibitors that have been tested in MS animal models as well as in clinical trials for other neurologic diseases. The potential use of these agents, such as the C5-binding antibody eculizumab in MS will require a detailed understanding of the role of the different complement effectors in this disease and the development of better CNS delivery strategies for these compounds.

Contribution of B cells to cortical damage in multiple sclerosis

Multiple sclerosis is associated with lesions not just in the white matter, but also involving the cortex. Cortical involvement has been linked to greater disease severity and hence understanding the factor underlying cortical pathology could help identify new therapeutic strategies for multiple sclerosis. The critical role of B cells in multiple sclerosis has been clarified by multiple pivotal trials of B cell depletion in people with multiple sclerosis. The presence of B cell rich areas of meningeal inflammation in multiple sclerosis has been identified at all stages of multiple sclerosis. Leptomeningeal inflammation is associated with greater extent of cortical demyelination and neuronal loss and with greater disease severity. Recent studies have identified several potential mechanisms by which B cells may mediate cortical injury including antibody production, extracellular vesicles containing neurotoxic substances and production of pro-inflammatory cytokines. Additionally, B cells may indirectly mediate cortical damage through effects on T cells, macrophages or microglia. Several animal models replicate the meningeal inflammation and cortical injury noted in people with multiple sclerosis. Studies in these models have identified BTK inhibition and type II anti-CD20 antibodies as potential agents that can impact meningeal inflammation. Trials of anti-CD20 monoclonal antibodies in people with multiple sclerosis have unsuccessfully attempted to eliminate B cells in the leptomeninges. New strategies to target B cells in multiple sclerosis include BTK inhibition and cell-based therapies aimed at B cells infected with Epstein Barr virus. Future studies will clarify the mechanisms by which B cells mediate cortical injury and treatment strategies that can target B cells in the leptomeninges and CNS parenchyma.

Two years' effect of dimethyl fumarate on focal and diffuse gray matter pathology in multiple sclerosis

BACKGROUND

Data on the effect of dimethyl fumarate (DMF) on focal and diffuse gray matter (GM) damage, a relevant pathological substrate of multiple sclerosis (MS)-related disability are lacking.

OBJECTIVE

To evaluate the DMF effect on cortical lesions (CLs) accumulation and global and regional GM atrophy in subjects with relapsing-remitting MS.

METHODS

A total of 148 patients (mean age 38.1 ± 9.7 years) treated with DMF ended a 2-year longitudinal study. All underwent regular Expanded Disability Status Scale (EDSS assessment), and at least two 3T-magnetic resonance imaging (MRI) at 3 and 24 months after DMF initiation. CLs and changes in global and regional atrophy of several brain regions were compared with 47 untreated age and sex-matched patients.

RESULTS

DMF-treated patients showed lower CLs accumulation (median 0[0-3] vs 2[0-7], p < 0.001) with respect to controls. Global cortical thickness (p < 0.001) and regional thickness and volume were lower in treated group (cerebellum, hippocampus, caudate, and putamen: p < 0.001; thalamus p = 0.03). Lower relapse rate (14% vs 40%, p < 0.001), EDSS change (0.2 ± 0.4 vs 0.4 ± 0.9, p < 0.001), and new WM lesions (median 0[0-5] vs 2[0-6], p < 0.001) were reported. No severe adverse drug reactions occurred.

CONCLUSIONS

Beyond the well-known effect on disease activity, these results provide evidence of the effect of DMF through reduced progression of focal and diffuse GM damage.

CSF TNF and osteopontin levels correlate with the response to dimethyl fumarate in early multiple sclerosis

Background:

Disease activity in the first years after a diagnosis of relapsing-remitting multiple sclerosis (RRMS) is a negative prognostic factor for long-term disability. Markers of both clinical and radiological responses to disease-modifying therapies (DMTs) are advocated.

Objective:

The objective of this study is to estimate the value of cerebrospinal fluid (CSF) inflammatory markers at the time of diagnosis in predicting the disease activity in treatment-naïve multiple sclerosis (MS) patients exposed to dimethyl fumarate (DMF).

Methods:

In total, 48 RRMS patients (31 females/17 males) treated with DMF after the diagnosis were included in this 2-year longitudinal study. All patients underwent a CSF examination, regular clinical and 3T magnetic resonance imaging (MRI) scans that included the assessment of white matter (WM) lesions, cortical lesions (CLs) and global cortical thickness. CSF levels of 10 pro-inflammatory markers – CXCL13 [chemokine (C-X-C motif) ligand 13 or B lymphocyte chemoattractant], CXCL12 (stromal cell-derived factor or C-X-C motif chemokine 12), tumour necrosis factor (TNF), APRIL (a proliferation-inducing ligand, or tumour necrosis factor ligand superfamily member 13), LIGHT (tumour necrosis factor ligand superfamily member 14 or tumour necrosis factor superfamily member 14), interferon (IFN) gamma, interleukin 12 (IL-12), osteopontin, sCD163 [soluble-CD163 (cluster of differentiation 163)] and Chitinase3-like1 – were assessed using immune-assay multiplex techniques. The combined three-domain status of ‘no evidence of disease activity’ (NEDA-3) was defined by no relapses, no disability worsening and no MRI activity, including CLs.

Results:

Twenty patients (42%) reached the NEDA-3 status; patients with disease activity showed higher CSF TNF (p = 0.009), osteopontin (p = 0.005), CXCL12 (p = 0.037), CXCL13 (p = 0.040) and IFN gamma levels (p = 0.019) compared with NEDA-3 patients. After applying a random forest approach, TNF and osteopontin revealed the most important variables associated with the NEDA-3 status. Six molecules that emerged at the random forest approach were added in a multivariate regression model with demographic, clinical and MRI measures of WM and grey matter damage as independent variables. TNF levels confirmed to be associated with the absence of disease activity: odds ratio (OR) = 0.25, CI% = 0.04–0.77.

Conclusion:

CSF inflammatory markers may provide prognostic information in predicting disease activity in the first years after DMF initiation. CSF TNF levels are a possible candidate in predicting treatment response, in addition to clinical, demographic and MRI variables.

Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes

Introduction

Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms.

Methods

A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest.

Results

Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment.

Conclusion

The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00368-2.

Obesity and the Brain

Innate and adaptive immunity are essential for neurodevelopment and central nervous system (CNS) homeostasis; however, the fragile equilibrium between immune and brain cells can be disturbed by any immune dysregulation and cause detrimental effects. Accumulating evidence indicates that, despite the blood-brain barrier (BBB), overactivation of the immune system leads to brain vulnerability that increases the risk of neuropsychiatric disorders, particularly upon subsequent exposure later in life. Disruption of microglial function in later life can be triggered by various environmental and psychological factors, including obesity-driven chronic low-grade inflammation and gut dysbiosis. Increased visceral adiposity has been recognized as an important risk factor for multiple neuropsychiatric conditions. The review aims to present our current understanding of the topic.

Association of Brain Atrophy With Disease Progression Independent of Relapse Activity in Patients With Relapsing Multiple Sclerosis

Importance

The mechanisms driving neurodegeneration and brain atrophy in relapsing multiple sclerosis (RMS) are not completely understood.

Objective

To determine whether disability progression independent of relapse activity (PIRA) in patients with RMS is associated with accelerated brain tissue loss.

Design, Setting, and Participants

In this observational, longitudinal cohort study with median (IQR) follow-up of 3.2 years (2.0-4.9), data were acquired from January 2012 to September 2019 in a consortium of tertiary university and nonuniversity referral hospitals. Patients were included if they had regular clinical follow-up and at least 2 brain magnetic resonance imaging (MRI) scans suitable for volumetric analysis. Data were analyzed between January 2020 and March 2021.

Exposures

According to the clinical evolution during the entire observation, patients were classified as those presenting (1) relapse activity only, (2) PIRA episodes only, (3) mixed activity, or (4) clinical stability.

Main Outcomes and Measures

Mean difference in annual percentage change (MD-APC) in brain volume/cortical thickness between groups, calculated after propensity score matching. Brain atrophy rates, and their association with the variables of interest, were explored with linear mixed-effect models.

Results

Included were 1904 brain MRI scans from 516 patients with RMS (67.4% female; mean [SD] age, 41.4 [11.1] years; median [IQR] Expanded Disability Status Scale score, 2.0 [1.5-3.0]). Scans with insufficient quality were excluded (n = 19). Radiological inflammatory activity was associated with increased atrophy rates in several brain compartments, while an increased annualized relapse rate was linked to accelerated deep gray matter (GM) volume loss. When compared with clinically stable patients, patients with PIRA had an increased rate of brain volume loss (MD-APC, -0.36; 95% CI, -0.60 to -0.12; P = .02), mainly driven by GM loss in the cerebral cortex. Patients who were relapsing presented increased whole brain atrophy (MD-APC, -0.18; 95% CI, -0.34 to -0.02; P = .04) with respect to clinically stable patients, with accelerated GM loss in both cerebral cortex and deep GM. No differences in brain atrophy rates were measured between patients with PIRA and those presenting relapse activity.

Conclusions and Relevance

Our study shows that patients with RMS and PIRA exhibit accelerated brain atrophy, especially in the cerebral cortex. These results point to the need to recognize the insidious manifestations of PIRA in clinical practice and to further evaluate treatment strategies for patients with PIRA in clinical trials.

Reproducibility of Lesion Count in Various Subregions on MRI Scans in Multiple Sclerosis

Purpose

Lesion number and burden can predict the long-term outcome of multiple sclerosis, while the localization of the lesions is also a good predictive marker of disease progression. These biomarkers are used in studies and in clinical practice, but the reproducibility of lesion count is not well-known.

Methods

In total, five raters evaluated T2 hyperintense lesions in 140 patients with multiple sclerosis in six localizations: periventricular, juxtacortical, deep white matter, infratentorial, spinal cord, and optic nerve. Black holes on T1-weighted images and brain atrophy were subjectively measured on a binary scale. Reproducibility was measured using the intraclass correlation coefficient (ICC). ICCs were also calculated for the four most accurate raters to see how one outlier can influence the results.

Results

Overall, moderate reproducibility (ICC 0.5-0.75) was shown, which did not improve considerably when the most divergent rater was excluded. The areas that produced the worst results were the optic nerve region (ICC: 0.118) and atrophy judgment (ICC: 0.364). Comparing high- and low-lesion burdens in each region revealed that the ICC is higher when the lesion count is in the mid-range. In the periventricular and deep white matter area, where lesions are common, higher ICC was found in patients who had a lower lesion count. On the other hand, juxtacortical lesions and black holes that are less common showed higher ICC when the subjects had more lesions. This difference was significant in the juxtacortical region when the most accurate raters compared patients with low (ICC: 0.406 CI: 0.273-0.546) and high (0.702 CI: 0.603-0.785) lesion loads.

Conclusion

Lesion classification showed high variability by location and overall moderate reproducibility. The excellent range was not achieved, owing to the fact that some areas showed poor performance. Hence, putting effort toward the development of artificial intelligence for the evaluation of lesion burden should be considered.

Late-Onset MS: Disease Course and Safety-Efficacy of DMTS

Multiple sclerosis (MS), an inflammatory demyelinating and neurodegenerative disease of the central nervous system, usually begins between the ages of 20 and 49 years, though in rare cases it is diagnosed in childhood and adolescence before the age of 18 years, or at the age of 50 years and later. When the onset of the disease occurs at 50 years or older it is conventionally defined as late onset MS (LOMS). Compared to classical MS, the LOMS is characterized by progressive course, a greater delay in diagnosis and a higher prevalence of motor disability. The older the patients, the greater is the risk of comorbidities that can negatively influence the course of the disease and can limit therapeutic strategies. To date, there is no study focused on the efficacy of Disease Modifying Therapies (DMT) in older patients with MS. The only data available are retrievable from subgroup analysis from phase-3 trials of DMT efficacy. In this work, we discuss how the aging process influences the onset, the clinical course and the therapeutic approach in LOMS.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.