Natural history studies have identified factors that predict evolution to multiple sclerosis or risk of disability accumulation over time. Although these studies are based on large multicentre cohorts with long follow-ups, they have limitations such as lack of standardized protocols, a retrospective data collection or lack of a systematic magnetic resonance imaging acquisition and analysis protocol, often resulting in failure to take magnetic resonance and oligoclonal bands into account as joint covariates in the prediction models. To overcome some of these limitations, the aim of our study was to identify and stratify baseline demographic, clinical, radiological and biological characteristics that might predict multiple sclerosis development and disability accumulation using a multivariate approach based on a large prospective cohort of patients with clinically isolated syndromes. From 1995 to 2013, 1058 patients with clinically isolated syndromes were included. We evaluated the influence of baseline prognostic factors on the risk for developing clinically definite multiple sclerosis, McDonald multiple sclerosis, and disability accumulation (Expanded Disability Status Scale score of 3.0) based on univariate (hazard ratio with 95% confidence intervals) and multivariate (adjusted hazard ratio with 95% confidence intervals) Cox regression models. We ultimately included 1015 patients followed for a mean of 81 (standard deviation = 57) months. Female/male ratio was 2.1. Females exhibited a similar risk of conversion to multiple sclerosis and of disability accumulation compared to males. Each younger decade at onset was associated with a greater risk of conversion to multiple sclerosis and with a protective effect on disability. Patients with optic neuritis had a lower risk of clinically definite multiple sclerosis [hazard ratio 0.6 (0.5–0.8)] and disability progression [hazard ratio 0.5 (0.3–0.8)]; however, this protective effect remained marginal only for disability [adjusted hazard ratio 0.6 (0.4–1.0)] in adjusted models. The presence of oligoclonal bands increased the risk of clinically definite multiple sclerosis [adjusted hazard ratio 1.3 (1.0–1.8)] and of disability [adjusted hazard ratio 2.0 (1.2–3.6)] independently of other factors. The presence of 10 or more brain lesions on magnetic resonance increased the risk of clinically definite multiple sclerosis [adjusted hazard ratio 11.3 (6.7–19.3)] and disability [adjusted hazard ratio 2.9 (1.4–6.0)]. Disease-modifying treatment before the second attack reduced the risk of McDonald multiple sclerosis [adjusted hazard ratio 0.6 (0.4–0.9)] and disability accumulation [adjusted hazard ratio 0.5 (0.3–0.9)]. We conclude that the demographic and topographic characteristics are low-impact prognostic factors, the presence of oligoclonal bands is a medium-impact prognostic factor, and the number of lesions on brain magnetic resonance is a high-impact prognostic factor.

Objective: Gray matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS.Methods: We analyzed 3,604 brain high‐resolution T1‐weighted magnetic resonance imaging scans from 1,417 participants: 1,214 MS patients (253 clinically isolated syndrome [CIS], 708 relapsing‐remitting [RRMS], 128 secondary‐progressive [SPMS], and 125 primary‐progressive [PPMS]), over an average follow‐up of 2.41 years (standard deviation [SD] = 1.97), and 203 healthy controls (HCs; average follow‐up = 1.83 year; SD = 1.77), attending seven European centers. Disability was assessed with the Expanded Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem, and cerebral white matter. Hierarchical mixed models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time‐to‐EDSS progression.Results: SPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time‐to‐EDSS progression (hazard ratio = 0.73; 95% confidence interval, 0.65, 0.82; p < 0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow‐up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (–1.45%), PPMS (–1.66%), and RRMS (–1.34%) than CIS (–0.88%) and HCs (–0.94%; p < 0.01). The rate of temporal GM atrophy in SPMS (–1.21%) was significantly faster than RRMS (–0.76%), CIS (–0.75%), and HCs (–0.51%). Similarly, the rate of parietal GM atrophy in SPMS (–1.24‐%) was faster than CIS (–0.63%) and HCs (–0.23%; all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta = 0.04; p < 0.001).Interpretation: This large, multicenter and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions. Ann Neurol 2018;83:210–222

The role of MRI in the assessment of multiple sclerosis (MS) goes far beyond the diagnostic process. MRI techniques can be used as regular monitoring to help stage patients with MS and measure disease progression. MRI can also be used to measure lesion burden, thus providing useful information for the prediction of long-term disability. With the introduction of a new generation of immunomodulatory and/or immunosuppressive drugs for the treatment of MS, MRI also makes an important contribution to the monitoring of treatment, and can be used to determine baseline tissue damage and detect subsequent repair. This use of MRI can help predict treatment response and assess the efficacy and safety of new therapies. In the second part of the MAGNIMS (Magnetic Resonance Imaging in MS) network's guidelines on the use of MRI in MS, we focus on the implementation of this technique in prognostic and monitoring tasks. We present recommendations on how and when to use MRI for disease monitoring, and discuss some promising MRI approaches that may be introduced into clinical practice in the near future.

The clinical use of MRI in patients with multiple sclerosis (MS) has advanced markedly over the past few years. Technical improvements and continuously emerging data from clinical trials and observational studies have contributed to the enhanced performance of this tool for achieving a prompt diagnosis in patients with MS. The aim of this article is to provide guidelines for the implementation of MRI of the brain and spinal cord in the diagnosis of patients who are suspected of having MS. These guidelines are based on an extensive review of the recent literature, as well as on the personal experience of the members of the MAGNIMS (Magnetic Resonance Imaging in MS) network. We address the indications, timing, coverage, reporting and interpretation of MRI studies in patients with suspected MS. Our recommendations are intended to help radiologists and neurologists standardize and optimize the use of MRI in clinical practice for the diagnosis of MS.

See Stankoff and Louapre (doi: 10.1093/brain/awy114 ) for a scientific commentary on this article. Grey matter atrophy is present from the earliest stages of multiple sclerosis, but its temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in multiple sclerosis and its association with disability accumulation. In this longitudinal study, we included 1417 subjects: 253 with clinically isolated syndrome, 708 with relapsing-remitting multiple sclerosis, 128 with secondary-progressive multiple sclerosis, 125 with primary-progressive multiple sclerosis, and 203 healthy control subjects from seven European centres. Subjects underwent repeated MRI (total number of scans 3604); the mean follow-up for patients was 2.41 years (standard deviation = 1.97). Disability was scored using the Expanded Disability Status Scale. We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template and used an established data-driven event-based model to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific event-based model stage, based on the number of their atrophic regions. Linear mixed-effects models were used to explore associations between the rate of increase in event-based model stages, and T₂ lesion load, disease-modifying treatments, comorbidity, disease duration and disability accumulation. The first regions to become atrophic in patients with clinically isolated syndrome and relapse-onset multiple sclerosis were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. A similar sequence of atrophy was detected in primary-progressive multiple sclerosis with the involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset multiple sclerosis and late atrophy in primary-progressive multiple sclerosis. Patients with secondary-progressive multiple sclerosis showed the highest event-based model stage (the highest number of atrophic regions, P < 0.001) at the study entry. All multiple sclerosis phenotypes, but clinically isolated syndrome, showed a faster rate of increase in the event-based model stage than healthy controls. T₂ lesion load and disease duration in all patients were associated with increased event-based model stage, but no effects of disease-modifying treatments and comorbidity on event-based model stage were observed. The annualized rate of event-based model stage was associated with the disability accumulation in relapsing-remitting multiple sclerosis, independent of disease duration (P < 0.0001). The data-driven staging of atrophy progression in a large multiple sclerosis sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across multiple sclerosis phenotypes. The spread of atrophy was associated with disease duration and with disability accumulation over time in relapsing-remitting multiple sclerosis.

Objective: Conventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging,NODDI), to demonstrate the strong potential of the new marker.Methods: We related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion.Results: We report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI‐derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates.Interpretation: Neurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices.