Baseline MRI predicts future attacks and disability in clinically isolated syndromes

Patterns of autoantibody expression in multiple sclerosis identified through development of an autoantigen discovery technology

Multiple sclerosis (MS) is a debilitating autoimmune disease of the CNS, which is characterized by demyelination and axonal injury and frequently preceded by a demyelinating event called clinically isolated syndrome (CIS). Despite the importance of B cells and autoantibodies in MS pathology, their target specificities remain largely unknown. For an agnostic and comprehensive evaluation of autoantibodies in MS, we developed and employed what we believe to be a novel autoantigen discovery technology, the Antigenome Platform. This Platform is a high-throughput assay comprising large-fragment (approximately 100 amino acids) cDNA libraries, phage display, serum antibody screening technology, and robust bioinformatics analysis pipelines. For autoantibody discovery, we assayed serum samples from CIS patients who received either placebo or treatment who were enrolled in the REFLEX clinical trial, which assessed the effects of IFN-β-1a (Rebif) clinical and MRI activity in patients with CIS. Serum autoantibodies from patients with CIS were significantly and reproducibly enriched for known and previously unreported protein targets; 166 targets were selected by over 10% of patients' sera. Further, 10 autoantibody biomarkers associated with disease activity and 17 associated with patient response to IFN-β-1a therapy. These findings indicate widespread autoantibody production in MS and provide biomarkers for continued study and prediction of disease progression.

The value of magnetic resonance imaging of the optic nerve for the diagnosis of multiple sclerosis in patients with optic neuritis

BACKGROUND

Although optic neuritis (ON) is common in multiple sclerosis (MS), lesions of the optic nerve are not included as an anatomical substrate for dissemination in space and time (DIS and DIT).

OBJECTIVE

To assess the increase in sensitivity of including MRI lesions of the optic nerve for the diagnosis of MS in patients with ON.

METHODS

We included patients consecutively referred with first time, monosymptomatic ON, with no known cause of the ON, who underwent orbital MRI including fat suppressed T2 and T1-sequences with and without gadolinium contrast.

RESULTS

One hundred and twenty patients were included. Optic nerve T2 lesions and/or T1-contrast enhancement was shown in 104 patients. Sixty-three patients were diagnosed with MS at baseline. Nine patients developed MS during follow-up. The inclusion of optic nerve MRI lesions led to the diagnosis of 8 additional patients and increased sensitivity to 0.99 (95% CI 0.96-1.00) compared to 0.88 (95% CI 0.79-0.95) for 2017 criteria, while decreasing the specificity to 0.81 (95% CI 0.70-0.92) compared to 1.00.

CONCLUSION

Amending the diagnostic criteria for MS to include MRI lesions of the optic nerve as a substrate for DIS and DIT may increase sensitivity and lead to more rapid diagnosis of MS.

One-year risk of multiple sclerosis after a first episode of optic neuritis according to modern diagnosis criteria

PURPOSE

The last updates to diagnostic criteria for multiple sclerosis (MS) included a diagnostic category of 'possible MS'. However, no recent data is available to assess how much this distinction helps predict MS after isolated optic neuritis (ON). This study aimed to assess the global risk of developing MS one year after a first ON episode, and the specific risk according to the initial diagnosis of isolated ON or ON with possible MS.

METHODS

One-year follow-up of a multicentric prospective cohort of adult patients with acute ON.

RESULTS

This study included 55 patients with acute ON of no known etiological diagnosis. Overall, the final diagnosis at one year was MS (23, 42 %), MOGAD (7, 13 %), NMOSD (1, 2 %), CRION (3, 5 %), possible MS (6, 11 %), secondary ON (3, 5 %), and strictly isolated ON (12, 22 %). Three of the 17 (18 %) patients with strictly isolated ON and 2/8 (25 %) with possible MS at baseline progressed to MS. All secondary MS diagnosis were made through radiological monitoring.

CONCLUSION

One year after the first ON episode, we observed a similar conversion rate to MS for patients with strictly isolated ON and possible MS, with a higher prevalence of MS than found by the ONTT.

Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors

Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in timely diagnosis and personalized patient management. The application of Artificial Intelligence (AI) to MS holds promises for early detection, accurate diagnosis, and predictive modeling. The objectives of this study are: 1) to propose new MS trajectory descriptors that could be employed in Machine Learning (ML) regressors and classifiers to predict patient evolution; 2) to explore the contribution of ML models in discerning MS trajectory descriptors using only baseline Magnetic Resonance Imaging (MRI) studies. This study involved 446 MS patients who had a baseline MRI, at least two measurements of Expanded Disability Status Scale (EDSS), and a 1-year follow-up. Patients were divided into two groups: 1) for model development and 2) for evaluation. Three descriptors: β1, β2, and EDSS(t), were related to baseline MRI parameters using regression and classification XGBoost models. Shapley Additive Explanations (SHAP) analysis enhanced model transparency by identifying influential features. The results of this study demonstrate the potential of AI in predicting MS progression using the proposed patient trajectories and baseline MRI scans, outperforming classic Multiple Linear Regression (MLR) methods. In conclusion, MS trajectory descriptors are crucial; incorporating AI analysis into MRI assessments presents promising opportunities to advance predictive capabilities. SHAP analysis enhances model interpretation, revealing feature importance for clinical decisions.

Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI

BACKGROUND

The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect of different input strategies on model's performance are lacking.

PURPOSE

To compare whole-brain input sampling strategies and regional/specific-tissue strategies, which focus on a priori known relevant areas for disability accrual, to stratify MS patients based on their disability level.

STUDY TYPE

Retrospective.

SUBJECTS

Three hundred nineteen MS patients (382 brain MRI scans) with clinical assessment of disability level performed within the following 6 months (~70% training/~15% validation/~15% inference in-house dataset) and 440 MS patients from multiple centers (independent external validation cohort).

FIELD STRENGTH/SEQUENCE

Single vendor 1.5 T or 3.0 T. Magnetization-Prepared Rapid Gradient-Echo and Fluid-Attenuated Inversion Recovery sequences.

ASSESSMENT

A 7-fold patient cross validation strategy was used to train a 3D-CNN to classify patients into two groups, Expanded Disability Status Scale score (EDSS) ≥ 3.0 or EDSS < 3.0. Two strategies were investigated: 1) a global approach, taking the whole brain volume as input and 2) regional approaches using five different regions-of-interest: white matter, gray matter, subcortical gray matter, ventricles, and brainstem structures. The performance of the models was assessed in the in-house and the independent external cohorts.

STATISTICAL TESTS

Balanced accuracy, sensitivity, specificity, area under receiver operating characteristic (ROC) curve (AUC).

RESULTS

With the in-house dataset, the gray matter regional model showed the highest stratification accuracy (81%), followed by the global approach (79%). In the external dataset, without any further retraining, an accuracy of 72% was achieved for the white matter model and 71% for the global approach.

DATA CONCLUSION

The global approach offered the best trade-off between internal performance and external validation to stratify MS patients based on accumulated disability.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Vitamin D did not reduce multiple sclerosis disease activity after a clinically isolated syndrome

Low serum levels of 25-hydroxyvitamin D [25(OH)D] and low sunlight exposure are known risk factors for the development of multiple sclerosis. Add-on vitamin D supplementation trials in established multiple sclerosis have been inconclusive. The effects of vitamin D supplementation to prevent multiple sclerosis is unknown. We aimed to test the hypothesis that oral vitamin D3 supplementation in high-risk clinically isolated syndrome (abnormal MRI, at least three T2 brain and/or spinal cord lesions), delays time to conversion to definite multiple sclerosis, that the therapeutic effect is dose-dependent, and that all doses are safe and well tolerated. We conducted a double-blind trial in Australia and New Zealand. Eligible participants were randomized 1:1:1:1 to placebo, 1000, 5000 or 10 000 international units (IU) of oral vitamin D3 daily within each study centre (n = 23) and followed for up to 48 weeks. Between 2013 and 2021, we enrolled 204 participants. Brain MRI scans were performed at baseline, 24 and 48 weeks. The main study outcome was conversion to clinically definite multiple sclerosis based on the 2010 McDonald criteria defined as either a clinical relapse or new brain MRI T2 lesion development. We included 199 cases in the intention-to-treat analysis based on assigned dose. Of these, 116 converted to multiple sclerosis by 48 weeks (58%). Compared to placebo, the hazard ratios (95% confidence interval) for conversion were 1000 IU 0.87 (0.50, 1.50); 5000 IU 1.37 (0.82, 2.29); and 10 000 IU 1.28 (0.76, 2.14). In an adjusted model including age, sex, latitude, study centre and baseline symptom number, clinically isolated syndrome onset site, presence of infratentorial lesions and use of steroids, the hazard ratios (versus placebo) were 1000 IU 0.80 (0.45, 1.44); 5000 IU 1.36 (0.78, 2.38); and 10 000 IU 1.07 (0.62, 1.85). Vitamin D3 supplementation was safe and well tolerated. We did not demonstrate reduction in multiple sclerosis disease activity by vitamin D3 supplementation after a high-risk clinically isolated syndrome.

Consensus statement of the Spanish Society of Neurology on the treatment of multiple sclerosis and holistic patient management in 2023

The last consensus statement of the Spanish Society of Neurology's Demyelinating Diseases Study Group on the treatment of multiple sclerosis (MS) was issued in 2016. Although many of the positions taken remain valid, there have been significant changes in the management and treatment of MS, both due to the approval of new drugs with different action mechanisms and due to the evolution of previously fixed concepts. This has enabled new approaches to specific situations such as pregnancy and vaccination, and the inclusion of new variables in clinical decision-making, such as the early use of high-efficacy disease-modifying therapies (DMT), consideration of the patient's perspective, and the use of such novel technologies as remote monitoring. In the light of these changes, this updated consensus statement, developed according to the Delphi method, seeks to reflect the new paradigm in the management of patients with MS, based on the available scientific evidence and the clinical expertise of the participants. The most significant recommendations are that immunomodulatory DMT be started in patients with radiologically isolated syndrome with persistent radiological activity, that patient perspectives be considered, and that the term "lines of therapy" no longer be used in the classification of DMTs (> 90% consensus). Following diagnosis of MS, the first DMT should be selected according to the presence/absence of factors of poor prognosis (whether epidemiological, clinical, radiological, or biomarkers) for the occurrence of new relapses or progression of disability; high-efficacy DMTs may be considered from disease onset.

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.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.

The Interaural Time Difference for High-Pass Filtered Noise and Its Relationship With Brainstem Dysfunction and Disability in Multiple Sclerosis

PURPOSE

Just noticeable difference for interaural time difference (JND-ITD) is a sensitive test to detect silent lesions and neural asynchrony along the auditory pathways among individuals with multiple sclerosis (MS), but it has not been studied with brainstem functional system scores (BFSS) and expanded disability status scale (EDSS). The study aims to assess the usefulness of JND-ITD thresholds in individuals with MS and relate to brainstem magnetic resonance imaging (MRI) lesions, BFSS, and disability (EDSS).

METHOD

Standard group comparison design was adapted to compare the JND-ITD thresholds between individuals with MS (n = 45) and age and gender-matched healthy participants (n = 45). All participants underwent case history, neurological examination including BFSS and EDSS scoring, MRI brain imaging, minimental state examination, routine audiological evaluation, and ITD testing for high-pass filtered noise stimuli.

RESULTS

Of the 36 MS participants with abnormal JND-ITD thresholds, 22 (48.9%) participants could not identify maximum JND-ITD values (1,280 μs) in the ITD task. Abnormal JND-ITDs thresholds (139-1,280 μs) were obtained in 14 (31.11%) participants with MS. The JND-ITD thresholds were significantly different between the healthy and MS group. No significant association was found between the presence of ITD abnormality with the presence of brainstem lesions (MRI) and brainstem dysfunction (BFSS). Also, this study did not find any relationship between JND-ITD thresholds with disability (EDSS).

CONCLUSIONS

This study supports the findings that JND-ITD for high-pass filtered noise is a sensitive test to detect lesions along the auditory system. Even though JND-ITD thresholds did not relate with BFSS and EDSS scores, JND-ITD abnormalities can be of great value in identifying lesions along the auditory system, especially in the early stages of MS, when clinical neurological examination does not show any signs of brainstem dysfunction, disability, and MRI without any lesions in the brain.

Kappa Free Light Chain Index Predicts Disease Course in Clinically and Radiologically Isolated Syndromes

BACKGROUND AND OBJECTIVES

To evaluate whether the kappa free light chain index (K-index) can predict the occurrence of new T2-weighted MRI lesions (T2L) and clinical events in clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS).

METHODS

All consecutive patients presenting for the diagnostic workup, including CSF analysis, of clinical and/or MRI suspicion of multiple sclerosis (MS) since May 1, 2018, were evaluated. All patients diagnosed with CIS and RIS with at least 1-year follow-up were included. Clinical events and new T2L were collected during follow-up. The K-index performances in predicting new T2L and a clinical event were evaluated using time-dependent ROC analyses. The time to clinical event or new T2L was estimated using survival analysis according to the binarized K-index using an independent cutoff of 8.9, and the ability of each variable to predict outcomes was compared using the Harrell c-index.

RESULTS

One hundred and eighty two patients (146 CIS and 36 RIS, median age 39 [30; 48] y-o, 70% females) were included with a median follow-up of 21 [13, 33] months. One hundred five (58%) patients (85 CIS and 20 RIS) experienced new T2L, and 28 (15%; 21 CIS and 7 RIS) experienced a clinical event. The K-index could predict new T2L over time in CIS (area under the curve [AUC] ranging from 0.86 to 0.96) and in RIS (AUC ranging from 0.84 to 0.54) but also a clinical event in CIS (AUC ranging from 0.75 to 0.87). Compared with oligoclonal bands (OCBs), the K-index had a better sensitivity and a slight lower specificity in predicting new T2L and clinical events in both populations. In the predictive model, the K-index was the variable that best predict new T2L in both CIS and RIS but also clinical events in CIS (c-index ranging from 0.70 to 0.77), better than the other variables, including OCB.

DISCUSSION

This study provides evidence that the K-index predicts new T2L in CIS and RIS but also clinical attack in patients with CIS. We suggest adding the K-index in the further MS diagnosis criteria revisions as a dissemination-in-time biomarker.

Teriflunomide and Time to Clinical Multiple Sclerosis in Patients With Radiologically Isolated Syndrome: The TERIS Randomized Clinical Trial

Importance

Radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS) punctuated by incidental magnetic resonance imaging (MRI) white matter anomalies within the central nervous system.

Objective

To determine the time to onset of symptoms consistent with MS.

Design, Setting, and Participants

From September 2017 to October 2022, this multicenter, double-blind, phase 3, randomized clinical trial investigated the efficacy of teriflunomide in delaying MS in individuals with RIS, with a 3-year follow-up. The setting included referral centers in France, Switzerland, and Turkey. Participants older than 18 years meeting 2009 RIS criteria were randomly assigned (1:1) to oral teriflunomide, 14 mg daily, or placebo up to week 96 or, optionally, to week 144.

Interventions

Clinical, MRI, and patient-reported outcomes (PROs) were collected at baseline and yearly until week 96, with an optional third year in the allocated arm if no symptoms have occurred.

Main outcomes

Primary analysis was performed in the intention-to-treat population, and safety was assessed accordingly. Secondary end points included MRI outcomes and PROs.

Results

Among 124 individuals assessed for eligibility, 35 were excluded for declining to participate, not meeting inclusion criteria, or loss of follow-up. Eighty-nine participants (mean [SD] age, 37.8 [12.1] years; 63 female [70.8%]) were enrolled (placebo, 45 [50.6%]; teriflunomide, 44 [49.4%]). Eighteen participants (placebo, 9 [50.0%]; teriflunomide, 9 [50.0%]) discontinued the study, resulting in a dropout rate of 20% for adverse events (3 [16.7%]), consent withdrawal (4 [22.2%]), loss to follow-up (5 [27.8%]), voluntary withdrawal (4 [22.2%]), pregnancy (1 [5.6%]), and study termination (1 [5.6%]). The time to the first clinical event was significantly extended in the teriflunomide arm compared with placebo, in both the unadjusted (hazard ratio [HR], 0.37; 95% CI, 0.16-0.84; P = .02) and adjusted (HR, 0.28; 95% CI, 0.11-0.71; P = .007) analysis. Secondary imaging end point outcomes including the comparison of the cumulative number of new or newly enlarging T2 lesions (rate ratio [RR], 0.57; 95% CI, 0.27-1.20; P = .14), new gadolinium-enhancing lesions (RR, 0.33; 95% CI, 0.09-1.17; P = .09), and the proportion of participants with new lesions (odds ratio, 0.72; 95% CI, 0.25-2.06; P = .54) were not significant.

Conclusion and Relevance

Treatment with teriflunomide resulted in an unadjusted risk reduction of 63% and an adjusted risk reduction of 72%, relative to placebo, in preventing a first clinical demyelinating event. These data suggest a benefit to early treatment in the MS disease spectrum.

Trial Registration

ClinicalTrials.gov Identifier: NCT03122652.

Clinical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis

An 18-protein multiple sclerosis (MS) disease activity (DA) test was validated based on associations between algorithm scores and clinical/radiographic assessments (N = 614 serum samples; Train [n = 426; algorithm development] and Test [n = 188; evaluation] subsets). The multi-protein model was trained based on presence/absence of gadolinium-positive (Gd+) lesions and was also strongly associated with new/enlarging T2 lesions, and active versus stable disease (composite of radiographic and clinical evidence of DA) with improved performance (p < 0.05) compared to the neurofilament light single protein model. The odds of having ≥1 Gd + lesions with a moderate/high DA score were 4.49 times that of a low DA score, and the odds of having ≥2 Gd + lesions with a high DA score were 20.99 times that of a low/moderate DA score. The MSDA Test was clinically validated with improved performance compared to the top-performing single-protein model and can serve as a quantitative tool to enhance the care of MS patients.

The spatio-temporal relationship between concurrent lesion and brain atrophy changes in early multiple sclerosis: A post-hoc analysis of the REFLEXION study

BACKGROUND

White matter (WM) lesions and brain atrophy are present early in multiple sclerosis (MS). However, their spatio-temporal relationship remains unclear.

METHODS

Yearly magnetic resonance images were analysed in 387 patients with a first clinical demyelinating event (FCDE) from the 5-year REFLEXION study. Patients received early (from baseline; N = 258; ET) or delayed treatment (from month-24; N = 129; DT) with subcutaneous interferon beta-1a. FSL-SIENA/VIENA were used to provide yearly percentage volume change of brain (PBVC) and ventricles (PVVC). Yearly total lesion volume change (TLVC) was determined by a semi-automated method. Using linear mixed models and voxel-wise analyses, we firstly investigated the overall relationship between TLVC and PBVC and between TLVC and PVVC in the same follow-up period. Analyses were then separately performed for: the untreated period of DT patients (first two years), the first year of treatment (year 1 for ET and year 3 for DT), and a period where patients had received at least 1 year of treatment (stable treatment; ET: years 2, 3, 4, and 5; DT: years 4 and 5).

RESULTS

Whole brain: across the whole study period, lower TLVC was related to faster atrophy (PBVC: B = 0.046, SE = 0.013, p < 0.001; PVVC: B = -0.466, SE = 0.118, p < 0.001). Within the untreated period of DT patients, lower TLVC was related to faster atrophy (PBVC: B = 0.072, SE = 0.029, p = 0.013; PVVC: B = -0.917, SE = 0.306, p = 0.003). A similar relationship was found within the first year of treatment of ET patients (PBVC: B = 0.081, SE = 0.027, p = 0.003; PVVC: B = -1.08, SE = 0.284, p < 0.001), consistent with resolving oedema and pseudo-atrophy. Voxel-wise: overall, higher TLVC was related to faster ventricular enlargement. Lower TLVC was related to faster widespread atrophy in year 1 in both ET (first year of treatment) and DT (untreated) patients. In the second untreated year of DT patients and within the stable treatment period of ET patients (year 4), faster periventricular and occipital lobe atrophy was associated with higher TLVC.

CONCLUSIONS

WM lesion changes and atrophy occurred simultaneously in early MS. Spatio-temporal correspondence of these two processes involved mostly the periventricular area. Within the first year of the study, in both treatment groups, faster atrophy was linked to lower lesion volume changes, consistent with higher shrinking and disappearing lesion activity. This might reflect the pseudo-atrophy phenomenon that is probably related to the therapy driven (only in ET patients, as they received treatment from baseline) and "natural" (both ET and DT patients entered the study after a FCDE) resolution of oedema. In an untreated period and later on during stable treatment, (real) atrophy was related to higher lesion volume changes, consistent with increased new and enlarging lesion activity.

Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI

The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of extracting image features not detectable through conventional methods. Additionally, the study of CNN-derived attention maps, which indicate the most relevant anatomical features for CNN-based decisions, has the potential to uncover key disease mechanisms leading to disability accumulation. From a cohort of patients prospectively followed up after a first demyelinating attack, we selected those with T1-weighted and T2-FLAIR brain MRI sequences available for image analysis and a clinical assessment performed within the following six months (N = 319). Patients were divided into two groups according to expanded disability status scale (EDSS) score: ≥3.0 and < 3.0. A 3D-CNN model predicted the class using whole-brain MRI scans as input. A comparison with a logistic regression (LR) model using volumetric measurements as explanatory variables and a validation of the CNN model on an independent dataset with similar characteristics (N = 440) were also performed. The layer-wise relevance propagation method was used to obtain individual attention maps. The CNN model achieved a mean accuracy of 79% and proved to be superior to the equivalent LR-model (77%). Additionally, the model was successfully validated in the independent external cohort without any re-training (accuracy = 71%). Attention-map analyses revealed the predominant role of frontotemporal cortex and cerebellum for CNN decisions, suggesting that the mechanisms leading to disability accrual exceed the mere presence of brain lesions or atrophy and probably involve how damage is distributed in the central nervous system.

Analytical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis

PURPOSE

To characterize and analytically validate the MSDA Test, a multi-protein, serum-based biomarker assay developed using Olink^® PEA methodology.

EXPERIMENTAL DESIGN

Two lots of the MSDA Test panel were manufactured and subjected to a comprehensive analytical characterization and validation protocol to detect biomarkers present in the serum of patients with multiple sclerosis (MS). Biomarker concentrations were incorporated into a final algorithm used for calculating four Disease Pathway scores (Immunomodulation, Neuroinflammation, Myelin Biology, and Neuroaxonal Integrity) and an overall Disease Activity score.

RESULTS

Analytical characterization demonstrated that the multi-protein panel satisfied the criteria necessary for a fit-for-purpose validation considering the assay's intended clinical use. This panel met acceptability criteria for 18 biomarkers included in the final algorithm out of 21 biomarkers evaluated. VCAN was omitted based on factors outside of analytical validation; COL4A1 and GH were excluded based on imprecision and diurnal variability, respectively. Performance of the four Disease Pathway and overall Disease Activity scores met the established acceptability criteria.

CONCLUSIONS AND CLINICAL RELEVANCE

Analytical validation of this multi-protein, serum-based assay is the first step in establishing its potential utility as a quantitative, minimally invasive, and scalable biomarker panel to enhance the standard of care for patients with MS.

Lessons from immunotherapies in multiple sclerosis

The improved understanding of multiple sclerosis (MS) neurobiology alongside the development of novel markers of disease will allow precision medicine to be applied to MS patients, bringing the promise of improved care. Combinations of clinical and paraclinical data are currently used for diagnosis and prognosis. The addition of advanced magnetic resonance imaging and biofluid markers has been strongly encouraged, since classifying patients according to the underlying biology will improve monitoring and treatment strategies. For example, silent progression seems to contribute significantly more than relapses to overall disability accumulation, but currently approved treatments for MS act mainly on neuroinflammation and offer only a partial protection against neurodegeneration. Further research, involving traditional and adaptive trial designs, should strive to halt, repair or protect against central nervous system damage. To personalize new treatments, their selectivity, tolerability, ease of administration, and safety must be considered, while to personalize treatment approaches, patient preferences, risk-aversion, and lifestyle must be factored in, and patient feedback used to indicate real-world treatment efficacy. The use of biosensors and machine-learning approaches to integrate biological, anatomical, and physiological parameters will take personalized medicine a step closer toward the patient's virtual twin, in which treatments can be tried before they are applied.

Using personalized prognosis in the treatment of relapsing multiple sclerosis: A practical guide

The clinical course of multiple sclerosis (MS) is highly variable among patients, thus creating important challenges for the neurologist to appropriately treat and monitor patient progress. Despite some patients having apparently similar symptom severity at MS disease onset, their prognoses may differ greatly. To this end, we believe that a proactive disposition on the part of the neurologist to identify prognostic “red flags” early in the disease course can lead to much better long-term outcomes for the patient in terms of reduced disability and improved quality of life. Here, we present a prognosis tool in the form of a checklist of clinical, imaging and biomarker parameters which, based on consensus in the literature and on our own clinical experiences, we have established to be associated with poorer or improved clinical outcomes. The neurologist is encouraged to use this tool to identify the presence or absence of specific variables in individual patients at disease onset and thereby implement sufficiently effective treatment strategies that appropriately address the likely prognosis for each patient.

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning

Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by increasing statistical power using a deep-learning predictive enrichment strategy. Specifically, a multi-headed multilayer perceptron is used to estimate the conditional average treatment effect (CATE) using baseline clinical and imaging features, and patients predicted to be most responsive are preferentially randomized into a trial. Leveraging data from six randomized clinical trials (n = 3,830), we first pre-trained the model on the subset of relapsing-remitting MS patients (n = 2,520), then fine-tuned it on a subset of primary progressive MS (PPMS) patients (n = 695). In a separate held-out test set of PPMS patients randomized to anti-CD20 antibodies or placebo (n = 297), the average treatment effect was larger for the 50% (HR, 0.492; 95% CI, 0.266-0.912; p = 0.0218) and 30% (HR, 0.361; 95% CI, 0.165-0.79; p = 0.008) predicted to be most responsive, compared to 0.743 (95% CI, 0.482-1.15; p = 0.179) for the entire group. The same model could also identify responders to laquinimod in another held-out test set of PPMS patients (n = 318). Finally, we show that using this model for predictive enrichment results in important increases in power.

There are limited predictive biomarkers for drug treatment responses in individuals with multiple sclerosis. Here using existing clinical trials data, the authors propose a deep-learning predictive enrichment strategy to identify which participants are most likely to respond to a treatment.

The prognostic significance of early blood neurofilament light chain concentration and magnetic resonance imaging variables in relapse-onset multiple sclerosis

BACKGROUND

Improved prognostication remains vital in multiple sclerosis to inform personalized treatment approaches. Blood neurofilament light (bNfL) is a promising prognostic biomarker, but to what extent it provides additional information, independent of established MRI metrics, is yet to be established.

METHODS

We obtained all available bNfL data for 133 patients from a longitudinal observational cohort study. Patients were dichotomized into good or poor outcome groups based upon clinical and cognitive assessments performed 15 years after a clinically isolated syndrome. We performed longitudinal modeling of early NfL and MRI variables to examine differences between outcome groups.

RESULTS

The bNfL dataset was incomplete, with one to three (mean 1.5) samples available per participant. Within 3 months of onset, bNfL was similar between groups. The bNfL concentration subsequently decreased in those with a good outcome, and remained persistently elevated in those with a poor outcome. By year 5, NfL in the poor outcome group was approximately double that of those with a good outcome (14.58 [10.40-18.77] vs. 7.71 [6.39-9.04] pg/ml, respectively). Differences were reduced after adjustment for longitudinal changes in T2LV, but trends persisted for a greater rate of increase in NfL in those with a poor outcome, independent of T2LV.

CONCLUSIONS

This analysis requires replication in cohorts with more complete bNfL datasets, but suggests that persistently elevated blood NfL may be more common in patients with a poor long-term outcome. Persistent elevation of blood NfL may provide additional prognostic information not wholly accounted for by standard monitoring techniques.

Evolution from a first clinical demyelinating even to multiple sclerosis in the REFLEX trial Regional susceptibility in the conversion to multiple sclerosis at disease onset and their amenability to subcutaneous interferon beta-1a

Background and purpose

In the REFLEX trial (ClinicalTrials.gov identifier: NCT00404352), patients with a first clinical demyelinating event (FCDE) displayed significantly delayed onset of multiple sclerosis (MS; McDonald criteria) when treated with subcutaneous interferon beta‐1a (sc IFN β‐1a) versus placebo. This post hoc analysis evaluated the effect of sc IFN β‐1a on spatio‐temporal evolution of disease activity, assessed by changes in T2 lesion distribution, in specific brain regions of such patients and its relationship with conversion to MS.

Methods

Post hoc analysis of baseline and 24‐month magnetic resonance imaging data from FCDE patients who received sc IFN β‐1a 44 μg once or three times weekly, or placebo in the REFLEX trial. Patients were grouped according to McDonald MS status (converter/non‐converter) or treatment (sc IFN β‐1a/placebo). For each patient group, a baseline lesion probability map (LPM) and longitudinal new/enlarging and shrinking/disappearing LPMs were created. Lesion location/frequency of lesion occurrence were assessed in the white matter.

Results

At Month 24, lesion frequency was significantly higher in the anterior thalamic radiation (ATR) and corticospinal tract (CST) of converters versus non‐converters (p < 0.05). Additionally, the overall distribution of new/enlarging lesions across the brain at Month 24 was similar in placebo‐ and sc IFN β‐1a‐treated patients (ratio: 0.95). Patients treated with sc IFN β‐1a versus placebo showed significantly lower new lesion frequency in specific brain regions (cluster corrected): ATR (p = 0.025), superior longitudinal fasciculus (p = 0.042), CST (p = 0.048), and inferior longitudinal fasciculus (p = 0.048).

Conclusions

T2 lesion distribution in specific brain locations predict conversion to McDonald MS and show significantly reduced new lesion occurrence after treatment with sc IFN β‐1a in an FCDE population.

Magnetic Resonance Imaging as a Prognostic Disability Marker in Clinically Isolated Syndrome and Multiple Sclerosis: A Systematic Review and Meta-Analysis

To date, there are no definite imaging predictors for long-term disability in multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the key prognostic tool for MS, primarily at the early stage of the disease. Recent findings showed that white matter lesion (WML) counts and volumes could predict long-term disability for MS. However, the prognostic value of MRI in the early stage of the disease and its link to long-term physical disability have not been assessed systematically and quantitatively. A meta-analysis was conducted using studies from four databases to assess whether MS lesion counts and volumes at baseline MRI scans could predict long-term disability, assessed by the expanded disability status scale (EDSS). Fifteen studies were eligible for the qualitative analysis and three studies for meta-analysis. T2 brain lesion counts and volumes after the disease onset were associated with disability progression after 10 years. Four or more lesions at baseline showed a highly significant association with EDSS 3 and EDSS 6, with a pooled OR of 4.10 and 4.3, respectively. The risk increased when more than 10 lesions were present. This review and meta-analysis confirmed that lesion counts and volumes could be associated with disability and might offer additional valid guidance in treatment decision making. Future work is essential to determine whether these prognostic markers have high predictive potential.

Prognosis of a second clinical event from baseline MRI in patients with a CIS: a multicenter study using a machine learning approach

PURPOSE

To predict the occurrence of a second clinical event in patients with a CIS suggestive of MS, from baseline magnetic resonance imaging (MRI), by means of a pattern recognition approach.

METHODS

Two hundred sixty-six patients with a CIS were recruited from four participating centers. Over a follow-up of 3 years, 130 patients had a second clinical episode and 136 did not. Grey matter and white matter T1-hypointensities masks segmented from 3D T1-weighted images acquired on 3 T scanners were used as features for the classification approach. Differences between CIS that remained CIS and those that developed a second event were assessed at a global level and at a regional level, arranging the regions according to their contribution to the classification model.

RESULTS

All classification metrics were around or even below 50% for both global and regional approaches. Accuracies did not change when T1-hypointensity maps were added to the model; just the specificity was increased up to 80%. Among the 30 regions with the largest contribution, 26 were grey matter and 4 were white matter regions. For grey matter, regions contributing showed either a larger or a smaller volume in the group of patients that remained CIS, compared to those with a second event. The volume of T1-hypointensities was always larger for the group that presented a second event.

CONCLUSIONS

Prediction of a second clinical event in CIS patients from baseline MRI seems to present a highly heterogeneous pattern, leading to very low classification accuracies. Adding the T1-hypointensity maps does not seem to improve the accuracy of the classification model.

MRI Patterns Distinguish AQP4 Antibody Positive Neuromyelitis Optica Spectrum Disorder From Multiple Sclerosis

Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are inflammatory diseases of the CNS. Overlap in the clinical and MRI features of NMOSD and MS means that distinguishing these conditions can be difficult. With the aim of evaluating the diagnostic utility of MRI features in distinguishing NMOSD from MS, we have conducted a cross-sectional analysis of imaging data and developed predictive models to distinguish the two conditions. NMOSD and MS MRI lesions were identified and defined through a literature search. Aquaporin-4 (AQP4) antibody positive NMOSD cases and age- and sex-matched MS cases were collected. MRI of orbits, brain and spine were reported by at least two blinded reviewers. MRI brain or spine was available for 166/168 (99%) of cases. Longitudinally extensive (OR = 203), "bright spotty" (OR = 93.8), whole (axial; OR = 57.8) or gadolinium (Gd) enhancing (OR = 28.6) spinal cord lesions, bilateral (OR = 31.3) or Gd-enhancing (OR = 15.4) optic nerve lesions, and nucleus tractus solitarius (OR = 19.2), periaqueductal (OR = 16.8) or hypothalamic (OR = 7.2) brain lesions were associated with NMOSD. Ovoid (OR = 0.029), Dawson's fingers (OR = 0.031), pyramidal corpus callosum (OR = 0.058), periventricular (OR = 0.136), temporal lobe (OR = 0.137) and T1 black holes (OR = 0.154) brain lesions were associated with MS. A score-based algorithm and a decision tree determined by machine learning accurately predicted more than 85% of both diagnoses using first available imaging alone. We have confirmed NMOSD and MS specific MRI features and combined these in predictive models that can accurately identify more than 85% of cases as either AQP4 seropositive NMOSD or MS.

Nonlesional diffusely abnormal appearing white matter in clinically isolated syndrome: Prevalence, association with clinical and MRI features, and risk for conversion to multiple sclerosis

BACKGROUND AND PURPOSE

While diffusely abnormal white matter (DAWM) is a nonlesional MRI abnormality identified in ∼25% of patients with multiple sclerosis (MS), it has yet to be investigated in patients at an earlier disease stage, namely clinically isolated syndrome (CIS). The goals of this study were to (1) determine the prevalence of DAWM in patients with a CIS suggestive of MS, (2) evaluate the association between DAWM and demographic, clinical, and MRI features, and (3) evaluate the prognostic significance of DAWM on conversion from CIS to MS.

METHODS

One hundred and forty-two CIS participants were categorized into DAWM and non-DAWM groups at baseline and followed for up to 24 months or until MS diagnosis. The primary outcome was conversion to MS (2005 McDonald criteria) within 6 months.

RESULTS

DAWM was present in 27.5% of participants, and was positively associated with brainstem symptom onset, receiving corticosteroids, dissemination in space, and T₂ lesion volume. DAWM was associated with an increased risk of conversion to MS over 6 months after adjustment for age and disability (hazard ratio [HR] = 2.24, p = 0.004). This association remained at a trend-level after adjustment for high-risk imaging features (HR = 1.68, p = 0.10).

CONCLUSIONS

DAWM is present in a similar proportion of patients with CIS and clinically definite MS, and it is associated with increased risk of conversion to MS over 6 months.

Effectiveness of Brainstem Auditory Evoked Potentials Scoring in Evaluating Brainstem Dysfunction and Disability Among Individuals With Multiple Sclerosis

Purpose The brainstem dysfunction in multiple sclerosis (MS) often causes significant functional impairment leading to disability. This study aims to explore modified brainstem auditory evoked potential (BAEP) scores based on the pattern of BAEP abnormalities and relate with brainstem symptoms, brainstem functional system scores (BFSS), brainstem lesions, and disability. Method Forty-five participants with relapsing-remitting MS and 45 age- and gender-matched healthy controls underwent case history assessment, otoscopic examination, pure-tone audiometry, and BAEP testing. Also, neurological examination (Expanded Disability Status Scale, FSS scales) and magnetic resonance imaging were carried out on MS participants. Patterns of BAEP abnormalities were categorized and converted to BAEP scores. Results Out of 45 participants' brainstem symptoms, BFSS > 1, brainstem lesions (magnetic resonance imaging), and BAEP abnormalities were observed in 75.6%, 42.2%, 62.2%, and 55.56% of participants, respectively. Waves V and III abnormalities were more common among MS participants and showed a significant difference from the control group in the Mann-Whitney U test. Chi-square test did not show a significant association of BAEP abnormalities with brainstem symptoms and lesions but showed significant association with BFSS. The mean and standard deviation of BAEP scores in MS participants were 1.73 + 2.37. All healthy controls showed BAEP scores of 0. BAEP scores in MS participants showed significant correlation with BFSS scores and predict Expanded Disability Status Scale scores. Conclusion BAEP scores based on the pattern of BAEP abnormality can be a valid and useful measure in evaluating brainstem functions and predicting disability in MS.

Integrative biochemical, proteomics and metabolomics cerebrospinal fluid biomarkers predict clinical conversion to multiple sclerosis

Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalized medicine approach. We sought to identify biomarkers from biochemical, metabolic and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2-10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict the occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.

Using advanced analysis of multifocal visual-evoked potentials to evaluate the risk of clinical progression in patients with radiologically isolated syndrome

This study aimed to assess the role of multifocal visual-evoked potentials (mfVEPs) as a guiding factor for clinical conversion of radiologically isolated syndrome (RIS). We longitudinally followed a cohort of 15 patients diagnosed with RIS. All subjects underwent thorough ophthalmological, neurological and imaging examinations. The mfVEP signals were analysed to obtain features in the time domain (SNR_min: amplitude, Lat_max: monocular latency) and in the continuous wavelet transform (CWT) domain (b_max: instant in which the CWT function maximum appears, N_max: number of CWT function maximums). The best features were used as inputs to a RUSBoost boosting-based sampling algorithm to improve the mfVEP diagnostic performance. Five of the 15 patients developed an objective clinical symptom consistent with an inflammatory demyelinating central nervous system syndrome during follow-up (mean time: 13.40 months). The (SNR_min) variable decreased significantly in the group that converted (2.74 ± 0.92 vs. 4.07 ± 0.95, p = 0.01). Similarly, the (b_max) feature increased significantly in RIS patients who converted (169.44 ± 24.81 vs. 139.03 ± 11.95 (ms), p = 0.02). The area under the curve analysis produced SNR_min and b_max values of 0.92 and 0.88, respectively. These results provide a set of new mfVEP features that can be potentially useful for predicting prognosis in RIS patients.

Subgroup analysis of clinical and MRI outcomes in participants with a first clinical demyelinating event at risk of multiple sclerosis in the ORACLE-MS study

BACKGROUND

In the Phase 3, 96-week ORACLE-MS study, cladribine 10 mg tablets (3.5 mg/kg or 5.25 mg/kg cumulative dose over 2 years) significantly reduced the rate of conversion to clinically definite multiple sclerosis (CDMS) per the Poser criteria (henceforth referred to as CDMS), multiple sclerosis (MS) per the 2005 McDonald criteria, and the number of new or persisting T1 gadolinium-enhancing (Gd+), new or enlarging T2, and combined unique active (CUA) lesions versus placebo in participants with a first clinical demyelinating event (FCDE). Patient demographic and disease characteristics may be predictors of disease progression. The current study analyzed the effect of cladribine tablets in subgroups of participants in the ORACLE-MS study by baseline demographics and disease characteristics.

METHODS

This analysis retrospectively examined data collected from 616 participants enrolled in the ORACLE-MS study (placebo, n=206; cladribine tablets 3.5 mg/kg, n=206; cladribine tablets 5.25 mg/kg, n=204). Five subgroups were predetermined by baseline demographics, including sex, age (<30 or ≥30 years), classification of FCDE, and lesion characteristics, including absence or presence of T1 Gd+ lesions and number of T2 lesions (<9 or ≥9). Selected endpoints of the ORACLE-MS study were re-analyzed for these subgroups. The primary and main secondary endpoints were time to conversion to CDMS and MS (2005 McDonald criteria), respectively. Secondary magnetic resonance imaging (MRI) endpoints included cumulative T1 Gd+ and new or enlarging T2 lesions. Cox proportional hazards models were used to evaluate time to conversion to CDMS and MS (2005 McDonald criteria). This analysis focused primarily on the results for the cladribine tablets 3.5 mg/kg group because this dosage is approved for relapsing forms of MS.

RESULTS

In the overall intent-to-treat (ITT) population, cladribine tablets 3.5 mg/kg significantly reduced the risk of conversion to CDMS (hazard ratio [HR]=0.326; P<0.0001) and MS (2005 McDonald criteria; HR=0.485; P<0.0001) versus placebo. Similar effects of cladribine tablets on risk of conversion were observed in post hoc analyses of subgroups defined by various baseline characteristics. In both the ITT population and across subgroups, cladribine tablets 3.5 mg/kg reduced the numbers of cumulative T1 Gd+ (range of rate ratios: 0.106-0.399), new or enlarging T2 (range of rate ratios: 0.178-0.485), and CUA (range of rate ratios: 0.154-0.384) lesions versus placebo (all nominal P<0.03). Multivariate Cox proportional hazards models revealed that age (HR=0.577, nominal P<0.0001), FCDE classification (HR=0.738, nominal P=0.0043), presence of T1 Gd+ lesions (HR=0.554, nominal P<0.0001), and number of T2 lesions (HR=0.417, nominal P<0.0001) at baseline were factors associated with risk of conversion to MS (2005 McDonald criteria), whereas no baseline factors examined were associated with risk of conversion to CDMS.

CONCLUSION

In this post hoc analysis of the ORACLE-MS study, cladribine tablets reduced the risk of conversion to multiple sclerosis and lesion burden in participants with an FCDE in the overall ITT population and multiple subgroups defined by baseline demographics and lesion characteristics.

CSF levels of HoxB3 and YKL-40 may predict conversion from clinically isolated syndrome to relapsing remitting multiple sclerosis

INTRODUCTION

Multiple sclerosis (MS) often initiates with an acute episode of neurological disturbance, known as clinically isolated syndrome (CIS). There is an unmet need for biomarkers that differentiate patients who will convert to MS and who will remain as CIS after the first attack.

METHODS

First attack serum and cerebrospinal fluid (CSF) samples of 33 CIS patients were collected and these patients were divided as those who converted to MS (CIS-MS, n=17) and those who continued as CIS (CIS-CIS, n=16) in a 3-year follow-up period. Levels of homeobox protein Hox-B3 (HoxB3) and YKL-40 were measured by ELISA in samples of CIS-CIS, CIS-MS, relapsing remitting MS (RRMS) patients (n=15) and healthy controls (n=20).

RESULTS

CIS-CIS patients showed significantly reduced CSF levels of YKL-40 and increased serum/CSF levels of HoxB3 compared with CIS-MS and RRMS patients. CIS-MS and RRMS patients had comparable YKL-40 and HoxB3 level profiles. Receiver operating characteristic (ROC) curve analysis showed the highest sensitivity for CSF HoxB3 measurements in prediction of CIS-MS conversion. Kaplan-Meier analysis demonstrated that CIS patients with lower CSF HoxB3 (<3.678 ng/ml) and higher CSF YKL-40 (>654.9 ng/ml) displayed a significantly shorter time to clinically definite MS.

CONCLUSION

CSF levels of HoxB3 and YKL-40 appear to predict CIS to MS conversion, especially when applied in combination. HoxB3, which is a transcription factor involved in immune cell activity, stands out as a potential candidate molecule with biomarker capacity for MS.

Single-subject structural cortical networks in clinically isolated syndrome

BACKGROUND

Structural cortical networks (SCNs) represent patterns of coordinated morphological modifications in cortical areas, and they present the advantage of being extracted from previously acquired clinical magnetic resonance imaging (MRI) scans. SCNs have shown pathophysiological changes in many brain disorders, including multiple sclerosis.

OBJECTIVE

To investigate alterations of SCNs at the individual level in patients with clinically isolated syndrome (CIS), thereby assessing their clinical relevance.

METHODS

We analyzed baseline data collected in a prospective multicenter (MAGNIMS) study. CIS patients (n = 60) and healthy controls (n = 38) underwent high-resolution 3T MRI. Measures of disability and cognitive processing were obtained for patients. Single-subject SCNs were extracted from brain 3D-T1 weighted sequences; global and local network parameters were computed.

RESULTS

Compared to healthy controls, CIS patients showed altered small-world topology, an efficient network organization combining dense local clustering with relatively few long-distance connections. These disruptions were worse for patients with higher lesion load and worse cognitive processing speed. Alterations of centrality measures and clustering of connections were observed in specific cortical areas in CIS patients when compared with healthy controls.

CONCLUSION

Our study indicates that SCNs can be used to demonstrate clinically relevant alterations of connectivity in CIS.

Radiologically Isolated Syndrome: A Review for Neuroradiologists

Radiologically isolated syndrome refers to an entity in which white matter lesions fulfilling the criteria for multiple sclerosis occur in individuals without a history of a clinical demyelinating attack or alternative etiology. Since its introduction in 2009, the diagnostic criteria of radiologically isolated syndrome and its clinical relevance have been widely debated by neurologists and radiologists. The aim of the present study was to review the following: 1) historical evolution of radiologically isolated syndrome criteria, 2) clinical and imaging findings in adults and children with radiologically isolated syndrome, 3) imaging features of patients with radiologically isolated syndrome at high risk for conversion to MS, and 4) challenges and controversies for work-up, management, and therapeutic interventions of patients with radiologically isolated syndrome.

MRI features associated with rapid disease activity in clinically isolated syndrome patients at high risk for multiple sclerosis

Clinically isolated syndrome (CIS) is a central nervous system inflammatory and demyelinating event that lasts at least 24 h and can represent the first episode of relapsing-remitting multiple sclerosis. MRI is an important imaging tool in the diagnosis and longitudinal monitoring of CIS progression. Accurate differential diagnosis of high-risk versus low-risk CIS is important because high-risk CIS patients could be treated early. Although a few studies have previously characterized CIS and explored possible imaging predictors of CIS conversion to MS, it remains unclear which amongst the commonly measured MRI features, if any, are good predictors of rapid disease progression in CIS patients. The goal of this review paper is to identify MRI features in high-risk CIS patients that are associated with rapid disease activity within 5 years as measured by clinical disability.

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry

Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern classification using SVMs facilitates predicting conversion to clinically definite multiple sclerosis (CDMS) from clinically isolated syndrome (CIS). We used baseline MRI data from 364 patients with CIS, randomised to interferon beta-1b or placebo. Non-linear SVMs and 10-fold cross-validation were applied to predict converters/non-converters (175/189) at two years follow-up based on clinical and demographic data, lesion-specific quantitative geometric features and grey-matter-to-whole-brain volume ratios. We applied linear SVM analysis and leave-one-out cross-validation to subgroups of converters (n = 25) and non-converters (n = 44) based on cortical grey matter segmentations. Highest prediction accuracies of 70.4% (p = 8e-5) were reached with a combination of lesion-specific geometric (image-based) and demographic/clinical features. Cortical grey matter was informative for the placebo group (acc.: 64.6%, p = 0.002) but not for the interferon group. Classification based on demographic/clinical covariates only resulted in an accuracy of 56% (p = 0.05). Overall, lesion geometry was more informative in the interferon group, EDSS and sex were more important for the placebo cohort. Alongside standard demographic and clinical measures, both lesion geometry and grey matter based information can aid prediction of conversion to CDMS.

Intrathecal IgM production is a strong risk factor for early conversion to multiple sclerosis

OBJECTIVES

To evaluate intrathecal immunoglobulin M (IgM) production, as compared to previously established risk factors, as risk factor for conversion from clinically isolated syndrome (CIS) to multiple sclerosis (MS) and to explore the association of intrathecal IgM production with onset age and radiologic and CSF findings in CIS/early MS.

METHODS

Comprehensive CSF data, including oligoclonal immunoglobulin G (IgG) bands (OCB) and calculated intrathecal IgM and IgG production, were collected in a prospective study of 150 patients with CIS/early MS with regular clinical and MRI assessments.

RESULTS

Intrathecal IgM production >0% occurred in 23.2% (33/142) of patients, who were on average 5 years younger at disease onset (p = 0.013) and more frequently had infratentorial lesions (18/32, 56.3%) than patients without intrathecal IgM production (33/104, 31.7%, p = 0.021). In multivariable Cox regression analyses, intrathecal IgM production in patients with a CIS (n = 93, median clinical and MRI follow-up 24 and 21 months) was strongly associated with conversion to MS according to the McDonald 2010 criteria (hazard ratio [95% confidence interval] 3.05 [1.45-6.44], p = 0.003) after adjustment for age (0.96 [0.93-1.00], p = 0.059), OCB (0.92 [0.33-2.61], p = 0.879), intrathecal IgG production (0.98 [0.48-1.99], p = 0.947), and radiologic evidence of dissemination in space (2.63 [1.11-6.22], p = 0.028).

CONCLUSION

Intrathecal IgM production is a strong independent risk factor for early conversion to MS and may thus represent a clinically meaningful marker for predicting future disease activity in patients with a CIS.

Changing patterns of multiple sclerosis in Korea: Toward a more baseline MRI lesions and intrathecal humoral immune responses

BACKGROUND

The environmental risks of multiple sclerosis (MS), including adolescent obesity and vitamin D deficiency, are increasing in Korea. We aimed to determine whether the patterns and/or severity of MS in Korea can change according to the year of birth or disease onset.

METHODS

Two hundred and sixty-six patients with adult-onset MS, including 164 with an available baseline magnetic resonance imaging (MRI), were retrospectively included from 17 nationwide referral hospitals in Korea. The demographics, MRI T2 lesion burden at disease onset, cerebrospinal fluid markers, and prognosis were assessed.

RESULTS

The birth year, time from disease onset to first MRI, and female sex were associated with a higher number of baseline MRI T2 lesions. The birth year was also associated with the presence of oligoclonal band in the cerebrospinal fluid and high immunoglobin G index. An increased female/male ratio was observed among those with a more recent year of birth and/or disease onset.

CONCLUSIONS

In Korea, the disease pattern of adult-onset MS may be changing toward a more baseline T2 MRI lesions, intrathecal humoral immune responses, and also higher female ratio.

Infratentorial and spinal cord lesions: Cumulative predictors of long-term disability?

Objective:

The objective of the study was to determine whether early infratentorial and/or spinal cord lesions are long-term cumulative predictors of disability progression in multiple sclerosis (MS).

Methods:

We selected 153 MS patients from the longitudinal Amsterdam MS cohort. Lesion analysis was performed at baseline and year 2. Disability progression after 6 and 11 years was measured using the Expanded Disability Status Scale (EDSS) and EDSS-plus (including 25-foot walk and 9-hole peg test). Patients with spinal cord or infratentorial lesions were compared for the risk of 6- and 11-year disability progression to patients without spinal cord or infratentorial lesions, respectively. Subsequently, patients with lesions on both locations were compared to patients with only spinal cord or only infratentorial lesions.

Results:

Baseline spinal cord lesions show a higher risk of 6-year EDSS progression (odds ratio (OR): 3.6, p = 0.007) and EDSS-plus progression (OR: 2.5, p = 0.028) and 11-year EDSS progression (OR: 2.8, p = 0.047). Patients with both infratentorial and spinal cord lesions did not have a higher risk of 6-year disability progression than patients with only infratentorial or only spinal cord lesions.

Conclusion:

The presence of early spinal cord lesions seems to be a dominant risk factor of disability progression. Simultaneous presence of early infratentorial and spinal cord lesions did not undisputedly predict disability progression.

Early imaging predictors of longer term multiple sclerosis risk and severity in acute optic neuritis

Background

Biomarkers are urgently required for predicting the likely progression of multiple sclerosis (MS) at the earliest stages of the disease to aid in personalised therapy.

Objective

We aimed to examine early brain volumetric and microstructural changes and retinal nerve fibre layer thinning as predictors of longer term MS severity in patients with clinically isolated syndromes (CIS).

Methods

Lesion metrics, brain and regional atrophy, diffusion fractional anisotropy and retinal nerve fibre layer thickness were prospectively assessed in 36 patients with CIS over the first 12 months after presentation and compared with clinical outcomes at longer term follow-up [median (IQR) = 8.5 (7.8–8.9) years].

Results

In total, 25 (69%) patients converted to MS and had greater baseline lesion volume (p = 0.008) and number (p = 0.03)than CIS patients. Over the initial 12 months, new lesions (p = 0.0001), retinal nerve fibre layer thinning (p = 0.04) and ventricular enlargement (p = 0.03) were greater in MS than CIS patients. In MS patients, final Expanded Disability Status Scale score correlated with retinal nerve fibre layer thinning over the first 12 months (ρ = −0.67, p = 0.001).

Conclusions

Additional to lesion metrics, early measurements of fractional anisotropy and retinal nerve fibre layer thinning are informative about longer term clinical outcomes in CIS.

The Relevance of Neuroimaging Findings to Physical Disability in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system and one of the leading causes of disability in young adults. While some patients with MS have a benign course in which they develop limited disability even after many years, other patients have a rapidly progressive course resulting in severe disability. However, the progression of the disease, particularly disability, is currently a predictable course with neuroimaging features to some extend. Magnetic resonance imaging (MRI) is not only the main diagnostic tool but also used to monitor response to therapies, thanks to its high sensitivity and ability to identify clinically silent lesions. This report presents a literature review which examines in detail the relationship between MRI findings and disability.

Magnetic resonance imaging as a prognostic disability marker in clinically isolated syndrome: A systematic review

Magnetic resonance imaging (MRI) is the key prognostic tool in people with a clinically isolated syndrome (CIS). There is increasing interest in treating people following a CIS in the hope that conversion to multiple sclerosis (MS) will be prevented and future disability reduced. So far, the prognostic value of MRI for disability following a CIS has not been evaluated systematically. We systematically searched MEDLINE and EMBASE. Cohort studies were selected if they reported associations of MRI and disability following a CIS, included at least 50 people with a CIS at baseline, had at least 5 years of follow-up and obtained at least one structural MRI measurement (T1 lesions, T2 lesions, T1 contrast-enhancing lesions or brain atrophy). We assessed the studies for quality and rated the completeness of MRI reporting. In total, 13 studies were identified reporting on the following: T2 lesion number and volume, T2 infratentorial lesion number and volume, T1 contrast-enhancing lesions and grey matter fraction. T2 brain lesion number determined soon after the occurrence of a CIS was associated with disability progression after 5-7 years, with an increased risk when 10 or more lesions were present. Infratentorial lesions were also associated with a higher risk of subsequent disability. The number and distribution of MRI-visible lesions soon after a CIS are associated with disability later on, and may offer additional useful information when making treatment decisions in people with early MS. Further work is required to determine whether other measures have a higher predictive potential.

Monitoring of Lymphocyte Populations During Treatment with Interferon-β-1b to Predict Multiple Sclerosis Disability Progression

The authors aim to understand how lymphocyte populations could predict the course of multiple sclerosis (MS) in people treated with interferon-β (IFN-β). Twenty-five male patients and 72 female patients were analyzed in the study. Peripheral blood samples were taken before and 5 years after the treatment with IFN-β. Lymphocyte subsets were analyzed by flow cytometry. The authors compared lymphocyte parameters between confirmed sustained progression (CSP) and non-CSP groups by using Welch's one-way analysis of means or a chi-square test of independence. A penalized (lasso) logistic regression model was fitted to identify the combination of lymphocyte parameters for potential biomarkers. The combination of lymphocyte counts, relative CD3+/CD25+ cells, absolute CD8 T cells, absolute CD8+/CD38+ cells, absolute CD38+ cells, and relative CD5+/CD19+ cells was identified as potential biomarker for the IFN-β treatment to monitor MS development in relation to CSP. The results suggest that other biomarkers aid in patient observation, predict a favorable outcome, and assist in the decision-making process for the early therapy escalation.

Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach

Magnetic resonance imaging (MRI) scans play a pivotal role in the evaluation of patients presenting with a clinically isolated syndrome (CIS), as these may depict brain lesions suggestive of an inflammatory cause. We hypothesized that it is possible to predict the conversion from CIS to multiple sclerosis (MS) based on the baseline MRI scan by studying image features of these lesions.

We analyzed 84 patients diagnosed with CIS from a prospective observational single center cohort. The patients were followed up for at least three years. Conversion to MS was defined according to the 2010 McDonald criteria. Brain lesions were segmented based on 3D FLAIR and 3D T1 images. We generated brain lesion masks by a computer assisted manual segmentation. We also generated a set of automated segmentations using the Lesion Segmentation Toolbox for SPM to assess the influence of different segmentation methods. Shape and brightness features were automatically calculated from the segmented masks and used as input data to train an oblique random forest classifier. Prediction accuracies of the resulting model were validated through a three-fold cross-validation.

Conversion from CIS to MS occurred in 66 of 84 patients (79%). The conversion or non-conversion was predicted correctly in 71 patients based on shape features derived from the computer assisted manual segmentation masks (84.5% accuracy). This predictor was more accurate than predicting conversion using dissemination in space at baseline according to the 2010 McDonald criteria (75% accuracy). While shape features strongly contributed to the accuracy of the predictor, including intensity features did not further improve performance.

As patients who convert to definite MS benefit from early treatment, an early classification model is highly desirable. Our study shows that shape parameters of lesions can contribute to predicting the future course of CIS patients more accurately.

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A random forest tool can help to identify patients who convert from clinical isolated syndrome into multiple sclerosis (MS).

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The classifier is driven by shape features of lesions in the first MR scan.

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The found shape features reflect the typical ovoid growth of MS lesions.

MRI in predicting conversion to multiple sclerosis within 1 year

OBJECTIVES

Most patients diagnosed with multiple sclerosis (MS) present with a clinically isolated syndrome (CIS). We aimed to verify previously reported imaging and clinical findings, and to identify new MRI findings that might serve as prognostic factors for a second clinical episode or a change in the MRI scan during the first year following a CIS.

MATERIALS AND METHODS

We identified from our medical records, 46 individuals who presented with an episode of CIS, which was followed clinically and with imaging studies. A neuroradiologist blinded to the clinical data reviewed the images and recorded the number of lesions, lesion location, and the largest longitudinal diameter of the lesion.

RESULTS

One year after the first MRI, 25 (54%) patients had progressed to MS. The clinical presentation of those who were and were not diagnosed with MS was predominantly motor or sensory deficit. Patients with lesions that were temporal, occipital, or perpendicular to the corpus callosum at the first episode were more likely to have recurrence. Individuals with a combination of more than 13 lesions, with maximal lesion length greater than 0.75 cm, and a lesion perpendicular to the corpus callosum, had a 19 times higher chance of conversion MS during the following year.

CONCLUSIONS

Assessment of the number of lesions, lesion location, and maximal lesion size can predict the risk to develop another clinical episode or a new lesion/new enhancement in MRI during the year after CIS. For patients with a higher risk of recurrence, we recommend closer follow-up.

Multi-component relaxation in clinically isolated syndrome: Lesion myelination may predict multiple sclerosis conversion

We performed a longitudinal case-control study on patients with clinically isolated syndrome (CIS) with the aid of quantitative whole-brain myelin imaging. The aim was (1) to parse early myelin decay and to break down its distribution pattern, and (2) to identify an imaging biomarker of the conversion into clinically definite Multiple Sclerosis (MS) based on in vivo measurable changes of myelination.

Imaging and clinical data were collected immediately after the onset of first neurological symptoms and follow-up explorations were performed after 3, 6, and, 12 months. The multi-component Driven Equilibrium Single Pulse Observation of T1/T2 (mcDESPOT) was applied to obtain the volume fraction of myelin water (MWF) in different white matter (WM) regions at every time-point. This measure was subjected to further voxel-based analysis with the aid of a comparison of the normal distribution of myelination measures with an age and sex matched healthy control group. Both global and focal relative myelination content measures were retrieved.

We found that (1) CIS patients at the first clinical episode suggestive of MS can be discriminated from healthy control WM conditions (p < 0.001) and therewith reproduced our earlier findings in late CIS, (2) that deficient myelination in the CIS group increased in T2 lesion depending on the presence of gadolinium enhancement (p < 0.05), and (3) that independently the CIS T2 lesion relative myelin content provided a risk estimate of the conversion to clinically definite MS (Odds Ratio 2.52).

We initially hypothesized that normal appearing WM myelin loss may determine the severity of early disease and the subsequent risk of clinically definite MS development. However, in contrast we found that WM lesion myelin loss was pivotal for MS conversion. Regional myelination measures may thus play an important role in future clinical risk stratification.

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The multicomponent relaxation method mcDESPOT allowed 3D resolved data acquisition appropriate for group comparison and voxel-wise analysis.

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Myelin imaging in early clinically isolated syndrome revealed initial imaging widespread myelin loss even in normal appearing brain tissue.

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In clinically isolated syndrome the myelin measures varied depending on the presence of Gadolinium enhancement.

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Short-term risk of clinically isolated syndrome to convert to multiple sclerosis was determined by myelin measures within white matter lesions.

Multiple Sclerosis: Epidemiologic, Clinical, and Therapeutic Aspects

Multiple sclerosis (MS) is a chronic autoimmune and degenerative disease of the central nervous system that affects young people. MS develops in genetically susceptible individuals exposed to different unknown triggering factors. Different phenotypes are described. About 15% of patients present with a primary progressive course and 85% with a relapsing-remitting course. An increasing number of disease-modifying treatments has emerged. Although encouraging, the number of drugs challenges the neurologist because each treatment has its own risk-benefit profile. Patients should be involved in the decision-making process to ensure good treatment and safety monitoring adherence.

Prediction of Conversion from Clinically Isolated Syndrome to Multiple Sclerosis According to Baseline Characteristics: A Prospective Study

Objective

Clinically isolated syndrome (CIS) is a clinical state that proceeds with inflammation and demyelination, suggestive of multiple sclerosis (MS) in the central nervous system in the absence of other alternative diagnoses. The purpose of this study was to determine in a prospective cohort, the predictor factors in conversion from CIS to MS on the basis of clinical, magnetic resonance (MR) imaging and cerebrospinal fluid (CSF) findings.

Methods

Forty-one CIS patients were included in this study and followed up for at least two years.

Results

Clinically, polysymptomatic or sensorial involvement, good prognostic factors and complete response to pulse therapy were found to be of prognostic value in conversion to MS. A greater presence of oligoclonal bands in CSF was identified in the converted group (92.8%). In terms of localization, presence of callosal lesion (71.4%), periventricular lesion (97.1%), Gd-enhanced lesion (48.6%), black hole (54.2%) and brainstem lesion (57.1%) was statistically significant in terms of conversion to MS.

Conclusion

A carefully performed neurological assessment of symptoms and signs, and evaluation of lesions on MR combined with CSF findings are important for identifying the risk of conversion to MS. This information may be useful when considering treatment in CIS patients instead of waiting for conversion to MS.

Clinically isolated syndromes or clinically isolated patients? A patient and clinician perspective on the utility of CIS as a diagnosis

BACKGROUND

The term "Clinically Isolated Syndrome" (CIS) was introduced to describe a first clinical neurologic episode suggestive of an inflammatory demyelinating CNS disorder. Thereafter, the risk of developing clinically definite multiple sclerosis ranges from 20% to 80%, depending on a number of prognostic factors. Although the concept of CIS has been an important component in improving our understanding of risk levels in Multiple Sclerosis and prognosis, communicating uncertainty in this context remains a challenge for both patients and their clinicians. We therefore wished to explore both the patients understanding of the concept of CIS and the subsequent impact of a diagnosis. We also explored the concept of CIS from the clinician's perspective.

METHODS

The study uses a qualitative descriptive design involving both a semi-structured interview of patients with CIS as well as a short questionnaire sent to practising clinicians in the Republic of Ireland. Narrative data was coded onto themes.

RESULTS

Thirty CIS patients were interviewed. The majority of patients understood the term "CIS" but not the link between CIS and MS. Two themes were identified: emotional reactions following CIS diagnosis; and terminology and communication. Confusion and anxiety among patients due to inconsistent communication of CIS was identified. Of the thirty-three clinicians surveyed, only thirty-nine per cent found the term "CIS" clinically useful. Eighteen per cent of clinicians diagnosed MS from the CIS case vignette provided.

CONCLUSION

In the diagnosis of a first demyelinating event, use of the term "CIS" is confusing to patients and inconsistent among clinicians. We suggest that the term "CIS" be abandoned in favour of terminology that reflects both its pathogenesis and inherent risk of subsequent MS.