Performance of the 2017 and 2010 Revised McDonald Criteria in Predicting MS Diagnosis After a Clinically Isolated Syndrome: A MAGNIMS Study

Glial cell injury and atrophied lesion volume as measures of chronic multiple sclerosis inflammation

BACKGROUND

Atrophied lesion volume (aLV), a proposed biomarker of disability progression in multiple sclerosis (MS) and transition into progressive MS (PMS), depicts chronic periventricular white matter (WM) pathology. Meningeal infiltrates, imaged as leptomeningeal contrast enhancement (LMCE), are linked with greater cortical pathology.

OBJECTIVES

To determine the relationship between serum-derived proteomic data with the development of aLV and LMCE in a heterogeneous group of people with MS (pwMS).

METHODS

Proteomic and MRI data for 202 pwMS (148 clinically isolated syndrome /relapsing-remitting MS and 54 progressive MS (PMS)) were acquired at baseline and at 5.4-year follow-up. The concentrations of 21 proteins related to multiple MS pathophysiology pathways were derived using a custom-developed Proximity Extension Assay on the Olink™ platform. The accrual of aLV was determined as the volume of baseline T2-weighted lesions that were replaced by cerebrospinal fluid over the follow-up. Regression models and age-adjusted analysis of covariance (ANCOVA) were used.

RESULTS

Older age (standardized beta = 0.176, p = 0.022), higher glial fibrillary acidic protein (standardized beta = 0.312, p = 0.001), and lower myelin oligodendrocyte glycoprotein levels (standardized beta = -0.271, p = 0.002) were associated with accrual of aLV over follow-up. This relationship was driven by the pwPMS population. The presence of LMCE at the follow-up visit was not predicted by any baseline proteomic biomarker nor cross-sectionally associated with any protein concentration.

CONCLUSION

Proteomic markers of glial activation are associated with chronic lesional WM pathology (measured as aLV) and may be specific to the progressive MS phenotype. LMCE presence in MS does not appear to relate to proteomic measures.

Multiple Sclerosis: Clinical Update and Clinically-Oriented Radiologic Reporting

Multiple sclerosis (MS) is a chronic inflammatory disease of the nervous system. MR imaging findings play an integral part in establishing diagnostic hallmarks of the disease during initial diagnosis and evaluating disease status. Multiple iterations of diagnostic criteria and consensus guidelines are put forth by various expert groups incorporating imaging of the brain and spine, and efforts have been made to standardize imaging protocols for MS. Emerging ancillary imaging findings have also attracted increasing interests and should be sought for on radiologic examination. In this paper, the authors review the clinical guidelines and approach to imaging of MS and related disorders, focusing on clinically impactful image interpretation and MR imaging reporting.

Predicting the conversion from clinically isolated syndrome to multiple sclerosis: An explainable machine learning approach

INTRODUCTION

Predicting the conversion of clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) is critical to personalizing treatment planning and benefits for patients. The aim of this study is to develop an explainable machine learning (ML) model for predicting this conversion based on demographic, clinical, and imaging data.

METHOD

The ML model, Extreme Gradient Boosting (XGBoost), was employed on the public dataset of 273 Mexican mestizo CIS patients with 10-year follow-up. The data was divided into a training set for cross-validation and feature selection, and a holdout test set for final testing. Feature importance was determined using the SHapley Additive Explanations library (SHAP). Then, two experiments were conducted to optimize the model's performance by selectively adding variables and selecting the most contributive variables for the final model.

RESULTS

Nine variables including age, gender, schooling, motor symptoms, infratentorial and periventricular lesion at imaging, oligoclonal band in cerebrospinal fluid, lesion and symptoms types were significant. The model achieved an accuracy of 83.6 %, AUC of 91.8 %, sensitivity of 83.9 %, and specificity of 83.4 % in cross-validation. In the final testing, the model achieved an accuracy of 78.3 %, AUC of 85.8 %, sensitivity of 75 %, and specificity of 81.1 %. Finally, a web-based demo of the model was created for testing purposes.

CONCLUSION

The model, focusing on feature selection and interpretability, effectively stratifies risk for treatment decisions and disability prevention in MS patients. It provides a numerical risk estimate for CDMS conversion, enhancing transparency in clinical decision-making and aiding in patient care.

Transcranial magnetic stimulation enhances the specificity of multiple sclerosis diagnostic criteria: a critical narrative review

Background

Multiple sclerosis (MS) is an immune-mediated neurodegenerative disease that involves attacks of inflammatory demyelination and axonal damage, with variable but continuous disability accumulation. Transcranial magnetic stimulation (TMS) is a noninvasive method to characterize conduction loss and axonal damage in the corticospinal tract. TMS as a technique provides indices of corticospinal tract function that may serve as putative MS biomarkers. To date, no reviews have directly addressed the diagnostic performance of TMS in MS. The authors aimed to conduct a critical narrative review on the diagnostic performance of TMS in MS.

Methods

The authors searched the Embase, PubMed, Scopus, and Web of Science databases for studies that reported the sensitivity and/or specificity of any reported TMS technique compared to established clinical MS diagnostic criteria. Studies were summarized and critically appraised for their quality and validity.

Results

Seventeen of 1,073 records were included for data extraction and critical appraisal. Markers of demyelination and axonal damage-most notably, central motor conduction time (CMCT)-were specific, but not sensitive, for MS. Thirteen (76%), two (12%), and two (12%) studies exhibited high, unclear, and low risk of bias, respectively. No study demonstrated validity for TMS techniques as diagnostic biomarkers in MS.

Conclusions

CMCT has the potential to: (1) enhance the specificity of clinical MS diagnostic criteria by "ruling in" true-positives, or (2) revise a diagnosis from relapsing to progressive forms of MS. However, there is presently insufficient high-quality evidence to recommend any TMS technique in the diagnostic algorithm for MS.

The diagnostic value of the central vein sign in radiologically isolated syndrome

OBJECTIVE

The radiologically isolated syndrome (RIS) represents the earliest detectable preclinical phase of multiple sclerosis (MS). Increasing evidence suggests that the central vein sign (CVS) enhances lesion specificity, allowing for greater MS diagnostic accuracy. This study evaluated the diagnostic performance of the CVS in RIS.

METHODS

Patients were prospectively recruited in a single tertiary center for MS care. Participants with RIS were included and compared to a control group of sex and age-matched subjects. All participants underwent 3 Tesla magnetic resonance imaging, including postcontrast susceptibility-based sequences, and the presence of CVS was analyzed. Sensitivity and specificity were assessed for different CVS lesion criteria, defined by proportions of lesions positive for CVS (CVS+) or by the absolute number of CVS+ lesions.

RESULTS

180 participants (45 RIS, 45 MS, 90 non-MS) were included, representing 5285 white matter lesions. Among them, 4608 were eligible for the CVS assessment (970 in RIS, 1378 in MS, and 2260 in non-MS). According to independent ROC comparisons, the proportion of CVS+ lesions performed similarly in diagnosing RIS from non-MS than MS from non-MS (p = 0.837). When a 6-lesion CVS+ threshold was applied, RIS lesions could be diagnosed with an accuracy of 87%. MS could be diagnosed with a sensitivity of 98% and a specificity of 83%. Adding OCBs or Kappa index to CVS biomarker increased the specificity to 100% for RIS diagnosis.

INTERPRETATION

This study shows evidence that CVS is an effective imaging biomarker in differentiating RIS from non-MS, with similar performances to those in MS.

Review of multiple sclerosis: Epidemiology, etiology, pathophysiology, and treatment

Multiple sclerosis (MS) is a chronic autoimmune disease with demyelination, inflammation, neuronal loss, and gliosis (scarring). Our object to review MS pathophysiology causes and treatment. A Narrative Review article was conducted by searching on Google scholar, PubMed, Research Gate about relevant keywords we exclude any unique cases and case reports. The destruction of myelinated axons in the central nervous system reserves this brunt. This destruction is generated by immunogenic T cells that produce cytokines, copying a proinflammatory T helper cells1-mediated response. Autoreactive cluster of differentiation 4 + cells, particularly the T helper cells1 subtype, are activated outside the system after viral infections. T-helper cells (cluster of differentiation 4+) are the leading initiators of MS myelin destruction. The treatment plan for individuals with MS includes managing acute episodes, using disease-modifying agents to decrease MS biological function of MS, and providing symptom relief. Management of spasticity requires physiotherapy, prescription of initial drugs such as baclofen or gabapentin, secondary drug options such as tizanidine or dantrolene, and third-line treatment such as benzodiazepines. To treat urinary incontinence some options include anticholinergic medications such as oxybutynin hydrochloride, tricyclic antidepressants (such as amitriptyline), and intermittent self-catheterization. When it comes to bowel problems, one can try to implement stool softeners and consume a high roughage diet. The review takes about MS causes Pathophysiology and examines current treatment strategies, emphasizing the advancements in disease-modifying therapies and symptomatic treatments. This comprehensive analysis enhances the understanding of MS and underscores the ongoing need for research to develop more effective treatments.

Time to involve the multiple sclerosis expert community at large when revising the McDonald diagnostic criteria

Prof. Kurtzke once said, "Multiple sclerosis is what a good clinician would call multiple sclerosis." Recent McDonald's diagnostic criteria revisions have allowed for earlier diagnoses over the past decades. Revisions often allowed increasing sensitivity but at the expense of lowering specificity. In this correspondence, I suggest that the multiple sclerosis expert community worldwide should be given the opportunity to comment and provide feedback on the proposed revisions of the diagnostic criteria before their publication via providing a duration where open commentaries are welcomed to allow for the expert panel to incorporate diverse feedback to improve the final product.

Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis

Importance

Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice.

Objective

To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI).

Design, Setting, and Participants

This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2).

Exposures

MS/CIS vs non-MS conditions.

Main Outcomes and Measures

Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model.

Results

The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis.

Conclusions and Relevance

The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

Real-life evaluation of the 2017 McDonald criteria for relapsing-remitting multiple sclerosis after a clinically isolated syndrome confirms a gain in time-to-diagnosis

BACKGROUND

Previous cohort studies evaluating the performances of the McDonald criteria suffered from bias regarding real-life conditions. We aimed to evaluate the probability of diagnosing relapsing-remitting multiple sclerosis (MS) at several timepoints from the first medical evaluation and the gain in time-to-diagnosis with the 2017 McDonald criteria compared with the 2001, 2005 and 2010 versions in real life.

METHODS

Patients with a first demyelinating event suggestive of MS between 2002 and 2020 were included in the ReLSEP, an exhaustive and prospectively incremented registry of MS patients in North-Eastern France. We estimated the probability of being positive at the first medical evaluation and at five timepoints according to the four versions of criteria using Kaplan-Meier estimators and Cox models.

RESULTS

A total of 2220 patients were followed up for a median of 7.1 years. At baseline, 31.7%, 32.1%, 36.6% and 54.0% of patients, respectively, fulfilled the 2001, 2005, 2010 and 2017 McDonald criteria. Using the 2017 criteria, the gain in time-to-diagnosis was 3.7 months compared with the 2010 criteria. The presence of intrathecal synthesis of immunoglobulin G in the McDonald 2017 criteria led to a 1.8-month reduction in median time-to-diagnosis compared to a version of McDonald 2017 without this criteria.

CONCLUSIONS

In real-life, the 2017 McDonald criteria revision undoubtedly shortened time-to-diagnosis.

The Impact of Insurance Restrictions in Newly Diagnosed Individuals With Multiple Sclerosis

BACKGROUND

The medical system in the United States has been riddled with insurance restrictions used by insurance companies to limit health care costs. The effects of insurance restrictions on patients receiving disease-modifying therapies for multiple sclerosis (MS) have not been specifically studied.

METHODS

A retrospective cross-sectional study of 52 individuals recently diagnosed with MS at a tertiary neurology clinic was conducted to measure the association between prior authorization (PA) duration and other variables of interest. The Cox proportional hazards model was used to determine likelihood of approval. Further analysis included multivariable logistic regression to assess the influence of variables of interest on the initial decision from the insurance company and the effect of the PA on disease activity.

RESULTS

Of 52 PAs, 50% were initially denied. An initial denial decreased the likelihood of approval by 98% (HR, 0.02; 95% CI, <0.01-0.09; P < .001). The odds of denial for oral medications (odds ratio [OR], 4.91; 95% CI, 1.33-21.52; P = .02) and infusions (OR, 8.35; 95% CI, 1.10-88.77; P = .05) were significantly higher than for injections. Medicaid had higher odds of denial compared with commercial insurance (OR, 4.51; 95% CI, 1.13-22.01; P = .04). An initial denial by insurance significantly increased the likelihood of disease activity (OR, 6.18; 95% CI, 1.33-44.86; P = .03).

CONCLUSIONS

Insurance restrictions delay necessary treatments, increase the likelihood of disease activity, and rarely change the approved disease-modifying therapy. Reducing PAs may lead to improved outcomes for patients with MS.

Inclusion of optic neuritis in dissemination in space improves the performance of McDonald 2017 criteria in Hispanic people with suspected multiple sclerosis

BACKGROUND

Hispanic people compared to White people with multiple sclerosis (MS) are two times more likely to present with optic neuritis (ON). ON in dissemination in space (DIS) after a single attack is not part of the current McDonald 2017 criteria.

OBJECTIVE

To evaluate if adding ON in DIS (ON-modified criteria) improves the performance of the McDonald 2017 criteria in the diagnosis of MS after a single attack of ON.

METHODS

Retrospective study of 102 patients of Hispanic background. Cases were reviewed between 2017 and 2021. Clinical ON was reported for 35 cases. ON in DIS was verified for 28 patients via MRI, optical coherence tomography, and/or visual evoked potential. We investigated the performance of the McDonald 2017 criteria and ON-modified criteria and calculated sensitivity, specificity, positive and negative predictive values, and accuracy.

RESULTS

The ON-modified criteria significantly improved the performance of the McDonald 2017 criteria (p = 0.003) and identified an additional nine patients. Both sensitivity and accuracy increased from 64% to 74% and 62% to 71%, respectively, while specificity remained unchanged (40% (95% confidence interval (CI): 0.10, 0.70)).

CONCLUSION

This study provides evidence that the inclusion of ON in DIS improved the overall performance of the McDonald 2017 criteria among Hispanic people.

Metabolic Insights into Iron Deposition in Relapsing-Remitting Multiple Sclerosis via 7 T Magnetic Resonance Spectroscopic Imaging

OBJECTIVE

To investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition.

METHODS

7 T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 ± 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), "non-iron" (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions ("rim": distinct rim-shaped iron accumulation; "area": iron deposition across the entire lesions; "transition": transition between "area" and "rim" accumulation shape), and for lesion layers of "non-iron" and "rim" lesions. Furthermore, newly emerging "non-iron" and "iron" lesions were compared longitudinally, as measured before their appearance and one year later.

RESULTS

Thirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, "area" lesions exhibited a 65% higher mIns/tNAA (p = 0.035) than "rim" lesions. Comparing lesion layers of both "non-iron" and "rim" lesions, a steeper metabolic gradient of mIns/tNAA ("non-iron" +15%, "rim" +40%) and tNAA/tCr ("non-iron" -15%, "rim" -35%) was found in "iron" lesions, with the lesion core showing +22% higher mIns/tNAA (p = 0.005) and -23% lower tNAA/tCr (p = 0.048) in "iron" compared to "non-iron" lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in "iron" lesions (year 0: p = 0.013, year 1: p = 0.041) as opposed to "non-iron" lesions (year 0: p = 0.022, year 1: p = 0.231).

CONCLUSION

7 T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring.

Association of Very Early Treatment Initiation With the Risk of Long-term Disability in Patients With a First Demyelinating Event

BACKGROUND AND OBJECTIVES

Early treatment is associated with better long-term outcomes in patients with a first demyelinating event and early multiple sclerosis (MS). However, magnetic resonance (MR) findings are not usually integrated to construct propensity scores (PSs) when evaluating outcomes. We assessed the association of receiving very early treatment with the risk of long-term disability including an MR score (MRS) in patients with a first demyelinating event.

METHODS

We included 580 patients with a first demyelinating event prospectively collected between 1994 and 2021, who received at least 1 disease-modifying drug (DMD). Patients were classified into tertiles according to the cohort's distribution of the time from the first demyelinating event to the first DMD: first tertile (FT) or very early treatment (6 months; n = 194), second tertile (6.1-16 months, n = 192), and third tertile (TT) (16.1 months, n = 194). A 5-point MRS was built according to the sum of the following indicators: ≥9 brain lesions (1 point); ≥1 infratentorial lesion (1 point); ≥1 spinal cord (SC) lesion (1 point); ≥1 contrast-enhancing (CE) brain lesion (1 point); and ≥1 CE SC lesion (1 point). PS based on covariates and the MRS was computed for each of the outcomes. Inverse PS-weighted Cox and linear regression models assessed the risk of different outcomes between tertile groups. Finally, to confirm the role of MR in treatment decision, we studied the time elapsed from the first demyelinating event to treatment initiation according to the MRS in all patients with radiologic available information, renamed as raw-MRS.

RESULTS

Very early treatment decreased the risk of reaching Expanded Disability Status Scale 3.0 (hazard ratio [HR] 0.55, 95% CI 0.32-0.97), secondary progressive MS (HR 0.40, 95% CI 0.19-0.85), and sustained disease progression at 12 months after treatment initiation (HR 0.50, 95% CI 0.29-0.84), when compared with patients from the TT group. Patients from the FT group had a lower disability progression rate (β estimate -0.009, 95% CI -0.016 to -0.002) and a lower severe disability measured by the Patient-Determined Disease Step (β estimate -0.52, 95% CI -0.91 to -0.13) than the TT group. Finally, there was a 62.4% reduction in the median time between the first demyelinating event and the first-ever treatment initiation from patients displaying a raw-MRS 1 to patients with a raw-MRS 5.

DISCUSSION

Using PS models with and without MRS, we showed that treatment initiation at very early stages is associated with a reduction in the risk of long-term disability accrual in patients with a first demyelinating event.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that earlier treatment of patients with MS presenting with a first demyelinating event is associated with improved clinical outcomes.

Global Barriers to the Diagnosis of Multiple Sclerosis: Data From the Multiple Sclerosis International Federation Atlas of MS, Third Edition

BACKGROUND AND OBJECTIVES

Recent data suggest increasing global prevalence of multiple sclerosis (MS). Early diagnosis of MS reduces the burden of disability-adjusted life years and associated health care costs. Yet diagnostic delays persist in MS care and even within national health care systems with robust resources, comprehensive registries, and MS subspecialist referral networks. The global prevalence and characteristics of barriers to expedited MS diagnosis, particularly in resource-restricted regions, have not been extensively studied. Recent revisions to MS diagnostic criteria demonstrate potential to facilitate earlier diagnosis, but global implementation remains largely unknown.

METHODS

The Multiple Sclerosis International Federation third edition of the Atlas of MS was a survey that assessed the current global state of diagnosis including adoption of MS diagnostic criteria; barriers to diagnosis with respect to the patient, health care provider, and health system; and existence of national guidelines or national standards for speed of MS diagnosis.

RESULTS

Coordinators from 107 countries (representing approximately 82% of the world population), participated. Eighty-three percent reported at least 1 "major barrier" to early MS diagnosis. The most frequently reported barriers included the following: "lack of awareness of MS symptoms among general public" (68%), "lack of awareness of MS symptoms among health care professionals" (59%), and "lack of availability of health care professionals with knowledge to diagnose MS" (44%). One-third reported lack of "specialist medical equipment or diagnostic tests." Thirty-four percent reported the use of only 2017 McDonald criteria (McD-C) for diagnosis, and 79% reported 2017 McD-C as the "most commonly used criteria." Sixty-six percent reported at least 1 barrier to the adoption of 2017 McD-C, including "neurologists lack awareness or training" by 45%. There was no significant association between national guidelines pertaining to MS diagnosis or practice standards addressing the speed of diagnosis and presence of barriers to early MS diagnosis and implementation of 2017 McD-C.

DISCUSSION

This study finds pervasive consistent global barriers to early diagnosis of MS. While these barriers reflected a lack of resources in many countries, data also suggest that interventions designed to develop and implement accessible education and training can provide cost-effective opportunities to improve access to early MS diagnosis.

Conversion Predictors of Clinically Isolated Syndrome to Multiple Sclerosis in Mexican Patients: A Prospective Study

BACKGROUND

Clinically Isolated Syndrome (CIS) is the first clinical episode suggestive of Clinical Definite Multiple Sclerosis (CDMS). There are no reports on possible predictors of conversion to CDMS in Mexican mestizo patients.

AIM OF THE STUDY

To investigate immunological markers, clinical and paraclinical findings, and the presence of herpesvirus DNA to predict the transition from CIS to CDMS in Mexican patients.

METHODS

A single-center prospective cohort study was conducted with newly diagnosed patients with CIS in Mexico between 2006 and 2010. Clinical information, immunophenotype, serum cytokines, anti-myelin protein immunoglobulins, and herpes viral DNA were determined at the time of diagnosis.

RESULTS

273 patients diagnosed with CIS met the enrolment criteria; after 10 years of follow-up, 46% met the 2010 McDonald criteria for CDMS. Baseline parameters associated with conversion to CDMS were motor symptoms, multifocal syndromes, and alterations of somatosensory evoked potentials. The presence of at least one lesion on magnetic resonance imaging was the main factor associated with an increased risk of conversion to CDMS (RR 15.52, 95% CI 3.96-60.79, p = 0.000). Patients who converted to CDMS showed a significantly lower percentage of circulating regulatory T cells, cytotoxic T cells, and B cells, and the conversion to CDMS was associated with the presence of varicella-zoster virus and herpes simplex virus 1 DNA in cerebrospinal fluid and blood.

CONCLUSION

There is scarce evidence in Mexico regarding the demographic and clinical aspects of CIS and CDMS. This study shows several predictors of conversion to CDMS to be considered in Mexican patients with CIS.

The CXCL13 Index as a Predictive Biomarker for Activity in Clinically Isolated Syndrome

Multiple sclerosis (MS) is a clinically heterogenous disease. Currently, we cannot identify patients with more active disease who may potentially benefit from earlier interventions. Previous data from our lab identified the CXCL13 index (I_CXCL13), a measure of intrathecal production of CXCL13, as a potential biomarker to predict future disease activity in MS patients two years after diagnosis. Patients with clinically isolated syndrome (CIS) or radiologically isolated syndrome (RIS) underwent a lumbar puncture and blood draw, and the I_CXCL13 was determined. They were then followed for at least 5 years for MS activity. Patients with high I_CXCL13 were more likely to convert to clinically definite MS (82.4%) compared to those with low I_CXCL13 (10.0%). The data presented below demonstrate that this predictive ability holds true in CIS and RIS patients, and for at least five years compared to our initial two-year follow-up study. These data support the concept that I_CXCL13 has the potential to be used to guide immunomodulatory therapy in MS.

Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice

MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.

The prevalence and incidence of multiple sclerosis over the past 20 years in northern Japan

OBJECTIVES

The prevalence of multiple sclerosis (MS) in East Asia is thought to be lower than in Western countries. Globally, there is a trend of increasing MS prevalence. We investigated the changes in the prevalence and clinical phenotype of MS in the Tokachi province of Hokkaido in northern Japan, from 2001 to 2021.

METHODS

Data processing sheets were sent to all related institutions inside and outside the Tokachi area of Hokkaido island in Japan and were collected from April to May 2021. The prevalence according to the Poser's diagnostic criteria for MS was determined on March 31, 2021.

RESULTS

In 2021, the crude MS prevalence in northern Japan was 22.4/100,000 (95% confidence interval, 17.6-28.0). The prevalences of MS standardized by the Japanese national population in 2001, 2006, 2011, 2016, and 2021 were 6.9, 11.5, 15.3, 18.5, and 23.3, respectively. The female/male ratio was 4.0 in 2021, increased from 2.6 in 2001. We checked the prevalence using the 2017 revised McDonald criteria, and found only additional male patient who had not fulfilled Poser's criteria. The age- and sex-adjusted incidence of MS per 100,000 individuals increased from 0.09 in 1980-1984 to 0.99 in 2005-2009; since then, it has remained stable. The proportions of primary-progressive, relapsing-remitting, and secondary-progressive MS types in 2021 were 3%, 82%, and 15%, respectively.

CONCLUSION

Our results demonstrated a consistent increase in the prevalence of MS among the northern Japanese over 20 years, particularly in females, and consistently lower rates of progressive MS in northern Japan than elsewhere in the world.

Performance of McDonald 2017 multiple sclerosis diagnostic criteria and evaluation of genetic ancestry in patients with a first demyelinating event in Argentina

BACKGROUND

Information on performance of multiple sclerosis (MS) diagnostic criteria is scarce for populations from Latin America, Asia, or the Caribbean.

OBJECTIVE

To assess performance of revised 2017 McDonald criteria as well as evaluate genetic ancestry in a group of MS patients from Argentina experiencing a debut demyelinating event.

METHODS

Demographic and clinical characteristics, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) findings and new T2 lesions were recorded at baseline and during relapses. Diagnostic accuracy in predicting conversion to clinically defined MS (CDMS) based on initial imaging applying revised 2017 criteria was evaluated and genetic ancestry-informative markers analyzed.

RESULTS

Of 201 patients experiencing their first demyelinating event (median follow-up 60 months), CDMS was confirmed in 67. We found 2017 diagnostic criteria were more sensitive (84% vs 67%) and less specific (14% vs 33%) than 2010 criteria, especially in a group of patients revised separately, presenting positive oligoclonal bands (88% vs 8%). Genetic testing performed in 128 cases showed 72% of patients were of European ancestry and 27% presented genetic admixture.

CONCLUSION

2017 McDonald criteria showed higher sensitivity and lower specificity compared with 2010 criteria, shortening both time-to-diagnosis and time-to-treatment implementation.

Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective

In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.

Improvement in time to multiple sclerosis diagnosis: 25-year retrospective analysis from New York State MS Consortium (NYSMSC)

Judicious multiple sclerosis (MS) diagnosis and early start of disease modifying therapy significantly improves long-term disability outcomes in persons with MS (pwMS). Retrospective analysis based on 25-year New York State MS Consortium (NYSMSC) data determined the effect of changes in the respective diagnostic criteria in shortening the time between symptom onset to MS diagnosis. Based on 9378 current and historical MS cases, there was a significant decrease in time to diagnosis in pwMS from 1982–2001 to >2017 periods (average 4.2 vs. 1.1 years, p < 0.001). Additional improvements and better implementation of the MS diagnostic criteria can further decrease the diagnosis lag.

Leistungsfähigkeit der McDonald-Kriterien von 2017

Hintergrund

Die schnelle und zuverlässige Diagnose einer Multiplen Sklerose (MS) ist entscheidend, um eine angepasste verlaufsmodifizierende Therapie zu beginnen. Die 2017-Revision der McDonald-Kriterien hat das Ziel, eine einfachere und frühzeitigere MS-Diagnose mit hoher diagnostischer Genauigkeit zu ermöglichen.

Ziel der Arbeit/Fragestellung

In der vorliegenden Arbeit wurden die publizierten Arbeiten, die die Anwendung der McDonald-Kriterien von 2017 und 2010 miteinander verglichen haben, ausgewertet und bezüglich der diagnostischen Leistungsfähigkeit analysiert.

Material und Methoden

Mittels Literaturrecherche in der PubMed-Datenbank (Suchbegriff: McDonald criteria 2010 and McDonald criteria 2017) wurden 20 Studien und ein Übersichtsartikel mit insgesamt 3006 auswertbaren Patienten identifiziert.

Ergebnisse

Bei Anwendung der McDonald-Kriterien von 2017 konnte die Diagnose einer MS bei mehr Patienten (2277/3006 Patienten, 76 %) und in einem früheren Stadium (3–10 Monate) verglichen mit der Revision von 2010 (1562/3006 Patienten, 52 %) gestellt werden. Von den zusätzlichen MS-Diagnosen sind 193/715 auf die Anpassung der bildgebenden Kriterien der zeitlichen Dissemination und 536/715 auf die Einführung der oligoklonalen Banden als diagnostisches Kriterium zurückführen.

Diskussion

Die revidierten McDonald-Kriterien von 2017 erlauben die Diagnosestellung einer MS bei einem höheren Anteil an Patienten beim ersten klinischen Ereignis.

What is the potential of paramagnetic rim lesions as diagnostic indicators in multiple sclerosis?

INTRODUCTION

In multiple sclerosis (MS), paramagnetic rim lesions (PRLs) on MRI identify a subset of chronic active lesions (CALs), which have been linked through clinical and pathological studies to more severe disease course and greater disability accumulation. Beside their prognostic relevance, increasing evidence supports the use of PRL as a diagnostic biomarker.

AREAS COVERED

This review summarizes the most recent updates regarding the MRI pathophysiology of PRL, their prevalence in MS (by clinical phenotypes) vs mimicking conditions, and their potential role as diagnostic MS biomarkers. We searched PubMed with terms including 'multiple sclerosis' AND 'paramagnetic rim lesions' OR 'iron rim lesions' OR 'rim lesions' for manuscripts published between January 2008 and July 2022.

EXPERT OPINION

Current research suggests that PRL can improve the diagnostic specificity and the overall accuracy of MS diagnosis when used together with the dissemination in space MRI criteria and the central vein sign. Nevertheless, future prospective multicenter studies should further define the real-world prevalence and specificity of PRL. International guidelines are needed to establish methodological criteria for PRL identification before its implementation into clinical practice.

The Brave New World of Early Treatment of Multiple Sclerosis: Using the Molecular Biomarkers CXCL13 and Neurofilament Light to Optimize Immunotherapy

Multiple sclerosis (MS) is a highly heterogeneous disease involving a combination of inflammation, demyelination, and CNS injury. It is the leading cause of non-traumatic neurological disability in younger people. There is no cure, but treatments in the form of immunomodulatory drugs (IMDs) are available. Experience over the last 30 years has shown that IMDs, also sometimes called disease-modifying therapies, are effective in downregulating neuroinflammatory activity. However, there are a number of negatives in IMD therapy, including potential for significant side-effects and adverse events, uncertainty about long-term benefits regarding disability outcomes, and very high and increasing financial costs. The two dozen currently available FDA-approved IMDs also are heterogeneous with respect to efficacy and safety, especially long-term safety, and determining an IMD treatment strategy is therefore challenging for the clinician. Decisions about optimal therapy have been particularly difficult in early MS, at the time of the initial clinical demyelinating event (ICDE), at a time when early, aggressive treatment would best be initiated on patients destined to have a highly inflammatory course. However, given the fact that the majority of ICDE patients have a more benign course, aggressive immunosuppression, with its attendant risks, should not be administered to this group, and should only be reserved for patients with a more neuroinflammatory course, a decision that can only be made in retrospect, months to years after the ICDE. This quandary of moderate vs. aggressive therapy facing clinicians would best be resolved by the use of biomarkers that are predictive of future neuroinflammation. Unfortunately, biomarkers, especially molecular biomarkers, have not thus far been particularly useful in assisting clinicians in predicting the likelihood of future neuroinflammation, and thus guiding therapy. However, the last decade has seen the emergence of two highly promising molecular biomarkers to guide therapy in early MS: the CXCL13 index and neurofilament light. This paper will review the immunological and neuroscientific underpinnings of these biomarkers and the data supporting their use in early MS and will propose how they will likely be used to maximize benefit and minimize risk of IMDs in MS patients.

The kappa free light chain index and oligoclonal bands have a similar role in the McDonald criteria

Intrathecal production of kappa free light chains (KFLC) occurs in multiple sclerosis and can be measured using the KFLC index. KFLC index values can be determined more easily than oligoclonal bands (OB) detection and seem more sensitive than the immunoglobulin (Ig)G index to diagnose multiple sclerosis. We assessed the value of OB, KFLC index cut-offs 5.9, 6.6, and 10.61, and IgG index to diagnose multiple sclerosis with prospectively acquired data from a clinically isolated syndrome (CIS) inception cohort. We selected patients with sufficient data to determine OB positivity, MRI dissemination in space (DIS) and time (DIT), IgG index, and sufficient quantities of paired CSF and blood samples to determine KFLC indexes (n = 214). We used Kendall´s Tau coefficient to estimate concordance; calculated the number of additional diagnoses when adding each positive index to DIS and positive OB; performed survival analyses for OB and each index with the outcomes second attack and 2017 MRI DIS and DIT; and estimated the diagnostic properties of OB and the different indexes for the abovementioned outcomes at five years. OB were positive in 138 patients (64.5%), KFLC-5.9 in 136 (63.6%), KFLC-6.6 in 135 (63.1%), KFLC-10.61 in 126 (58.9%) and IgG index in 101 (47.2%). The highest concordance was between OB and KFLC-6.6 (τ=0.727) followed by OB and KFLC-5.9 (τ=0.716). Combining DIS plus OB or KFLC-5.9 increased the number of diagnosed patients by 11 (5.1%), with KFLC-6.6 by 10 (4.7%), with KFLC-10.61 by 9 (4.2%), and with IgG index by 3 (1.4%). Patients with positive OB or indexes reached second attack and MRI DIS and DIT faster than patients with negative results (P < 0.0001 except IgG index in second attack: P = 0.016). In multivariable Cox models [aHR (95% CI)], the risk for second attack was very similar between KFLC-5.9 [2.0 (0.9-4.3), P = 0.068] and KFLC-6.6 [2.1 (1.1-4.2), P = 0.035]. The highest risk for MRI DIS and DIT was demonstrated with KFLC-5.9 [4.9 (2.5-9.6), P < 0.0001], followed by KFLC-6.6 [3.4 (1.9-6.3), P < 0.0001]. KFLC-5.9 and KFLC-6.6 had a slightly higher diagnostic accuracy than OB for second attack (70.5, 71.1, and 67.8) and MRI DIS and DIT (85.7, 85.1, and 81.0). KFLC indexes 5.9 and 6.6 performed slightly better than OB to assess multiple sclerosis risk and in terms of diagnostic accuracy. Given the concordance between OB and these indexes, we suggest using DIS plus positive OB or positive KFLC index as a modified criterion to diagnose multiple sclerosis.

Role of artificial intelligence in MS clinical practice

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For medical applications, machine learning (including deep learning) are the most commonly used artificial intelligence (AI) approaches.

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It can improve multiple sclerosis (MS) diagnosis, prognostication and treatment monitoring.

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Thanks to AI, MRI and cognitive phenotypes of MS patients were identified.

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AI can shorten MRI protocols for MS, allowing the application of advanced techniques.

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It can reduce the human effort for MRI analysis, especially for lesion segmentation.

Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and management of patients with multiple sclerosis (MS), this disease is an ideal candidate for the application of AI techniques. In this narrative review, we are going to discuss the potential applications of AI for MS clinical practice, together with their limitations. Among their several advantages, ML algorithms are able to automate repetitive tasks, to analyze more data in less time and to achieve higher accuracy and reproducibility than the human counterpart. To date, these algorithms have been applied to MS diagnosis, prognosis, disease and treatment monitoring. Other fields of application have been improvement of MRI protocols as well as automated lesion and tissue segmentation. However, several challenges remain, including a better understanding of the information selected by AI algorithms, appropriate multicenter and longitudinal validations of results and practical aspects regarding hardware and software integration. Finally, one cannot overemphasize the paramount importance of human supervision, in order to optimize the use and take full advantage of the potential of AI approaches.