Misdiagnosis of multiple sclerosis: Impact of the 2017 McDonald criteria on clinical practice

Racial and Ethnic Disparities in Multiple Sclerosis Prevalence

BACKGROUND AND OBJECTIVES

The goal of this work was to determine whether the prevalence of multiple sclerosis (MS) varies by race and ethnicity.

METHODS

We conducted a retrospective cohort study of >2.6 million adults from the multiethnic, community-dwelling members of Kaiser Permanente Southern California. The complete electronic health records of individuals with at least 1 ICD-9 code for MS between January 1, 2008 and December 31, 2010 were reviewed. MS prevalence and 95% CIs stratified by age, sex, and race and ethnicity among 2010 members were estimated with binomial regression. Age- and sex-standardized prevalence was estimated according to the 2010 US Census population.

RESULTS

We identified 3,863 patients with MS. The average age of patients with prevalent MS was 51.7 years (SD 13.1 years), and 76.8% were women. The female preponderance was more pronounced among Black (81.2%) and Asian (83.6%) than White (76.3%) or Hispanic (74.5%) individuals with MS. Age- and sex-standardized MS prevalence per 100,000 was similarly high among Black (225.8, 95% CI 207.1-244.5) and White (237.7, 95% CI 228.2-247.2) and significantly lower among Hispanic (69.9, 95% CI 64.4-75.5) and Asian (22.6, 95% CI 17.1-28.1) persons. MS prevalence was highest between the ages of 35 and 64 years and declined after 65 years of age across all racial and ethnic groups. Among adults 18 to 24 years of age, the crude MS prevalence was low but was highest among Black and Hispanic young adults, lower in White people, and lowest in Asian/Pacific Islander individuals (48.5, 25.0, 18.0, and 7.1 per 100,000, respectively).

DISCUSSION

MS prevalence varies by race and ethnicity, being similarly high in White and Black and significantly lower in Hispanic and Asian persons in Southern California. Taken together with previous studies, these findings indicate that the burden of MS in the US Black community has long been underrecognized. More studies are needed to determine whether MS is an emerging disease among US Hispanic adults and whether MS susceptibility and prevalence vary among Hispanic or Asian individuals from different cultures or ancestral backgrounds.

Accurate Machine Learning Model to Diagnose Chronic Autoimmune Diseases Utilizing Information From B Cells and Monocytes

Heterogeneity and limited comprehension of chronic autoimmune disease pathophysiology cause accurate diagnosis a challenging process. With the increasing resources of single-cell sequencing data, a reasonable way could be found to address this issue. In our study, with the use of large-scale public single-cell RNA sequencing (scRNA-seq) data, analysis of dataset integration (3.1 × 10⁵ PBMCs from fifteen SLE patients and eight healthy donors) and cellular cross talking (3.8 × 10⁵ PBMCs from twenty-eight SLE patients and eight healthy donors) were performed to identify the most crucial information characterizing SLE. Our findings revealed that the interactions among the PBMC subpopulations of SLE patients may be weakened under the inflammatory microenvironment, which could result in abnormal emergences or variations in signaling patterns within PBMCs. In particular, the alterations of B cells and monocytes may be the most significant findings. Utilizing this powerful information, an efficient mathematical model of unbiased random forest machine learning was established to distinguish SLE patients from healthy donors via not only scRNA-seq data but also bulk RNA-seq data. Surprisingly, our mathematical model could also accurately identify patients with rheumatoid arthritis and multiple sclerosis, not just SLE, via bulk RNA-seq data (derived from 688 samples). Since the variations in PBMCs should predate the clinical manifestations of these diseases, our machine learning model may be feasible to develop into an efficient tool for accurate diagnosis of chronic autoimmune diseases.

Stronger Microstructural Damage Revealed in Multiple Sclerosis Lesions With Central Vein Sign by Quantitative Gradient Echo MRI

Background

Multiple sclerosis (MS) lesions typically form around a central vein that can be visualized with FLAIR* MRI, creating the central vein sign (CVS) which may reflect lesion pathophysiology. Herein we used gradient echo plural contrast imaging (GEPCI) MRI to simultaneously visualize CVS and measure tissue damage in MS lesions. We examined CVS in relation to tissue integrity in white matter (WM) lesions and among MS subtypes.

Objective

We aimed to determine if CVS positive lesions were specific to MS subtype, if CVS can be detected consistently among readers using the GEPCI method, and if there were differences in tissue damage in lesions with vs without CVS.

Subjects and Methods

Thirty relapsing-remitting MS (RRMS) subjects and 38 primary and secondary progressive MS (PMS) subjects were scanned with GEPCI protocol at 3T. GEPCI T2*-SWI images were generated to visualize CVS. Two investigators independently evaluated WM lesions for CVS and measured lesion volumes. To estimate tissue damage severity, total lesion volume, and mean lesion volume, R2t*-based tissue damage score (TDS) of individual lesions and tissue damage load (TDL) were measured for CVS+, CVS-, and confluent lesions. Spearman correlations were made between MRI and clinical data. One-way ANCOVA with age and sex as covariates was used to compare measurements of CVS+ vs CVS- lesions in each individual.

Results

398 of 548 lesions meeting inclusion criteria showed CVS. Most patients had ≥40% CVS+ lesions. CVS+ lesions were present in similar proportion among MS subtypes. Interobserver agreement was high for CVS detection. CVS+ and confluent lesions had higher average and total volumes vs CVS- lesions. CVS+ and confluent lesions had more tissue damage than CVS- lesions based on TDL and mean TDS.

Conclusion

CVS occurred in RRMS and PMS in similar proportions. CVS+ lesions had greater tissue damage and larger size than CVS- lesions.

Kappa Free Light Chains, Soluble Interleukin-2 Receptor, and Interleukin-6 Help Explore Patients Presenting With Brain White Matter Hyperintensities

Introduction

Many patients are referred to multiple sclerosis (MS) tertiary centers to manage brain white matter hyperintensities (WMH). Multiple diagnoses can match in such situations, and we lack proper tools to diagnose complex cases.

Objective

This study aimed to prospectively analyze and correlate with the final diagnosis, cerebrospinal fluid (CSF) interleukin (IL)-1β, soluble IL-2 receptor (CD25), IL-6, IL-10, and kappa free light chains (KFLC) concentrations in patients presenting with brain WMH.

Methods

All patients over 18 years addressed to our MS tertiary center for the diagnostic workup of brain WMH were included from June 1, 2020, to June 1, 2021. Patients were separated into three groups-MS and related disorder (MSARD), other inflammatory neurological disorder (OIND), and non-inflammatory neurological disorder (NIND) groups-according to clinical presentation, MRI characteristics, and biological workup.

Results

A total of 176 patients (129 women, mean age 45.8 ± 14.7 years) were included. The diagnosis was MSARD (n = 88), OIND (n = 35), and NIND (n = 53). Median CSF KFLC index and KFLC intrathecal fraction (IF) were higher in MSARD than in the OIND and NIND groups; p < 0.001 for all comparisons. CSF CD25 and IL-6 concentrations were higher in the OIND group than in both the MSARD and NIND groups; p < 0.001 for all comparisons. KFLC index could rule in MSARD when compared to NIND (sensitivity, 0.76; specificity, 0.91) or OIND (sensitivity, 0.73; specificity, 0.76). These results were similar to those with oligoclonal bands (sensitivity, 0.59; specificity, 0.98 compared to NIND; sensitivity, 0.59; specificity, 0.88 compared to OIND). In contrast, elevated CSF CD25 and IL-6 could rule out MSARD when compared to OIND (sensitivity, 0.58 and 0.88; specificity, 0.95 and 0.74, respectively).

Discussion

Our results show that, as OCBs, KFLC biomarkers are helpful tools to rule in MSARD, whereas elevated CSF CD25 and IL-6 rule out MSARD. Interestingly, CSF IL-6 concentration could help identify neuromyelitis optica spectrum disorder, myelin oligodendrocyte glycoprotein antibody-associated disease, and central nervous system (CNS) vasculitis. These results need to be confirmed within more extensive and multicentric studies. Still, they sustain that KFLC, CSF CD25, and CSF IL-6 could be reliable biomarkers in brain WMH diagnostic workup for differentiating MSARD from other brain inflammatory MS mimickers.

Diagnostic Error in Neuro-ophthalmology: Avenues to Improve

Purpose of Review

To highlight potential avenues to reduce preventable diagnostic error of neuro-ophthalmic conditions and avoid patient harm.

Recent Findings

Recent prospective studies and studies of patient harm have advanced our understanding. Additionally, recent studies of fundus photography, telemedicine, and artificial intelligence highlight potential avenues for diagnostic improvement.

Summary

Diagnostic error of neuro-ophthalmic conditions can often be traced to failure to gather an adequate history, perform a complete physical exam, obtain adequate/appropriate neuroimaging, and generate a complete, appropriate differential diagnosis. Improving triage and identification of neuro-ophthalmic conditions by other providers and increasing access to subspecialty neuro-ophthalmology evaluation are essential avenues to reduce diagnostic error. Further research should evaluate the relationship between misdiagnosis and patient harm, and help identify the most impactful potential targets for improvement.

The Neuroimmunology of Multiple Sclerosis: Fictions and Facts

There have been tremendous advances in the neuroimmunology of multiple sclerosis over the past five decades, which have led to improved diagnosis and therapy in the clinic. However, further advances must take into account an understanding of some of the complex issues in the field, particularly an appreciation of "facts" and "fiction." Not surprisingly given the incredible complexity of both the nervous and immune systems, our understanding of the basic biology of the disease is very incomplete. This lack of understanding has led to many controversies in the field. This review identifies some of these controversies and facts/fictions with relation to the basic neuroimmunology of the disease (cells and molecules), and important clinical issues. Fortunately, the field is in a healthy transition from excessive reliance on animal models to a broader understanding of the disease in humans, which will likely lead to many improved treatments especially of the neurodegeneration in multiple sclerosis (MS).

Determination of CSF GFAP, CCN5, and vWF Levels Enhances the Diagnostic Accuracy of Clinically Defined MS From Non-MS Patients With CSF Oligoclonal Bands

Background

Inclusion of cerebrospinal fluid (CSF) oligoclonal IgG bands (OCGB) in the revised McDonald criteria increases the sensitivity of diagnosis when dissemination in time (DIT) cannot be proven. While OCGB negative patients are unlikely to develop clinically definite (CD) MS, OCGB positivity may lead to an erroneous diagnosis in conditions that present similarly, such as neuromyelitis optica spectrum disorders (NMOSD) or neurosarcoidosis.

Objective

To identify specific, OCGB-complementary, biomarkers to improve diagnostic accuracy in OCGB positive patients.

Methods

We analysed the CSF metabolome and proteome of CDMS (n=41) and confirmed non-MS patients (n=64) comprising a range of CNS conditions routinely encountered in neurology clinics.

Results

OCGB discriminated between CDMS and non-MS with high sensitivity (85%), but low specificity (67%), as previously described. Machine learning methods revealed CCN5 levels provide greater accuracy, sensitivity, and specificity than OCGB (79%, +5%; 90%, +5%; and 72%, +5% respectively) while glial fibrillary acidic protein (GFAP) identified CDMS with 100% specificity (+33%). A multiomics approach improved accuracy further to 90% (+16%).

Conclusion

The measurement of a few additional CSF biomarkers could be used to complement OCGB and improve the specificity of MS diagnosis when clinical and radiological evidence of DIT is absent.

The central vein sign helps in differentiating multiple sclerosis from its mimickers: lessons from Fabry disease

OBJECTIVES

Although the use of specific MRI criteria has significantly increased the diagnostic accuracy of multiple sclerosis (MS), reaching a correct neuroradiological diagnosis remains a challenging task, and therefore the search for new imaging biomarkers is crucial. This study aims to evaluate the incidence of one of the emerging neuroradiological signs highly suggestive of MS, the central vein sign (CVS), using data from Fabry disease (FD) patients as an index of microvascular disorder that could mimic MS.

METHODS

In this retrospective study, after the application of inclusion and exclusion criteria, MRI scans of 36 FD patients and 73 relapsing-remitting (RR) MS patients were evaluated. Among the RRMS participants, 32 subjects with a disease duration inferior to 5 years (early MS) were also analyzed. For all subjects, a Fazekas score (FS) was recorded, excluding patients with FS = 0. Different neuroradiological signs, including CVS, were evaluated on FLAIR T2-weighted and spoiled gradient recalled echo sequences.

RESULTS

Among all the recorded neuroradiological signs, the most striking difference was found for the CVS, with a detectable prevalence of 78.1% (57/73) in RRMS and of 71.4% (25/32) in early MS patients, while this sign was absent in FD (0/36).

CONCLUSIONS

Our results confirm the high incidence of CVS in MS, also in the early phases of the disease, while it seems to be absent in conditions with a different etiology. These results corroborate the possible role of CVS as a useful neuroradiological sign highly suggestive of MS.

KEY POINTS

• The search for new imaging biomarkers is crucial to achieve a correct neuroradiological diagnosis of MS. • The CVS shows an incidence superior to 70% in MS patients, even in the early phases of the disease, while it appears to be absent in FD. • These findings further corroborate the possible future central role of CVS in distinguishing between MS and its mimickers.

C1q inhibits differentiation of oligodendrocyte progenitor cells via Wnt/β-catenin signaling activation in a cuprizone-induced mouse model of multiple sclerosis

Multiple sclerosis (MS) is a chronic central nervous system demyelinating disease of autoimmune originate. Complement C1q, a complex glycoprotein, mediates a variety of immunoregulatory functions considered important in the prevention of autoimmunity. Although we found that the increased serum C1q level was highly associated with the Fazekas scores and T2 lesion volume of MS patients, the effect and mechanism of C1q on demyelination remains unclear. Cluster analysis and protein array results showed that serum Wnt receptors Frizzled-6 and LRP-6 levels in MS patients were both increased, we proposed that C1q may be involved in demyelination via Wnt signaling. The increased C1q protein levels in the serum and brain tissue were confirmed in a cuprizone (CPZ)-induced demyelination mice model. Moreover, CPZ treatment induced significant increase of LRP-6 and Frizzled-6 protein in mice corpus callosum. LRP-6 extra-cellular domain (LRP-6-ECD) level in the serum and cerebrospinal fluid (CSF) of CPZ mice also significantly increased. Knockdown of the subunit C1s of C1 not only substantially attenuated demyelination, promoted M2 microglia polarization and improved neurological function, but inhibited β-catenin expression and its nuclear translocation in oligodendrocyte progenitor cells (OPCs). In vitro, C1s silence reversed the increased level of LRP-6-ECD in the medium and β-catenin expression in OPCs induced by C1q treatment. Meanwhile, inhibition of C1s also markedly lowered the number of EDU positive OPCs, but enhanced the number of CNPase positive oligodendrocyte and the protein of MBP. The present study indicated that C1q was involved in demyelination in response to CPZ in mice by preventing OPC from differentiating into mature oligodendrocyte via Wnt/β-catenin signaling activation.

Brainstem syndrome at onset is related to an early MS diagnosis in Peru: A national referral center cohort

Background

MS is unpredictable regarding clinical symptoms; however, certain symptoms represent the preferred localization of white matter lesions such as brainstem, spinal cord; or optic nerve.

Objectives

To investigate the epidemiological, clinical, and imaging characteristics of MS patients in a national referral center in Peru, and to evaluate whether the type of symptom at onset relates with the time to making an MS diagnosis.

Methods

Retrospective study of MS patients at the Instituto Nacional de Ciencias Neurológicas between January 2010 and December 2018. Four different syndromes were selected for analysis as symptom onset (optic neuritis, brainstem syndrome, myelitis, and others).

Results

we identified 268 patients for whom a diagnosis of MS had been given; after excluding misdiagnosed patients (33 Neuromyelitis optica), lost or incomplete records, 121 patients were included. The majority of patients (46.6%) were born in Lima. Female to male ratio was 1.37 to 1, mean age at diagnosis was 31 years. At onset, myelitis was present in 35% of RRMS patients, followed by brainstem syndrome (25%) and optic neuritis (18%). Brainstem syndrome was statistically significant predictor for earlier diagnosis (adjusted HR: 2.09; p = 0.015).

Conclusion

Brainstem syndrome as an initial presentation of MS in Peru is related to an earlier diagnosis.

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In Peru, the epidemiology of MS is still a major neglected topic.

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Brainstem syndrome as an initial presentation of MS in Peru is related to an early diagnosis.

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Our population represents different regions of our country.

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Similar clinical, epidemiological and imaging characteristic to other Latin American countries were found.

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We found a misdiagnosis rate of 36.2%, which remains a contemporary problem in MS diagnosis.

New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis

ABSTRACT

There is growing interest in imaging multiple sclerosis (MS) through the ultra-high-field (UHF) lens, which currently means a static magnetic field strength of 7 T or higher. Because of higher signal-to-noise ratio and enhanced susceptibility effects, UHF magnetic resonance imaging improves conspicuity of MS pathological hallmarks, among them cortical demyelination and the central vein sign. This could, in turn, improve confidence in MS diagnosis and might also facilitate therapeutic monitoring of MS patients. Furthermore, UHF imaging offers unique insight into iron-related pathology, leptomeningeal inflammation, and spinal cord pathologies in neuroinflammation. Yet, limitations such as the longer scanning times to achieve improved resolution and incipient safety data on implanted medical devices need to be considered. In this review, we discuss applications of UHF imaging in MS, its advantages and limitations, and practical aspects of UHF in the clinical setting.

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

BACKGROUND AND OBJECTIVES

To compare the performance of the 2017 revisions to the McDonald criteria with the 2010 McDonald criteria in establishing MS diagnosis and predicting prognosis in patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS).

METHODS

CSF examination, brain and spinal cord MRI obtained ≤5 months from CIS onset, and a follow-up brain MRI acquired within 15 months from CIS onset were evaluated in 785 CIS patients from 9 European centers. Date of second clinical attack and of reaching Expanded Disability Status Score (EDSS) ≥ 3.0, if they occurred, were also collected. Performance of the 2017 and 2010 McDonald criteria for dissemination in space (DIS), time (DIT) (including oligoclonal bands assessment) and DIS + DIT for predicting a second clinical attack (clinically definite [CD] MS) and EDSS ≥ 3.0 at follow-up was evaluated. Time to MS diagnosis for the different criteria was also estimated.

RESULTS

At follow-up (median = 69.1 months), 406/785 CIS patients developed CDMS. At 36 months, the 2017 DIS + DIT criteria had higher sensitivity (0.83 vs 0.66), lower specificity (0.39 vs 0.60) and similar area under the curve values (0.61 vs 0.63). Median time to MS diagnosis was shorter with the 2017 vs the 2010 or CDMS criteria (2017 revision = 3.2; 2010 revision = 13.0; CDMS = 58.5 months). The 2 sets of criteria similarly predicted EDSS ≥ 3.0 milestone. Three periventricular lesions improved specificity in patients ≥45 years.

DISCUSSION

The 2017 McDonald criteria showed higher sensitivity, lower specificity and similar accuracy in predicting CDMS compared to 2010 McDonald criteria, while shortening time to diagnosis of MS.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the 2017 McDonald Criteria more accurately distinguish CDMS in patients early after a CIS when compared to the 2010 McDonald criteria.

Optical Coherence Tomography in the Differential Diagnosis of Patients with Multiple Sclerosis and Patients with MRI Nonspecific White Matter Lesions

In the differential diagnosis of nonspecific white matter lesions (NSWMLs) detected on magnetic resonance imaging (MRI), multiple sclerosis (MS) should be taken into consideration. Optical coherence tomography (OCT) is a promising tool applied in the differential diagnostic process of MS. We tested whether OCT may be useful in distinguishing between MS and NSWMLs patients. In patients with MS (n = 41) and NSWMLs (n = 19), the following OCT parameters were measured: thickness of the peripapillary Retinal Nerve Fibre Layer (pRNFL) in superior, inferior, nasal, and temporal segments; thickness of the ganglion cell-inner plexiform layer (GCIPL); thickness of macular RNFL (mRNFL); and macular volume (MV). In MS patients, GCIPL was significantly lower than in NSWMLs patients (p = 0.024). Additionally, in MS patients, mRNFL was significantly lower than in NSWMLs patients (p = 0.030). The average segmental pRNFL and MV did not differ between MS and NSWMLs patients (p > 0.05). GCIPL and macular RNFL thinning significantly influenced the risk of MS (18.6% [95% CI 2.7%, 25.3%]; 27.4% [95% CI 4.5%, 62.3%]), and reduced GCIPL thickness appeared to be the best predictor of MS. We conclude that OCT may be helpful in the differential diagnosis of MS and NSWMLs patients in real-world settings.

Multiple sclerosis diagnosis: Knowledge gaps and opportunities for educational intervention in neurologists in the United States

Background:

Few studies have addressed the results of educational efforts concerning proper use of McDonald criteria (MC) revisions outside multiple sclerosis (MS) subspecialty centers. Neurology residents and MS subspecialist neurologists demonstrated knowledge gaps for core elements of the MC in a recent prior study.

Objective:

To assess comprehension and application of MC core elements by non-MS specialist neurologists in the United States who routinely diagnose MS.

Methods:

Through a cross-sectional study design, a previously developed survey instrument was distributed online.

Results:

A total of 222 neurologists completed the study survey. Syndromes atypical for MS were frequently incorrectly considered “typical” MS presentations. Fourteen percent correctly identified definitions of both “periventricular” and “juxtacortical” lesions and 2% correctly applied these terms to 9/9 images. Twenty-four percent correctly identified all four central nervous system (CNS) regions for satisfaction of magnetic resonance imaging (MRI) dissemination in space. In two presented cases, 61% and 71% correctly identified dissemination in time (DIT) was not fulfilled, and 85% and 86% subsequently accepted nonspecific historical symptoms without objective evidence for DIT fulfillment.

Conclusion:

The high rate of knowledge deficiencies and application errors of core elements of the MC demonstrated by participants in this study raise pressing questions concerning adequacy of dissemination and educational efforts upon publication of revisions to MC.

Central vein sign: A diagnostic biomarker in multiple sclerosis (CAVS-MS) study protocol for a prospective multicenter trial

The specificity and implementation of current MRI-based diagnostic criteria for multiple sclerosis (MS) are imperfect. Approximately 1 in 5 of individuals diagnosed with MS are eventually determined not to have the disease, with overreliance on MRI findings a major cause of MS misdiagnosis. The central vein sign (CVS), a proposed MRI biomarker for MS lesions, has been extensively studied in numerous cross sectional studies and may increase diagnostic specificity for MS. CVS has desirable analytical, measurement, and scalability properties. "Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS)" is an NIH-supported, 2-year, prospective, international, multicenter study conducted by the North American Imaging in MS Cooperative (NAIMS) to evaluate CVS as a diagnostic biomarker for immediate translation into clinical care. Study objectives include determining the concordance of CVS and McDonald Criteria to diagnose MS, the sensitivity of CVS to detect MS in those with typical presentations, and the specificity of CVS among those with atypical presentations. The study will recruit a total of 400 participants (200 with typical and 200 with atypical presentations) across 11 sites. T2*-weighted, high-isotropic-resolution, segmented echo-planar MRI will be acquired at baseline and 24 months on 3-tesla scanners, and FLAIR* images (combination of FLAIR and T2*) will be generated for evaluating CVS. Data will be processed on a cloud-based platform that contains clinical and CVS rating modules. Imaging quality control will be conducted by automated methods and neuroradiologist review. CVS will be determined by Select6* and Select3* lesion methods following published criteria at each site and by central readers, including neurologists and neuroradiologists. Automated CVS detection and algorithms for incorporation of CVS into McDonald Criteria will be tested. Diagnosis will be adjudicated by three neurologists who served on the 2017 International Panel on the Diagnosis of MS. The CAVS-MS study aims to definitively establish CVS as a diagnostic biomarker that can be applied broadly to individuals presenting for evaluation of the diagnosis of MS.

Multi-parametric MRI phenotype with trustworthy machine learning for differentiating CNS demyelinating diseases

Background

Misdiagnosis of multiple sclerosis (MS) and neuromyelitis optica (NMO) may delay the treatment, resulting in poor prognosis. However, the precise identification of these two diseases is still challenging in clinical practice. We aimed to evaluate the value of quantitative radiomic features extracted from the brain white matter lesions for differential diagnosis of MS and NMO.

Methods

We recruited 116 CNS demyelinating patients including 78 MS, and 38 NMO. Three neuroradiologists performed visual differential diagnosis based on brain MRI for comparison purpose. A multi-level scheme was designed to harness the selection of discriminative and stable radiomics features extracted from brain while mater lesions in T1-MPRAGE, T2 sequences and clinical factors. Based on the imaging phenotype composed of the selected radiomic and clinical features, Multi-parametric Multivariate Random Forest (MM-RF) model was constructed and verified with both 10-fold cross-validation and independent testing. Result interpretation was provided to build trust in diagnostic decisions.

Results

Eighty-six patients were randomly selected to form the training set while the rest 30 patients for independent testing. On the training set, our MM-RF model achieved accuracy 0.849 and AUC 0.826 in 10-fold cross-validation, which were significantly higher than clinical visual analysis (0.709 and 0.683, p < 0.05). In the independent testing, the MM-RF model achieved AUC 0.902, accuracy 0.871, sensitivity 0.873, specificity 0.869, respectively. Furthermore, age, sex and EDSS were found mildly correlated with the radiomic features (p of all < 0.05).

Conclusions

Multi-parametric radiomic features have potential as practical quantitative imaging biomarkers for differentiating MS from NMO.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03015-w.

Insights into multiple sclerosis-associated uveitis: a scoping review

PURPOSE

This paper is a scoping review of research on multiple sclerosis (MS)-associated uveitis to determine its epidemiology, pathophysiology, clinical features and treatment.

METHODS

A comprehensive search of the medical databases MEDLINE (PubMed), EMBASE, Web of Science and Cochrane was carried out on 25 November 2019, to identify papers published between 1980 and 2019 that focus on patients with MS-associated uveitis.

RESULTS

Based on large cohort studies (n ≥ 1000), the prevalence of uveitis in patients with MS is estimated to be 0.53-1.34% (mean = 0.83%), and MS is diagnosed in 0.52-3.20% (mean = 1.30%) of patients with uveitis. The condition is most frequent among middle-aged women. Patients usually complain of floaters and/or blurred vision, with bilateral intermediate uveitis (with retinal vasculitis) as the most frequent ophthalmological finding. Both MS and intermediate uveitis are associated with HLA-DRB1*15:01 and IL-2RA gene polymorphism rs2104286 A > G, suggesting a common genetic background. T cells, and possibly B cells, play an important role in both autoimmune disorders. Multiple sclerosis (MS)-related uveitis is classically treated as non-infectious uveitis, with corticosteroids as the first treatment step. Other treatments include immunosuppressants, cryotherapy, laser photocoagulation and vitrectomy. These treatment options have a limited, if any, effect on the course of MS and can be complicated by side-effects. As treatment strategies for MS have increased in the last decade, it would be interesting to evaluate the efficacy of these new treatments during the course of uveitis. Moreover, the correlation between retinal periphlebitis and MS could be established more accurately with the recently developed techniques of wide-field fluorescein angiography in a large cohort of MS patients.

CONCLUSION

MS-associated uveitis is a rare, highly discussed pathology about which much is still unknown. Large epidemiological studies and extrapolation of new MS treatments to this condition are warranted.

Th17-Related Cytokines as Potential Discriminatory Markers between Neuromyelitis Optica (Devic's Disease) and Multiple Sclerosis-A Review

Multiple sclerosis (MS) and Devic’s disease (NMO; neuromyelitis optica) are autoimmune, inflammatory diseases of the central nervous system (CNS), the etiology of which remains unclear. It is a serious limitation in the treatment of these diseases. The resemblance of the clinical pictures of these two conditions generates a partial possibility of introducing similar treatment, but on the other hand, a high risk of misdiagnosis. Therefore, a better understanding and comparative characterization of the immunopathogenic mechanisms of each of these diseases are essential to improve their discriminatory diagnosis and more effective treatment. In this review, special attention is given to Th17 cells and Th17-related cytokines in the context of their potential usefulness as discriminatory markers for MS and NMO. The discussed results emphasize the role of Th17 immune response in both MS and NMO pathogenesis, which, however, cannot be considered without taking into account the broader perspective of immune response mechanisms.

Beyond McDonald: updated perspectives on MRI diagnosis of multiple sclerosis

INTRODUCTION

Magnetic resonance imaging (MRI) is an essential paraclinical test to establish an accurate and early diagnosis of multiple sclerosis (MS), which is based on the application of the McDonald criteria.

AREAS COVERED

The objective of this article is to analyze, based on publicly available database since the publication of the 2017 McDonald diagnostic criteria, the clinical impact of these criteria, to discuss the potential inclusion within these criteria of the optic nerve to demonstrate dissemination in space, and to guide the acquisition and interpretation of MRI scans for diagnostic purposes. Finally, the authors will review emerging MRI features that could improve the specificity of MRI in the diagnosis of MS and consequently minimize the misdiagnosis of this disease.

EXPERT OPINION

Although the optic nerve has not been included as one of the topographies required to demonstrate demyelinating lesion disseminated in space in the 2017 McDonald criteria, new studies seem to show some improvement in the sensitivity of these criteria when this topography is considered. New radiological findings such as the central vein sign and iron rims, should be considered within the typical MRI features of this disease with the objective of minimizing MRI-based diagnostic errors.

Proteomics of Multiple Sclerosis: Inherent Issues in Defining the Pathoetiology and Identifying (Early) Biomarkers

Multiple Sclerosis (MS) is a demyelinating disease of the human central nervous system having an unconfirmed pathoetiology. Although animal models are used to mimic the pathology and clinical symptoms, no single model successfully replicates the full complexity of MS from its initial clinical identification through disease progression. Most importantly, a lack of preclinical biomarkers is hampering the earliest possible diagnosis and treatment. Notably, the development of rationally targeted therapeutics enabling pre-emptive treatment to halt the disease is also delayed without such biomarkers. Using literature mining and bioinformatic analyses, this review assessed the available proteomic studies of MS patients and animal models to discern (1) whether the models effectively mimic MS; and (2) whether reasonable biomarker candidates have been identified. The implication and necessity of assessing proteoforms and the critical importance of this to identifying rational biomarkers are discussed. Moreover, the challenges of using different proteomic analytical approaches and biological samples are also addressed.

Beta-thalassemia intermedia with ischemic transients misdiagnosed as multiple sclerosis: A case report

The article's abstract is not available.  

A variant of uncertain significance in SDHAF1, the succinate dehydrogenase chaperone protein, in an adult patient with spastic paraparesis and leukoencephalopathy

Succinate dehydrogenase (SDH), or respiratory complex II, consists of four nuclear-encoded subunits. The chaperone protein succinate dehydrogenase assembly factor 1 (SDHAF1) plays an essential role in the assembly of SDH, and in the incorporation of iron-sulfur clusters into the SDHB subunit. SDHB couples the oxidation of succinate to fumarate with the reduction of ubiquinone (coenzyme Q) to ubiquinol. Previously reported mutations in SDHAF1 have been associated with infantile leukoencephalopathy. We report an adult case with a homozygous variant of uncertain significance (VUS) mutation in SDHAF1, presenting with dementia, spastic paraparesis, and cardiomyopathy, initially diagnosed as multiple sclerosis.

Multiple Sclerosis

Many groundbreaking advances have occurred in the field of multiple sclerosis since this series last reviewed the disorder in 2014. The U.S. Food and Drug Administration has approved 7 new medications for relapsing-remitting multiple sclerosis and approved the first medication for primary progressive multiple sclerosis. The McDonald criteria for diagnosing multiple sclerosis were updated in 2017. New blood tests can now differentiate patients with multiple sclerosis from those with neuromyelitis optica spectrum disorder, and 3 new medications have been approved specifically for the latter disorder. Also, new medications for treating the symptoms of multiple sclerosis have been introduced.

Diagnostic approach in multiple sclerosis with MRI: an update

Although neurological examination and medical history are the first and most important steps towards the diagnosis of multiple sclerosis (MS), MRI has taken a prominent role in the diagnostic workflow especially since the implementation of McDonald criteria. However, before applying those on MR imaging features, other diseases must be excluded and MS should be favoured as the most likely diagnosis. For the prognosis the earliest possible and correct diagnosis of MS is crucial, since increasingly effective disease modifying therapies are available for the different forms of clinical manifestation and progression. This review deals with the significance of MRI in the diagnostic workup of MS with special regard to daily clinical practice. The recommended MRI protocols for baseline and follow-up examinations are summarized and typical MS lesion patterns ("green flags") in four defined CNS compartments are introduced. Pivotal is the recognition of neurological aspects as well as imaging findings atypical for MS ("red flags"). In addition, routinely assessment of Aquaporin-4-IgG antibodies specific for neuromyelitis optica spectrum disorders (NMOSD) as well as the knowledge of associated lesion patterns on MRI is recommended. Mistaken identity of such lesions with MS and consecutive implementation of disease modifying therapies for MS can worsen the course of NMOSD.

Central vein sign and iron rim in multiple sclerosis: ready for clinical use?

PURPOSE OF REVIEW

To summarize recent evidence from the application of susceptibility-based MRI sequences to investigate the 'central vein sign' (CVS) and 'iron rim' as biomarkers to improve the diagnostic work-up of multiple sclerosis (MS) and predict disease severity.

RECENT FINDINGS

The CVS is a specific biomarker for MS being detectable from the earliest phase of the disease. A threshold of 40% of lesions with the CVS can be optimal to distinguish MS from non-MS patients. Iron rim lesions, reflecting chronic active lesions, develop in relapsing-remitting MS patients and persist in progressive MS. They increase in size in the first few years after their formation and then stabilize. Iron rim lesions can distinguish MS from non-MS patients but not the different MS phenotypes. The presence of at least four iron rim lesions is associated with an earlier clinical disability, higher prevalence of clinically progressive MS and more severe brain atrophy. Automated methods for CVS and iron rim lesion detection are under development to facilitate their quantification.

SUMMARY

The assessment of the CVS and iron rim lesions is feasible in the clinical scenario and provides MRI measures specific to MS pathological substrates, improving diagnosis and prognosis of these patients.

Adaptive changes in muscle activity after cryotherapy treatment: Potential mechanism for improvement the functional state in patients with multiple sclerosis

BACKGROUND

The available literature lacks data about the influence of whole body cryotherapy (WBC) on muscle activity in patients with sclerosis multiplex (MS).

OBJECTIVE

Assessment of the influence of the 20 WBC series on the surface electromyography (sEMG) signal and the relationship between it and the functional state in patients with MS.

METHODS

The study group was 114 of MS patients (aged 45.24±11.88yr.,) which 74 of them received 20 of WBC. An assessment was made of: the hand grip (HGS), Timed 25-Foot Walk, Fatigue Severity Scale, sEMG signal from the dominant limb.

RESULTS

After a series of 20 WBC: in the rest electromyograms, an increase of extensor carpi radialis (ECR) and a decrease of flexor carpi radialis (FCR) amplitude were demonstrated (non-normalized signal ECR p = 0.0001); significant differences in sEMG rest signals between ECR and FCR have decreased; for voluntary contraction in both assessed antagonistic muscle amplitude was significantly decreased (p = 0.0005; p = 0.0316, p = 0.0185); an increase of HGS (p < 0.001); gait improvement (p = 0.001); decrease fatigue (p = 0.024). No significant changes were observed in the control group.

CONCLUSIONS

Series of 20 WBC improves the functional state and reduces fatigue in patients with MS, which may be due to adaptive changes in bioelectrical muscle activity.

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics

OBJECTIVES

The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and compare model performance with that of 2 expert neuroradiologists.

MATERIALS AND METHODS

A total of 268 T2-weighted and T1-weighted brain magnetic resonance imagin scans were retrospectively collected from patients with migraine (n = 56), multiple sclerosis (n = 70), neuromyelitis optica spectrum disorders (n = 91), and central nervous system vasculitis (n = 51). The neural network architecture, trained on 178 scans, was based on a cascade of 4 three-dimensional convolutional layers, followed by a fully dense layer after feature extraction. The ability of the final algorithm to correctly classify the diseases in an independent test set of 90 scans was compared with that of the neuroradiologists.

RESULTS

The interrater agreement was 84.9% (Cohen κ = 0.78, P < 0.001). In the test set, deep learning and expert raters reached the highest diagnostic accuracy in multiple sclerosis (98.8% vs 72.8%, P < 0.001, for rater 1; and 81.8%, P < 0.001, for rater 2) and the lowest in neuromyelitis optica spectrum disorders (88.6% vs 4.4%, P < 0.001, for both raters), whereas they achieved intermediate values for migraine (92.2% vs 53%, P = 0.03, for rater 1; and 64.8%, P = 0.01, for rater 2) and vasculitis (92.1% vs 54.6%, P = 0.3, for rater 1; and 45.5%, P = 0.2, for rater 2). The overall performance of the automated method exceeded that of expert raters, with the worst misdiagnosis when discriminating between neuromyelitis optica spectrum disorders and vasculitis or migraine.

CONCLUSIONS

A neural network performed better than expert raters in terms of accuracy in classifying white matter disorders from magnetic resonance imaging and may help in their diagnostic work-up.

Compensatory image of the stability of people with multiple sclerosis and atrial vertigo based on posturography examination

Pathophysiology of balance disorders due to multiple sclerosis (MS) and atrial vertigo (AV) is different. We evaluated posture stability when maintaining balance in people with MS presenting symptoms of ataxia and those with AV. We included 45 women (15 with MS; 15 with AV; 15 controls). A posturography platform was used to measure balance parameters. To characterize the image of stability and the compensation of balance disorders, the surface area of the stabilogram (SAS), vision control index (VCI) and the vision-motion control index (VMCI) were used. The stability image of people with MS and AV with eyes open (p = 0.002), with eyes closed (p = 0.080) and with visual biofeedback (p = 0.0008) differed significantly. SAS depended on visual biofeedback regardless of the occurrence of balance disorders and was the basis for determining the compensatory share of vision-motor coordination. Differences in VCI between groups were insignificant. VMCI was significantly higher in people with balance disorders than in those without, but similar in the MS and AV groups. The image of stability is different in people with MS and AV. Thanks to visual biofeedback, it becomes possible to launch effective vision-motor coordination when compensating balance disorders. VCI may become the measure of compensation for balance disorders.

Diagnostic Error of Neuro-ophthalmologic Conditions: State of the Science

BACKGROUND

Diagnostic error is prevalent and costly, occurring in up to 15% of US medical encounters and affecting up to 5% of the US population. One-third of malpractice payments are related to diagnostic error. A complex and specialized diagnostic process makes neuro-ophthalmologic conditions particularly vulnerable to diagnostic error.

EVIDENCE ACQUISITION

English-language literature on diagnostic errors in neuro-ophthalmology and neurology was identified through electronic search of PubMed and Google Scholar and hand search.

RESULTS

Studies investigating diagnostic error of neuro-ophthalmologic conditions have revealed misdiagnosis rates as high as 60%-70% before evaluation by a neuro-ophthalmology specialist, resulting in unnecessary tests and treatments. Correct performance and interpretation of the physical examination, appropriate ordering and interpretation of neuroimaging tests, and generation of a differential diagnosis were identified as pitfalls in the diagnostic process. Most studies did not directly assess patient harms or financial costs of diagnostic error.

CONCLUSIONS

As an emerging field, diagnostic error in neuro-ophthalmology offers rich opportunities for further research and improvement of quality of care.

The frequency and characteristics of MS misdiagnosis in patients referred to the multiple sclerosis centre of Catalonia

Background:

Multiple sclerosis (MS) misdiagnosis may cause physical and emotional damage to patients.

Objectives:

The objective of this study is to determine the frequency and characteristics of MS misdiagnosis in patients referred to the Multiple Sclerosis Centre of Catalonia.

Methods:

We designed a prospective study including all new consecutive patients referred to our centre between July 2017 and June 2018. Instances of misdiagnosis were identified, and referral diagnosis and final diagnosis were compared after 1 year of follow-up. Association of misdiagnosis with magnetic resonance imaging (MRI) findings, presence of comorbidities and family history of autoimmunity were assessed.

Results:

A total of 354 patients were referred to our centre within the study period, 112 (31.8%) with ‘established MS’. Misdiagnosis was identified in eight out of 112 cases (7.1%). MRI identified multifocal white matter lesions, deemed non-specific or not suggestive of MS in all misdiagnosed cases. Patients with MS misdiagnosis had more comorbidities in general than patients with MS ( p = 0.026) as well as a personal history of autoimmunity ( p < 0.001).

Conclusion:

A low frequency of MS misdiagnosis was found in our clinical setting. Multifocal non-specific white matter lesions in referral MRI examinations and the presence of comorbidities, including a personal history of autoimmunity, seem to be contributing factors to misdiagnosis.

Evaluation of the Central Vein Sign as a Diagnostic Imaging Biomarker in Multiple Sclerosis

Importance

The central vein sign has been proposed as a specific imaging biomarker for distinguishing between multiple sclerosis (MS) and not MS, mainly based on findings from ultrahigh-field magnetic resonance imaging (MRI) studies. The diagnostic value of the central vein sign in a multicenter setting with a variety of clinical 3 tesla (T) MRI protocols, however, remains unknown.

Objective

To evaluate the sensitivity and specificity of various central vein sign lesion criteria for differentiating MS from non-MS conditions using 3T brain MRI with various commonly used pulse sequences.

Design, Setting, and Participants

This large multicenter, cross-sectional study enrolled participants (n = 648) of ongoing observational studies and patients included in neuroimaging research databases of 8 neuroimaging centers in Europe. Patient enrollment and MRI data collection were performed between January 1, 2010, and November 30, 2016. Data analysis was conducted between January 1, 2016, and April 30, 2018. Investigators were blinded to participant diagnosis by a novel blinding procedure.

Main Outcomes and Measures

Occurrence of central vein sign was detected on 3T T2*-weighted or susceptibility-weighted imaging. Sensitivity and specificity were assessed for these MRI sequences and for different central vein sign lesion criteria, which were defined by the proportion of lesions with central vein sign or by absolute numbers of lesions with central vein sign.

Results

A total of 606 participants were included in the study after exclusion of 42 participants. Among the 606 participants, 413 (68.2%) were women. Patients with clinically isolated syndrome and relapsing-remitting MS (RRMS) included 235 women (66.6%) and had a median (range) age of 37 (14.7-61.4) years, a median (range) disease duration of 2 (0-33) years, and a median (range) Expanded Disability Status Scale score of 1.5 (0-6.5). Patients without MS included 178 women (70.4%) and had a median (range) age of 54 (18-83) years. A total of 4447 lesions were analyzed in a total of 487 patients: 690 lesions in 98 participants with clinically isolated syndrome, 2815 lesions in 225 participants with RRMS, 54 lesions in 13 participants with neuromyelitis optica spectrum disorder, 54 lesions in 14 participants with systemic lupus erythematosus, 121 lesions in 29 participants with migraine or cluster headache, 240 lesions in 20 participants with diabetes, and 473 lesions in 88 participants with other types of small-vessel disease. The sensitivity was 68.1% and specificity was 82.9% for distinguishing MS from not MS using a 35% central vein sign proportion threshold. The 3 central vein sign lesion criteria had a sensitivity of 61.9% and specificity of 89.0%. Sensitivity was higher when an optimized T2*-weighted sequence was used.

Conclusions and Relevance

In this study, use of the central vein sign at 3T MRI yielded a high specificity and a moderate sensitivity in differentiating MS from not MS; international, multicenter studies may be needed to ascertain whether the central vein sign-based criteria can accurately detect MS.

Utility of shape evolution and displacement in the classification of chronic multiple sclerosis lesions

The accurate recognition of multiple sclerosis (MS) lesions is challenged by the high sensitivity and imperfect specificity of MRI. To examine whether longitudinal changes in volume, surface area, 3-dimensional (3D) displacement (i.e. change in lesion position), and 3D deformation (i.e. change in lesion shape) could inform on the origin of supratentorial brain lesions, we prospectively enrolled 23 patients with MS and 11 patients with small vessel disease (SVD) and performed standardized 3-T 3D brain MRI studies. Bayesian linear mixed effects regression models were constructed to evaluate associations between changes in lesion morphology and disease state. A total of 248 MS and 157 SVD lesions were studied. Individual MS lesions demonstrated significant decreases in volume < 3.75mm³ (p = 0.04), greater shifts in 3D displacement by 23.4% with increasing duration between MRI time points (p = 0.007), and greater transitions to a more non-spherical shape (p < 0.0001). If 62.2% of lesions within a given MRI study had a calculated theoretical radius > 2.49 based on deviation from a perfect 3D sphere, a 92.7% in-sample and 91.2% out-of-sample accuracy was identified for the diagnosis of MS. Longitudinal 3D shape evolution and displacement characteristics may improve lesion classification, adding to MRI techniques aimed at improving lesion specificity.

Retinal thinning and brain atrophy in early MS and CIS

BACKGROUND

Optical coherence tomography (OCT) could be complementary to magnetic resonance imaging (MRI) of the brain in monitoring course of multiple sclerosis (MS) and clinically isolated syndrome (CIS). Thinning of neurons in ganglion cell-inner plexiform layer (GCIPL) measured by OCT is assumed to be associated with brain atrophy.

OBJECTIVES

To evaluate association of GCIPL with brain parameters detected by quantitative MRI (qMRI) and MR-spectroscopy (MRS) in early MS and CIS.

METHODS

Seventeen newly diagnosed MS and 18 CIS patients were prospectively included. The patients were assessed at baseline as well as at 1 year follow-up by OCT, qMRI and MRS. Brain parenchymal and myelin volumes (BPV, MYV respectively) and the corresponding fractions (BPF, MYF) were measured with qMRI. Metabolites including myo-inositol (myo-Ins) were measured in the normal-appearing white matter (NAWM) using MRS. T-tests and ANOVA were used to analyze group differences, and linear regression models to evaluate association of GCIPL with BPV, MYV and myo-Ins after correlation analysis.

RESULTS

Disease activity reflected by lesions on MRI and presence of CSF oligoclonal IgG bands were more prominent in MS compared to CIS. GCIPL, BPV, MYV, BPF and MYF were reduced, while concentration of myo-Ins was increased in MS compared to CIS. Follow-up showed consistency of thinner GCIPL in MS compared to CIS. GCIPL thinning correlated with reduced BPV and MYV (P < .05 for both), but with increased myo-Ins (P < .01).

CONCLUSIONS

Significant GCIPL thinning occurs in early MS and is associated with enhanced brain inflammation and atrophy.

Inferring Multiple Sclerosis Stages from the Blood Transcriptome via Machine Learning

Peripheral blood mononuclear cells (PBMCs) bear specific dysregulations in genes and pathways at distinct stages of multiple sclerosis (MS) that may help with classifying MS and non-MS subjects, specifying the early stage of disease, or discriminating among MS courses. Here we describe an unbiased machine learning workflow to build MS stage-specific classifiers based on PBMC transcriptomics profiles from more than 300 individuals, including healthy subjects and patients with clinically isolated syndromes, relapsing-remitting MS, primary or secondary progressive MS, or other neurological disorders. The pipeline, designed to optimize and compare the performance of distinct machine learning algorithms in the training cohort, generates predictive models not influenced by demographic features, such as age and gender, and displays high accuracy in the independent validation cohort. Proper application of machine learning to transcriptional profiles of circulating blood cells may allow identification of disease state and stage in MS.

Generated PBMC transcriptomes from multiple sclerosis and control subjects

Unbiased machine learning workflow allows algorithm comparison and optimization

Classifiers built on training cohort have high accuracy in the independent test set

PBMC transcriptomes identify disease state and stage in multiple sclerosis

Conversion of clinically isolated syndrome to multiple sclerosis: a prospective study

BACKGROUND

Multiple sclerosis (MS) begins with an acute clinical attack (clinically isolated syndrome) in approximately 85% of patients. The conversion rate from clinically isolated syndrome to multiple sclerosis has been documented at 30% to 82% in previous studies. When an individual presents for evaluation after a single episode of inflammation of the CNS, several decisions regarding follow-up in subsequent years need to be made, including that of whether or not to start a therapy. There is, therefore, an emerging need to identify the predictive factors that anticipate conversion from CIS to MS.

METHODS

This paper presents a single-center prospective longitudinal study aimed at identification of the most powerful independent predictors for conversion from CIS to MS, utilizing the 2010 McDonald MS criteria and focusing on selected demographic, clinical, radiographical (magnetic resonance imaging - MRI), cerebrospinal fluid (predominantly oligoclonal bands - OCB) and electrophysiological parameters (multimodal sensory and motor-evoked potentials - EP). Two independent outcomes meeting MS criteria are evaluated: development of second clinical relapse (clinically definite multiple sclerosis) and progression in magnetic resonance imaging (based on new MRI T2 brain and/or spinal cord lesions). CIS patients were followed clinically and MRI was repeated at one and two years within the course of a follow-up period of at least 24 months (median 27, range 24-36 months).

RESULTS

Of the 64 CIS patients enrolled who completed at least a 2-year follow-up period (42 women and 22 men, median age 36.5, range 22-66 years), 45 (70.3%) (29 women and 16 men, median age 38; range 22-66 years) fulfilled the 2010 McDonald criteria for MS by dissemination in space (DIS) and time (DIT) over the follow-up period. Twenty-nine CIS patients converted to MS through a clinically symptomatic attack, and 16 CIS patients developed new T2 lesions on MRI, while 19 patients without progression remained stable as CIS. Confirmed among potential predictors for the conversion of CIS patients to MS were increased (>10) baseline MRI T2-hyperintense lesions (odds ratio (OR) 3.107, p = 0.046), OCB positivity (OR 5.958, p = 0.003) and subclinical EP abnormality (OR 14.400, p = 0.003). Multivariate statistical models (logistic regression and Cox proportional hazards regression models) confirmed these parameters as independent predictors of high sensitivity (84%) and acceptable specificity (63%).

CONCLUSION

In addition to accepted predictors for the conversion of CIS to MS (i.e. baseline MRI T2 lesion load and OCB positivity), already implemented in current diagnostic criteria for MS, this study demonstrates, in addition, the high predictive value of subclinical multimodal evoked potential abnormalities.

Visualizing the Central Nervous System: Imaging Tools for Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) are autoimmune central nervous system conditions with increasing incidence and prevalence. While MS is the most frequent inflammatory CNS disorder in young adults, NMOSD is a rare disease, that is pathogenetically distinct from MS, and accounts for approximately 1% of demyelinating disorders, with the relative proportion within the demyelinating CNS diseases varying widely among different races and regions. Most immunomodulatory drugs used in MS are inefficacious or even harmful in NMOSD, emphasizing the need for a timely and accurate diagnosis and distinction from MS. Despite distinct immunopathology and differences in disease course and severity there might be considerable overlap in clinical and imaging findings, posing a diagnostic challenge for managing neurologists. Differential diagnosis is facilitated by positive serology for AQP4-antibodies (AQP4-ab) in NMOSD, but might be difficult in seronegative cases. Imaging of the brain, optic nerve, retina and spinal cord is of paramount importance when managing patients with autoimmune CNS conditions. Once a diagnosis has been established, imaging techniques are often deployed at regular intervals over the disease course as surrogate measures for disease activity and progression and to surveil treatment effects. While the application of some imaging modalities for monitoring of disease course was established decades ago in MS, the situation is unclear in NMOSD where work on longitudinal imaging findings and their association with clinical disability is scant. Moreover, as long-term disability is mostly attack-related in NMOSD and does not stem from insidious progression as in MS, regular follow-up imaging might not be useful in the absence of clinical events. However, with accumulating evidence for covert tissue alteration in NMOSD and with the advent of approved immunotherapies the role of imaging in the management of NMOSD may be reconsidered. By contrast, MS management still faces the challenge of implementing imaging techniques that are capable of monitoring progressive tissue loss in clinical trials and cohort studies into treatment algorithms for individual patients. This article reviews the current status of imaging research in MS and NMOSD with an emphasis on emerging modalities that have the potential to be implemented in clinical practice.

Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines

MRI has improved the diagnostic work-up of multiple sclerosis, but inappropriate image interpretation and application of MRI diagnostic criteria contribute to misdiagnosis. Some diseases, now recognized as conditions distinct from multiple sclerosis, may satisfy the MRI criteria for multiple sclerosis (e.g. neuromyelitis optica spectrum disorders, Susac syndrome), thus making the diagnosis of multiple sclerosis more challenging, especially if biomarker testing (such as serum anti-AQP4 antibodies) is not informative. Improvements in MRI technology contribute and promise to better define the typical features of multiple sclerosis lesions (e.g. juxtacortical and periventricular location, cortical involvement). Greater understanding of some key aspects of multiple sclerosis pathobiology has allowed the identification of characteristics more specific to multiple sclerosis (e.g. central vein sign, subpial demyelination and lesional rims), which are not included in the current multiple sclerosis diagnostic criteria. In this review, we provide the clinicians and researchers with a practical guide to enhance the proper recognition of multiple sclerosis lesions, including a thorough definition and illustration of typical MRI features, as well as a discussion of red flags suggestive of alternative diagnoses. We also discuss the possible place of emerging qualitative features of lesions which may become important in the near future.

Challenges in multiple sclerosis diagnosis: Misunderstanding and misapplication of the McDonald criteria

Objective:

To assess comprehension and application of the McDonald criteria.

Background:

Studies suggest that knowledge gaps for specific core elements of the McDonald criteria may contribute to multiple sclerosis (MS) misdiagnosis.

Methods:

Neurology residents (NR) and multiple sclerosis specialists (MSS) in North America completed a web-based survey.

Results:

A total of 160 participants were included: 72 NR and 88 MSS. Syndromes incorrectly identified as typical of MS included: complete transverse myelopathy (35% NR and 15% MSS), intractable vomiting/nausea/hiccoughs (20% NR and 5% MSS), and bilateral optic neuritis/unilateral optic neuritis with poor visual recovery (17% NR and 10% MSS). Periventricular magnetic resonance imaging (MRI) lesions were correctly identified by 39% NR and 52% MSS, and juxtacortical lesions were correctly identified by 28% NR and 53% MSS. The correct definition of “periventricular” was chosen by 38% NR and 61% MSS, and that of “juxtacortical” was chosen by 19% NR and 54% MSS. Regions incorrectly identified for MRI dissemination in space fulfillment included the optic nerve (31% NR and 26% MSS) and the subcortical white matter (11% NR and 18% MSS). The majority of participants assessed previous non-specific neurological symptoms without objective evidence of a central nervous system (CNS) lesion as sufficient for clinical dissemination in time.

Conclusion:

The McDonald criteria are often misunderstood and misapplied. Concerted educational efforts may prevent MS misdiagnosis.

Application of the 2017 McDonald criteria in a Chinese population with clinically isolated syndrome

Background:

Diagnostic criteria for multiple sclerosis have evolved over time, with the most recent being the 2017 McDonald criteria. Evidence is lacking regarding the validity of the 2017 McDonald criteria among the Asian population. Therefore, this study aims to evaluate the diagnostic performance of the 2017 McDonald criteria in Chinese patients with clinically isolated syndrome (CIS).

Methods:

A total of 93 patients with initial findings suggestive of CIS in a tertiary hospital in China from 2012 to 2017 were included in this retrospective study. Baseline and follow-up data were reviewed. Diagnostic performance (sensitivity, specificity, accuracy), was assessed and survival analysis was performed for the 2017 and 2010 McDonald criteria respectively.

Results:

Among the 93 Chinese patients with CIS, 57 were female (61.3%) and the median (interquartile range) age of onset was 37 (31.3–41.8) years. The 2017 McDonald criteria displayed a higher sensitivity (75.0% versus 14.6%, p < 0.0001), lower specificity (47.1% versus 100.0%, p < 0.05) but an overall higher accuracy (67.7% versus 36.9%, p < 0.0001) when compared with the 2010 iteration. The novel criteria allow for a better detection of MS at baseline (40.8% versus 9.9%, p < 0.0001).

Conclusion:

The 2017 McDonald criteria had a higher sensitivity but lower specificity than the 2010 iteration. Overall it facilitated an earlier and more accurate diagnosis of multiple sclerosis in Chinese patients with CIS.

Diagnosis, Differential Diagnosis, and Misdiagnosis of Multiple Sclerosis

PURPOSE OF REVIEW

The diagnosis of multiple sclerosis (MS) is often challenging. This article discusses approaches to the clinical assessment for MS that may improve diagnostic accuracy.

RECENT FINDINGS

Contemporary diagnostic criteria for MS continue to evolve, while knowledge about diseases that form the differential diagnosis of MS continues to expand. Recent data concerning causes of MS misdiagnosis (the incorrect assignment of a diagnosis of MS) have further informed approaches to syndromes that may mimic MS and the accurate diagnosis of MS.

SUMMARY

This article provides a practical update on MS diagnosis through a discussion of recently revised MS diagnostic criteria, a renewed consideration of MS differential diagnosis, and contemporary data concerning MS misdiagnosis.

The "Central Vein Sign" on T2*-weighted Images as a Diagnostic Tool in Multiple Sclerosis: A Systematic Review and Meta-analysis using Individual Patient Data

We aimed to evaluate the pooled incidence of central vein sign on T2*-weighted images from patients with multiple sclerosis (MS), and to determine the diagnostic performance of this central vein sign for differentiating MS from other white matter lesions and provide an optimal cut-off value. A computerized systematic search of the literature in PUBMED and EMBASE was conducted up to December 14, 2018. Original articles investigating central vein sign on T2*-weighted images of patients with MS were selected. The pooled incidence was obtained using random-effects model. The pooled sensitivity and specificity were obtained using a bivariate random-effects model. An optimal cut-off value for the proportion of lesions with a central vein sign was calculated from those studies providing individual patient data. Twenty-one eligible articles covering 501 patients with MS were included. The pooled incidence of central vein sign at the level of individual lesion in patients with MS was 74% (95% CI, 65-82%). The pooled sensitivity and pooled specificity for the diagnostic performance of the central vein sign were 98% (95% CI, 92-100%) and 97% (95% CI, 91-99%), respectively. The area under the HSROC curve was 1.00 (95% CI, 0.99-1.00). The optimal cut-off value for the proportion of lesions with a central vein sign was found to be 45%. Although various T2*-weighted images have been used across studies, the current evidence supports the use of the central vein sign on T2*-weighted images to differentiate MS from other white matter lesions.

Population-based Incidence of Pediatric and Adult Optic Neuritis and the Risk of Multiple Sclerosis

PURPOSE

To determine the age- and sex-specific prevalence and incidence of demyelinating optic neuritis and the risk of multiple sclerosis (MS) in pediatric and adult populations in South Korea.

DESIGN

A nationwide, population-based, retrospective study using data from the Korean National Health Claims database from 2010 to 2016.

PARTICIPANTS

The entire South Korean population aged 65 years of age or younger (n = 44 700 564). All patients with optic neuritis from the entire Korean population were included.

METHODS

Patients aged 14 years of age or younger were classified as pediatric patients, and those aged 15 to 65 years were classified as adults. Each group was analyzed separately. Patients with optic neuritis had a subsequent diagnosis, including idiopathic, MS, neuromyelitis optica (NMO), and acute disseminated encephalomyelitis. Prevalence and incidence, conversion rate to MS, and treatment modalities (steroids, plasmapheresis, interferon-β, and immunosuppressants) were estimated.

MAIN OUTCOME MEASURES

Prevalence and incidence of optic neuritis, and conversion rate to MS.

RESULTS

Among 44 700 564 individuals, 531 pediatric patients (50.7% female) and 7183 adults (53.3% female) were identified as having optic neuritis. Annual incidence was 1.04 (95% confidence interval [CI], 1.01-1.07) per 100 000 pediatric individuals and 3.29 (95% CI, 3.28-3.30) per 100 000 adults. Peak incidence was observed at 10 to 14 years in the pediatric population and at 30 to 34 years and 50 to 54 years in the adult population. Conversion rate to MS was 13.8% in the pediatric population and 11.4% in the adult population. Fourteen percent of all patients were treated with chronic immunosuppressants, 38% of patients with NMO underwent plasmapheresis, and 50% of patients with MS were treated with interferon-β.

CONCLUSIONS

This is a nationwide epidemiologic study of optic neuritis in individuals of all ages in South Korea. The incidence of optic neuritis and subsequent risk of MS in the pediatric population are comparable to those reported in western countries but are lower in the adult population than in western countries. The incidence rate in adults was 3.2-fold higher than in the pediatric population, and the overall MS conversion rate in the entire Korean population was estimated to be 10.6%.

The "central vein sign" in patients with diagnostic "red flags" for multiple sclerosis: A prospective multicenter 3T study

BACKGROUND

The central vein sign (CVS) has been shown to help in the differential diagnosis of multiple sclerosis (MS), but most prior studies are retrospective.

OBJECTIVES

To prospectively assess the diagnostic predictive value of the CVS in diagnostically difficult cases.

METHODS

In this prospective multicenter study, 51 patients with suspected MS who had clinical, imaging, or laboratory "red flags" (i.e. features atypical for MS) underwent 3T fluid-attenuated inversion recovery (FLAIR*) magnetic resonance imaging (MRI) for CVS assessment. After the diagnostic work-up, expert clinicians blinded to the results of the CVS assessment came to a clinical diagnosis. The value of the CVS to prospectively predict an MS diagnosis was assessed.

RESULTS

Of the 39 patients who received a clinical diagnosis by the end of the study, 27 had MS and 12 received a non-MS diagnosis that included systemic lupus erythematosus, sarcoidosis, migraine, Sjögren disease, SPG4-spastic-paraparesis, neuromyelitis optica, and Susac syndrome. The percentage of perivenular lesions was higher in MS (median = 86%) compared to non-MS (median = 21%; p < 0.0001) patients. A 40% perivenular lesion cutoff was associated with 97% accuracy and a 96% positive/100% negative predictive value.

CONCLUSION

The CVS detected on 3T FLAIR* images can accurately predict an MS diagnosis in patients suspected to have MS, but with atypical clinical, laboratory, and imaging features.

Validation of multiple sclerosis diagnoses in the Swedish National Patient Register

Population-based registers are widely used in epidemiological studies. We aimed to estimate the validity of multiple sclerosis (MS) diagnoses registered in the Swedish National Patient Register (NPR) by two sequential register-based case-definition algorithms. Prevalent MS patients aged 16–64 years were identified from the in- and specialised out-patient NPR in 2001–2013, using International Classification of Diseases code G35. These identified MS diagnoses were validated through two sequential register-based case-definition algorithms, as the ‘gold-standard’ reference, by linking individual-level data longitudinally to other nationwide registers. The primary algorithm first sought to corroborate the MS diagnoses with MS-specific information in other nationwide registers. The exploratory secondary algorithm identified individuals with MS-related information in other registers and those who were unable to be followed sufficiently. Through multi-register linkage, we estimated the number of confirmed and uncertain individuals with an MS diagnosis recorded in the NPR. A total of 19,781 individuals (mean age at first visit 45.2 years; 69.5% women) had at least one MS diagnosis recorded in the NPR during 2001–2013. Using the two case-definition algorithms, 92.5% (n = 18,291) of the MS diagnoses recorded in the NPR were confirmed, while 7.5% (n = 1490) remained uncertain. Our findings indicate that a very high percentage of patients coded with an MS diagnosis in the Swedish NPR actually have MS, and supports the use of the NPR as a viable source to identify individuals with an MS diagnosis for population-based research. This exploratory methods paper suggests an alternative novel method to verify individuals’ diagnoses in register-based settings.