The tension between early diagnosis and misdiagnosis of multiple sclerosis

Misdiagnosis of Multiple Sclerosis: Past, Present, and Future

PURPOSE OF REVIEW

Misdiagnosis of multiple sclerosis (MS) is a prevalent worldwide problem. This review discusses how MS misdiagnosis has evolved over time and focuses on contemporary challenges and potential strategies for its prevention.

RECENT FINDINGS

Recent studies report cohorts with a range of misdiagnosis between 5 and 18%. Common disorders are frequently misdiagnosed as MS. Overreliance on MRI findings and misapplication of MS diagnostic criteria are often associated with misdiagnosis. Emerging imaging biomarkers, including the central vein sign and paramagnetic rim lesions, may aid diagnostic accuracy when evaluating patients for suspected MS. MS misdiagnosis can have harmful consequences for patients and healthcare systems. Further research is needed to better understand its causes. Concerted and novel educational efforts to ensure accurate and widespread implementation of MS diagnostic criteria remain an unmet need. The incorporation of diagnostic biomarkers highly specific for MS in the future may prevent misdiagnosis.

Erdheim-Chester disease: misdiagnosed as multiple sclerosis

Erdheim-Chester disease is a rare histiocytic neoplasm with a wide range of clinical manifestations. Due to its rarity and protean characteristics, this condition often presents a diagnostic challenge. A Caucasian woman in her late 60s presented with unsteadiness, dysphagia and dysarthria. She was initially diagnosed with secondary progressive multiple sclerosis but deteriorated over 2 years with a potential lack of therapeutic response. Subsequent investigations resulted in the diagnosis of Erdheim-Chester disease. She received targeted therapy with BRAF and MAPK-pathway inhibitors. Her initial response to treatment has been positive with functional gains and reduced disease burden on MR brain imaging, and with no significant adverse effects.

A Blood Test for the Diagnosis of Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune chronic disease characterized by inflammation and demyelination of the central nervous system (CNS). Despite numerous studies conducted, valid biomarkers enabling a definitive diagnosis of MS are not yet available. The aim of our study was to identify a marker from a blood sample to ease the diagnosis of MS. In this study, since there is evidence connecting the serotonin pathway to MS, we used an ELISA (Enzyme-Linked Immunosorbent Assay) to detect serum MS-specific auto-antibodies (auto-Ab) against the extracellular loop 1 (ECL-1) of the 5-hydroxytryptamine (5-HT) receptor subtype 2A (5-HT2A). We utilized an ELISA format employing poly-D-lysine as a pre-coating agent. The binding of 208 serum samples from controls, both healthy and pathological, and of 104 serum samples from relapsing-remitting MS (RRMS) patients was tested. We observed that the serum-binding activity in control cohort sera, including those with autoimmune and neurological diseases, was ten times lower compared to the RRMS patient cohort (p = 1.2 × 10-47), with a sensitivity and a specificity of 98% and 100%, respectively. These results show that in the serum of patients with MS there are auto-Ab against the serotonin receptor type 2A which can be successfully used in the diagnosis of MS due to their high sensitivity and specificity.

Real-world challenges in the diagnosis of primary progressive multiple sclerosis

BACKGROUND AND PURPOSE

Despite the 2017 revisions to the McDonald criteria, diagnosing primary progressive multiple sclerosis (PPMS) remains challenging. To improve clinical practice, the aim was to identify frequent diagnostic challenges in a real-world setting and associate these with the performance of the 2010 and 2017 PPMS diagnostic McDonald criteria.

METHODS

Clinical, radiological and laboratory characteristics at the time of diagnosis were retrospectively recorded from designated PPMS patient files. Possible complicating factors were recorded such as confounding comorbidity, signs indicative of alternative diagnoses, possible earlier relapses and/or incomplete diagnostic work-up (no cerebrospinal fluid examination and/or magnetic resonance imaging brain and spinal cord). The percentages of patients fulfilling the 2010 and 2017 McDonald criteria were calculated after censoring patients with these complicating factors.

RESULTS

A total of 322 designated PPMS patients were included. Of all participants, it was found that n = 28/322 had confounding comorbidity and/or signs indicative of alternative diagnoses, n = 103/294 had possible initial relapsing and/or uncertainly progressive phenotypes and n = 73/191 received an incomplete diagnostic work-up. When applying the 2010 and 2017 diagnostic PPMS McDonald criteria on n = 118 cases with a full diagnostic work-up and a primary progressive disease course without a better alternative explanation, these were met by 104/118 (88.1%) and 98/118 remaining patients (83.1%), respectively (p = 0.15).

CONCLUSION

Accurate interpretation of the initial clinical course, consideration of alternative diagnoses and a full diagnostic work-up are the cornerstones of a PPMS diagnosis. When these conditions are met, the 2010 and 2017 McDonald criteria for PPMS perform similarly, emphasizing the importance of their appropriate application in clinical practice.

Clinical and radiologic characteristics associated with multiple sclerosis misdiagnosis at a tertiary referral center in the United States

BACKGROUND

Misdiagnosis of multiple sclerosis (MS) is common and can have harmful effects on patients and healthcare systems. Identification of factors associated with misdiagnosis may aid development of prevention strategies.

OBJECTIVE

To identify clinical and radiological predictors of MS misdiagnosis.

METHODS

We retrospectively reviewed medical records of all patients who were referred to Johns Hopkins MS Center from January 2018 to June 2019. Patients who carried a diagnosis of MS were classified as correctly diagnosed or misdiagnosed with MS by the Johns Hopkins clinician. Demographics, clinical, laboratory, and radiologic data were collected. Differences between the two groups were evaluated, and a regression model was constructed to identify predictors of misdiagnosis.

RESULTS

Out of 338 patients who were previously diagnosed with MS, 41 (12%) had been misdiagnosed. An alternative diagnosis was confirmed in 28 (68%) of the misdiagnosed patients; cerebrovascular disease was the most common alternate diagnosis. Characteristics associated with misdiagnosis were female sex (odds ratio (OR): 5.81 (95% confidence interval (CI): 1.60, 21.05)) and non-specific brain magnetic resonance imaging (MRI) lesions (OR: 7.66 (3.42, 17.16)).

CONCLUSION

Misdiagnosis is a frequent problem in MS care. Non-specific brain lesions were the most significant predictor of misdiagnosis. Interventions aimed to reduce over-reliance on imaging findings and misapplication of the McDonald criteria may prevent MS misdiagnosis.

Experiences of receiving a diagnosis of multiple sclerosis: a meta-synthesis of qualitative studies

PURPOSE

This meta-synthesis aimed to synthesise qualitative evidence on experiences of people with Multiple Sclerosis (MS) in receiving a diagnosis, to derive a conceptual understanding of adjustment to MS diagnosis.

METHODS

Five electronic databases were systematically searched to identify qualitative studies that explored views and experiences around MS diagnosis. Papers were quality-appraised using a standardised checklist. Data synthesis was guided by principles of meta-ethnography, a well-established interpretive method for synthesising qualitative evidence.

RESULTS

Thirty-seven papers were selected (with 874 people with MS). Synthesis demonstrated that around the point of MS diagnosis people experienced considerable emotional upheaval (e.g., shock, denial, anger, fear) and difficulties (e.g., lengthy diagnosis process) that limited their ability to make sense of their diagnosis, leading to adjustment difficulties. However, support resources (e.g., support from clinicians) and adaptive coping strategies (e.g., acceptance) facilitated the adjustment process. Additionally, several unmet emotional and informational support needs (e.g., need for personalised information and tailored emotional support) were identified that, if addressed, could improve adjustment to diagnosis.

CONCLUSIONS

Our synthesis highlights the need for providing person-centred support and advice at the time of diagnosis and presents a conceptual map of adjustment for designing interventions to improve adjustment following MS diagnosis.Implications for RehabilitationThe period surrounding Multiple Sclerosis diagnosis can be stressful and psychologically demanding.Challenges and disruptions at diagnosis can threaten sense of self, resulting in negative emotions.Adaptive coping skills and support resources could contribute to better adjustment following diagnosis.Support interventions should be tailored to the needs of newly diagnosed people.

Lessons from immunotherapies in multiple sclerosis

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

ATR-FTIR spectroscopy of plasma supported by multivariate analysis discriminates multiple sclerosis disease

Multiple sclerosis (MS) is one of the most common neurodegenerative diseases showing various symptoms both of physical and cognitive type. In this work, we used attenuated total reflection Fourier transformed infrared (ATR-FTIR) spectroscopy to analyze plasma samples for discriminating MS patients from healthy control individuals, and identifying potential spectral biomarkers helping the diagnosis through a quick non-invasive blood test. The cohort of the study consists of 85 subjects, including 45 MS patients and 40 healthy controls. The differences in the spectral features both in the fingerprint region (1800-900 cm^-1) and in the high region (3050-2800 cm^-1) of the infrared spectra were highlighted also with the support of different chemometric methods, to capture the most significant wavenumbers for the differentiation. The results show an increase in the lipid/protein ratio in MS patients, indicating changes in the level (metabolism) of these molecular components in the plasma. Moreover, the multivariate tools provided a promising rate of success in the diagnosis, with 78% sensitivity and 83% specificity obtained through the random forest model in the fingerprint region. The MS diagnostic tools based on biomarkers identification on blood (and blood component, like plasma or serum) are very challenging and the specificity and sensitivity values obtained in this work are very encouraging. Overall, the results obtained suggest that ATR-FTIR spectroscopy on plasma samples, requiring minimal or no manipulation, coupled with statistical multivariate approaches, is a promising analytical tool to support MS diagnosis through the identification of spectral biomarkers.

Berlin Registry of Neuroimmunological entities (BERLimmun): protocol of a prospective observational study

BACKGROUND

Large-scale disease overarching longitudinal data are rare in the field of neuroimmunology. However, such data could aid early disease stratification, understanding disease etiology and ultimately improve treatment decisions. The Berlin Registry of Neuroimmunological Entities (BERLimmun) is a longitudinal prospective observational study, which aims to identify diagnostic, disease activity and prognostic markers and to elucidate the underlying pathobiology of neuroimmunological diseases.

METHODS

BERLimmun is a single-center prospective observational study of planned 650 patients with neuroimmunological disease entity (e.g. but not confined to: multiple sclerosis, isolated syndromes, neuromyelitis optica spectrum disorders) and 85 healthy participants with 15 years of follow-up. The protocol comprises annual in-person visits with multimodal standardized assessments of medical history, rater-based disability staging, patient-report of lifestyle, diet, general health and disease specific symptoms, tests of motor, cognitive and visual functions, structural imaging of the neuroaxis and retina and extensive sampling of biological specimen.

DISCUSSION

The BERLimmun database allows to investigate multiple key aspects of neuroimmunological diseases, such as immunological differences between diagnoses or compared to healthy participants, interrelations between findings of functional impairment and structural change, trajectories of change for different biomarkers over time and, importantly, to study determinants of the long-term disease course. BERLimmun opens an opportunity to a better understanding and distinction of neuroimmunological diseases.

An Update on Diagnostic Laboratory Biomarkers for Multiple Sclerosis

PURPOSE

For many patients, the multiple sclerosis (MS) diagnostic process can be lengthy, costly, and fraught with error. Recent research aims to address the unmet need for an accurate and simple diagnostic process through discovery of novel diagnostic biomarkers. This review summarizes recent studies on MS diagnostic fluid biomarkers, with a focus on blood biomarkers, and includes discussion of technical limitations and practical applicability.

RECENT FINDINGS

This line of research is in its early days. Accurate and easily obtainable biomarkers for MS have not yet been identified and validated, but several approaches to uncover them are underway. Continue efforts to define laboratory diagnostic biomarkers are likely to play an increasingly important role in defining MS at the earliest stages, leading to better long-term clinical outcomes.

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.

Paramagnetic rims are a promising diagnostic imaging biomarker in multiple sclerosis

BACKGROUND

White matter lesions (WMLs) on brain magnetic resonance imaging (MRI) in multiple sclerosis (MS) may contribute to misdiagnosis. In chronic active lesions, peripheral iron-laden macrophages appear as paramagnetic rim lesions (PRLs).

OBJECTIVE

To evaluate the sensitivity and specificity of PRLs in differentiating MS from mimics using clinical 3T MRI scanners.

METHOD

This retrospective international study reviewed MRI scans of patients with MS (n = 254), MS mimics (n = 91) and older healthy controls (n = 217). WMLs, detected using fluid-attenuated inversion recovery MRI, were analysed with phase-sensitive imaging. Sensitivity and specificity were assessed for PRLs.

RESULTS

At least one PRL was found in 22.9% of MS and 26.1% of clinically isolated syndrome (CIS) patients. Only one PRL was found elsewhere. The identification of ⩾1 PRL was the optimal cut-off and had high specificity (99.7%, confidence interval (CI) = 98.20%-99.99%) when distinguishing MS and CIS from mimics and healthy controls, but lower sensitivity (24.0%, CI = 18.9%-36.6%). All patients with a PRL showing a central vein sign (CVS) in the same lesion (n = 54) had MS or CIS, giving a specificity of 100% (CI = 98.8%-100.0%) but equally low sensitivity (21.3%, CI = 16.4%-26.81%).

CONCLUSION

PRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS.

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.

Magnetic Resonance Imaging of Autoimmune Demyelinating Diseases as a Diagnostic Challenge for Radiologists: Report of Two Cases and Literature Review

The magnetic resonance characteristics of autoimmune demyelinating diseases are complex and represent a challenge for the radiologist. In this study we presented two different cases of detected autoimmune demyelinating diseases: one case of acute disseminated encephalomyelitis and one case of neuromyelitis optica, respectively. Expected and unexpected findings of magnetic resonance imaging examination for autoimmune demyelinating diseases were reported in order to provide a valuable approach for diagnosis. In particular, we highlight, review and discuss the presence of several uncommon imaging findings which could lead to a misinterpretation. The integration of magnetic resonance imaging findings with clinical and laboratory data is necessary to provide a valuable diagnosis.

Functional neurological disorder: Extending the diagnosis to other disorders, and proposing an alternate disease term—Attentionally-modifiable disorder

BACKGROUND: The term “functional neurological disorder,” or “FND,” applies to disorders whose occurrence of neurological symptoms fluctuate with the patient’s attention to them. However, many other disorders that are not called “FND” nonetheless can also follow this pattern. Consequently, guidelines are unclear for diagnosing “FND.” OBJECTIVE: To review the neurological conditions that follow this pattern, but which have not so far been termed “FND,” to understand their overlap with conditions that have been termed “FND,” and to discuss the rationale for why FND has not been diagnosed for them. METHOD: A systematic review of the PubMed literature registry using the terms “fluctuation,” “inconsistency,” or “attention” did not yield much in the way of these candidate disorders. Consequently, this review instead relied on the author’s personal library of peer-reviewed studies of disorders that have resembled FND but which were not termed this way, due to his longstanding interest in this problem. Consequently, this approach was not systematic and was subjective regarding disease inclusion. RESULTS: This review identified numerous, diverse conditions that generally involve fluctuating neurological symptoms that can vary with the person’s attention to them, but which have not been called “FND.” The literature was unclear for reasons for not referring to “FND” in these instances. CONCLUSION: Most likely because of historical biases, the use of the term “FND” has been unnecessarily restricted. Because at its core FND is an attentionally-influenced disorder that can respond well to behavioral treatments, the field of neurological rehabilitation could benefit by extending the range of conditions that could be considered as “FND” and referred for similar behavioral treatments. Because the term “FND” has been viewed unfavorably by some patients and clinical practitioners and whose treatment is not implied, the alternative term attentionally-modifiable disorder is proposed.

Posttranslational modifications of proteins are key features in the identification of CSF biomarkers of multiple sclerosis

Background

Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system (CNS) characterized by demyelination and concomitant axonal loss. The lack of a single specific test, and the similarity to other inflammatory diseases of the central nervous system, makes it difficult to have a clear diagnosis of multiple sclerosis. Therefore, laboratory tests that allows a clear and definite diagnosis, as well as to predict the different clinical courses of the disease are of utmost importance. Herein, we compared the cerebrospinal fluid (CSF) proteome of patients with multiple sclerosis (in the relapse–remitting phase of the disease) and other diseases of the CNS (inflammatory and non-inflammatory) aiming at identifying reliable biomarkers of multiple sclerosis.

Methods

CSF samples from the discovery group were resolved by 2D-gel electrophoresis followed by identification of the protein spots by mass spectrometry. The results were analyzed using univariate (Student’s t test) and multivariate (Hierarchical Cluster Analysis, Principal Component Analysis, Linear Discriminant Analysis) statistical and numerical techniques, to identify a set of protein spots that were differentially expressed in CSF samples from patients with multiple sclerosis when compared with other two groups. Validation of the results was performed in samples from a different set of patients using quantitative (e.g., ELISA) and semi-quantitative (e.g., Western Blot) experimental approaches.

Results

Analysis of the 2D-gels showed 13 protein spots that were differentially expressed in the three groups of patients: Alpha-1-antichymotrypsin, Prostaglandin-H2-isomerase, Retinol binding protein 4, Transthyretin (TTR), Apolipoprotein E, Gelsolin, Angiotensinogen, Agrin, Serum albumin, Myosin-15, Apolipoprotein B-100 and EF-hand calcium-binding domain—containing protein. ELISA experiments allowed validating part of the results obtained in the proteomics analysis and showed that some of the alterations in the CSF proteome are also mirrored in serum samples from multiple sclerosis patients. CSF of multiple sclerosis patients was characterized by TTR oligomerization, thus highlighting the importance of analyzing posttranslational modifications of the proteome in the identification of novel biomarkers of the disease.

Conclusions

The model built based on the results obtained upon analysis of the 2D-gels and in the validation phase attained an accuracy of about 80% in distinguishing multiple sclerosis patients and the other two groups.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02404-2.

The frequency and characteristics of multiple sclerosis misdiagnosis in Latin America: A referral center study in Buenos Aires, Argentina

OBJECTIVE

Most contemporary data concerning the frequency and causes of multiple sclerosis (MS) misdiagnosis are from North America and Europe with different healthcare system structure and resources than countries in Latin America. We sought to determine the frequency, and potential contributors to MS misdiagnosis in patients evaluated at an MS referral center in Argentina.

METHODS

The study was a retrospective medical record review. We included patients evaluated at the MS Clinic at Fleni between April 2013 and March 2021. Diagnoses prior to consultation, final diagnoses after consultation, demographic, clinical and paraclinical data, and treatment were extracted and classified.

RESULTS

Seven hundred thirty-six patients were identified. Five hundred seventy-two presented with an established diagnosis of MS and after evaluation, misdiagnosis was identified in 89 (16%). Women were at 83% greater risk of misdiagnosis (p = 0.034). The most frequent alternative diagnoses were cerebrovascular disease, radiological isolated syndrome (RIS), and headache. Seventy-four (83%) of misdiagnosed patients presented with a syndrome atypical for demyelination, 62 (70%) had an atypical brain magnetic resonance imaging (MRI), and 54 (61%) were prescribed disease-modifying therapy.

CONCLUSION

Sixteen percent of patients with established MS were subsequently found to have been misdiagnosed. Women were at higher risk for misdiagnosis. Expert application of the McDonald criteria may prevent misdiagnosis and its associated morbidity and healthcare system cost.

Diagnosis of multiple sclerosis using multifocal ERG data feature fusion

The purpose of this paper is to implement a computer-aided diagnosis (CAD) system for multiple sclerosis (MS) based on analysing the outer retina as assessed by multifocal electroretinograms (mfERGs). MfERG recordings taken with the RETI-port/scan 21 (Roland Consult) device from 15 eyes of patients diagnosed with incipient relapsing-remitting MS and without prior optic neuritis, and from 6 eyes of control subjects, are selected. The mfERG recordings are grouped (whole macular visual field, five rings, and four quadrants). For each group, the correlation with a normative database of adaptively filtered signals, based on empirical model decomposition (EMD) and three features from the continuous wavelet transform (CWT) domain, are obtained. Of the initial 40 features, the 4 most relevant are selected in two stages: a) using a filter method and b) using a wrapper-feature selection method. The Support Vector Machine (SVM) is used as a classifier. With the optimal CAD configuration, a Matthews correlation coefficient value of 0.89 (accuracy = 0.95, specificity = 1.0 and sensitivity = 0.93) is obtained. This study identified an outer retina dysfunction in patients with recent MS by analysing the outer retina responses in the mfERG and employing an SVM as a classifier. In conclusion, a promising new electrophysiological-biomarker method based on feature fusion for MS diagnosis was identified.

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.

Differential diagnosis of multiple sclerosis

BACKGROUND AND OBJECTIVES

Despite immense progress of imaging and updates in the MacDonald criteria, the diagnosis of multiple sclerosis remains difficult as it must integrate history, clinical presentation, biological markers, and imaging. There is a multitude of syndromes resembling multiple sclerosis both clinically or on imaging. The goal of this review is to help clinicians orient themselves in these various diagnoses. We organized our review in two categories: inflammatory and autoimmune diseases that are close or can be confused with multiple sclerosis, and non-inflammatory syndromes that can present with symptoms or imaging mimicking those of multiple sclerosis.

METHOD

Review of literature CONCLUSION: Progress of imaging and biological sciences have drastically changed the approach and management of multiple sclerosis. But these developments have also shined a light on a variety of diseases previously unknown or poorly known, therefore greatly expanding the differential diagnosis of multiple sclerosis. While autoimmune, many of these diseases have underlying biological mechanisms that are very different from those of multiple sclerosis, rendering MS therapies usually inefficient. It is crucial to approach these diseases with utmost thoroughness, integrating history, clinical exam, and evolving ancillary tests.

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.

Consensus Curriculum for Fellowship Training in Multiple Sclerosis and Neuroimmunology

Management of multiple sclerosis and neuroimmunologic disorders has become increasingly complex because of the expanding number of recognized neuroimmune disorders, increased number of therapeutic options, and multidisciplinary care management needs of people with multiple sclerosis and neuroimmunologic disorders. More subspecialists are needed to optimize care of these patients, and many fellowship programs have been created or expanded to increase the subspecialty workforce. Consequently, defining the scope and standardizing fellowship training is essential to ensure that trainees receive high-quality training. A workgroup was created to develop a consensus fellowship curriculum to serve as a resource for all current and future training programs. This curriculum may also serve as a basis for future accreditation efforts.

Pathology-supported genetic testing as a method for disability prevention in multiple sclerosis (MS). Part I. Targeting a metabolic model rather than autoimmunity

In this Review (Part I), we investigate the scientific evidence that multiple sclerosis (MS) is caused by the death of oligodendrocytes, the cells that synthesize myelin, due to a lack of biochemical and nutritional factors involved in mitochondrial energy production in these cells. In MS, damage to the myelin sheaths surrounding nerve axons causes disruption of signal transmission from the brain to peripheral organs, which may lead to disability. However, the extent of disability is not deterred by the use of MS medication, which is based on the autoimmune hypothesis of MS. Rather, disability is associated with the loss of brain volume, which is related to the loss of grey and white matter. A pathology-supported genetic testing (PSGT) method, developed for personalized assessment and treatment to prevent brain volume loss and disability progression in MS is discussed. This involves identification of MS-related pathogenic pathways underpinned by genetic variation and lifestyle risk factors that may converge into biochemical abnormalities associated with adverse expanded disability status scale (EDSS) outcomes and magnetic resonance imaging (MRI) findings during patient follow-up. A Metabolic Model is presented which hypothesizes that disability may be prevented or reversed when oligodendrocytes are protected by nutritional reserve. Evidence for the validity of the Metabolic Model may be evaluated in consecutive test cases following the PSGT method. In Part II of this Review, two cases are presented that describe the PSGT procedures and the clinical outcomes of these individuals diagnosed with MS.

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.

Clinical presentation and diagnosis of multiple sclerosis

The diagnosis of multiple sclerosis (MS) is through clinical assessment and supported by investigations. There is no single accurate and reliable diagnostic test. MS is a disease of young adults with a female predominance. There are characteristic clinical presentations based on the areas of the central nervous system involved, for example optic nerve, brainstem and spinal cord. The main pattern of MS at onset is relapsing-remitting with clinical attacks of neurological dysfunction lasting at least 24 hours. The differential diagnosis includes other inflammatory central nervous system disorders. Magnetic resonance imaging of the brain and lumbar puncture are the key investigations. New diagnostic criteria have been developed to allow an earlier diagnosis and thus access to effective disease modifying treatments.

Update on brain MRI for the diagnosis and follow-up of MS patients

Over the past decades, MRI has become a major tool in the diagnosis and the follow-up of patients with multiple sclerosis (MS), especially for monitoring the effectiveness of therapy. The recent international recommendations issued for the standardization of neurological and radiological clinical practices converge on many points. In this setting, recommendations made by the "Observatoire français de la sclérose en plaques", the French MS registry, can be distinguished by its interdisciplinary complementarity, its longevity, its size, and its positions in direct connection with the clinic. Hence, after suspicions of gadolinium deposition in the brain, with multiple warning from the American and European health authorities, a national consultation took place and resulted in limitation to useful injections. The precautionary principle prevailing, the patient receives a limited quantity of contrast product even if no clinically harmful manifestation has been detected to date. The result of this round table bringing together neurologists and neuroradiologists from specialized centers was published in the form of a recommendation in early 2020. The interest of this project also lies in the constant improvement of the management of patients with MS and the possibility of developing advanced techniques to assist the clinician. The aim of this review is to explain to the neurologist, the interest of following this imaging protocol both in his/her clinical practice and in the possibilities that this opens up.

Cognitive impairment, the central vein sign, and paramagnetic rim lesions in RIS

Objective:

The central vein sign (CVS) and “paramagnetic rim lesions” (PRL) are emerging imaging biomarkers in multiple sclerosis (MS) reflecting perivenular demyelination and chronic, smoldering inflammation. The objective of this study was to assess relationships between cognitive impairment (CI) and the CVS and PRL in radiologically isolated syndrome (RIS).

Methods:

Twenty-seven adults with RIS underwent 3.0 T MRI of the brain and cervical spinal cord (SC) and cognitive assessment using the minimal assessment of cognitive function in MS battery. The CVS and PRL were assessed in white-matter lesions (WMLs) on T2*-weighted segmented echo-planar magnitude and phase images. Multivariable linear regression evaluated relationships between CI and MRI measures.

Results:

Global CI was present in 9 (33%) participants with processing speed and visual memory most frequently affected. Most participants (93%) had ⩾ 40% CVS + WML (a threshold distinguishing MS from other WM disorders); 63% demonstrated PRL. Linear regression revealed that CVS + WML predicted performance on verbal memory(β =-0.024, p = 0.03) while PRL predicted performance on verbal memory (β = -0.040, p = 0.04) and processing speed (β = -0.039, p = 0.03).

Conclusions:

CI is common in RIS and is associated with markers of perivenular demyelination and chronic inflammation in WML, such as CVS + WML and PRL. A prospective follow-up of this cohort will ascertain the importance of CI, CVS, and PRL as risk factors for conversion from RIS to MS.

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.

Functional neurological disorder and multiple sclerosis: a systematic review of misdiagnosis and clinical overlap

Multiple sclerosis (MS) and functional neurological disorder (FND) are both diagnostically challenging conditions which can present with similar symptoms. We systematically reviewed the literature to identify patients with MS who were misdiagnosed with FND, patients with FND who were misdiagnosed with MS, and reports of patients with both conditions. In addition to FND, we included studies of patients with other functional and psychiatric disorders where these caused symptoms leading to investigation for or a diagnosis of MS, which in a different context would likely have been labeled as FND. Our review suggests that MS is one of the most common causes of misdiagnosis of FND and vice versa. We discuss the clinical errors that appear to result in misdiagnoses, such as over-reliance on psychiatric comorbidity when making a diagnosis of FND or over-reliance on neuroimaging for the diagnosis of MS, and practical ways to avoid them. Comorbidity between these two conditions is also likely common, has been poorly studied, and adds complexity to diagnosis and treatment in patients with both MS and FND. Misdiagnosis and comorbidity in a landscape of emerging evidence-based treatments for both MS and FND are issues not only of clinical importance to the care of these patients, but also to treatment trials, especially of MS, where FND could be a hidden confounder.

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.

The Core of Gut Life: Firmicutes Profile in Patients with Relapsing-Remitting Multiple Sclerosis

The multiple sclerosis (MS) incidence rate has been increasing in Russia, but the information about the gut bacteriobiome in the MS-afflicted patients is scarce. Using the Illumina MiSeq sequencing of 16S rRNA gene amplicons, we aimed to analyze the Firmicutes phylum and its taxa in a cohort of Moscow patients with relapsing-remitting MS, assessing the effects of age, BMI, disease modifying therapy (DMT), disability (EDSS), and gender. Among 1252 identified bacterial OTUs, 857 represented Firmicutes. The phylum was the most abundant also in sequence reads, overall averaging 74 ± 13%. The general linear model (GLM) analysis implicated Firmicutes/Clostridia/Clostridiales/Lachospiraceae/Blautia/Blautia wexlerae as increasing with BMI, and only Lachospiraceae/Blautia/Blautia wexlerae as increasing with age. A marked DMT-related decrease in Firmicutes was observed in females at the phylum, class (Clostridia), and order (Clostridiales) levels. The results of our study implicate DMT and gender as factors shaping the fecal Firmicutes assemblages. Together with the gender-dependent differential MS incidence growth rate in the country, the results suggest the likely involvement of gender-specific pathoecological mechanisms underlying the occurrence of the disease, switching between its phenotypes and response to disease-modifying therapies. Overall, the presented profile of Firmicutes can be used as a reference for more detailed research aimed at elucidating the contribution of this core phylum and its lower taxa into the etiology and progression of relapsing-remitting multiple sclerosis.

Prognostication and contemporary management of clinically isolated syndrome

Clinically isolated syndrome (CIS) patients present with a single attack of inflammatory demyelination of the central nervous system. Recent advances in multiple sclerosis (MS) diagnostic criteria have expanded the number of CIS patients eligible for a diagnosis of MS at the onset of the disease, shrinking the prevalence of CIS. MS treatment options are rapidly expanding, which is driving the need to recognise MS at its earliest stages. In CIS patients, finding typical MS white matter lesions on the patient's MRI scan remains the most influential prognostic investigation for predicting subsequent diagnosis with MS. Additional imaging, cerebrospinal fluid and serum testing, information from the clinical history and genetic testing also contribute. For those subsequently diagnosed with MS, there is a wide spectrum of long-term clinical outcomes. Detailed assessment at the point of presentation with CIS provides fewer clues to calculate a personalised risk of long-term severe disability.Clinicians should select suitable CIS cases for steroid treatment to speed neurological recovery. Unfortunately, there are still no neuroprotection or remyelination strategies available. The use of MS disease modifying therapy for CIS varies among clinicians and national guidelines, suggesting a lack of robust evidence to guide practice. Clinicians should focus on confirming MS speedily and accurately with appropriate investigations. Diagnosis with CIS provides an opportune moment to promote a healthy lifestyle, in particular smoking cessation. Patients also need to understand the link between CIS and MS. This review provides clinicians an update on the contemporary evidence guiding prognostication and management of CIS.

The social construction of multiple sclerosis in Israel: a cultural reading of illness narratives

PURPOSE

Illness narratives are cultural artifacts that reflect the ways through which a certain culture perceives and constructs a given illness. Against this backdrop, the study explored the social construction of MS in Israeli society.

MATERIALS AND METHODS

Thematic content analysis of all (70) illness narratives posted on the Israel MS Society's website between 2012-2018, was employed.

RESULTS

Five themes were identified in our analysis, according to chronological order: (1) "Becoming ill" - consisted of framing MS as a sudden affliction or constructing MS as a gradual development. (2) "Negative changes" depicted MS as inflicting negative bodily changes and a disruption to the social order. The "happy ending" of the narratives pertained to (3) "adjustments" to MS and, (4) "never giving up" to MS. These were facilitated by embracing (5) "positive thinking and optimism."

CONCLUSIONS

MS is perceived in Israel as a form of "deviance" and as a biomedical phenomenon. Rehabilitation and healthcare staff, therefore, need to actively engage in interventions that challenge and change the ways that MS is perceived, as well as to partner with people with MS, and disability advocates to reconstruct and design policies and services that reflect a more socio-political understanding of MS.Implications for rehabilitationIllness narratives by people with multiple sclerosis (MS) can teach us about the ways though which a given society perceives and constructs MS.This study analyzed online illness narratives by Israelis with MS; it shows that MS was predominantly constructed as a bio-medical phenomenon and as a form of social deviance.Rehabilitation and healthcare professionals need to actively engage in interventions that challenge and change the ways MS is perceived among the public, policy makers, and people with multiple sclerosis.Rehabilitation and healthcare professionals should collaborate with people with MS and disability advocates in order to reconstruct and shape policies and the planning of communities such that they address the socio-cultural barriers that people with MS face.

The Use of the Central Vein Sign in the Diagnosis of Multiple Sclerosis: A Systematic Review and Meta-analysis

Background: The central vein sign (CVS) is a radiological feature proposed as a multiple sclerosis (MS) imaging biomarker able to accurately differentiate MS from other white matter diseases of the central nervous system. In this work, we evaluated the pooled proportion of the CVS in brain MS lesions and to estimate the diagnostic performance of CVS to perform a diagnosis of MS and propose an optimal cut-off value. Methods: A systematic search was performed on publicly available databases (PUBMED/MEDLINE and Web of Science) up to 24 August 2020. Analysis of the proportion of white matter MS lesions with a central vein was performed using bivariate random-effect models. A meta-regression analysis was performed and the impact of using particular sequences (such as 3D echo-planar imaging) and post-processing techniques (such as FLAIR*) was investigated. Pooled sensibility and specificity were estimated using bivariate models and meta-regression was performed to address heterogeneity. Inclusion and publication bias were assessed using asymmetry tests and a funnel plot. A hierarchical summary receiver operating curve (HSROC) was used to estimate the summary accuracy in diagnostic performance. The Youden index was employed to estimate the optimal cut-off value using individual patient data. Results: The pooled proportion of lesions showing a CVS in the MS population was 73%. The use of the CVS showed a remarkable diagnostic performance in MS cases, providing a pooled specificity of 92% and a sensitivity of 95%. The optimal cut-off value obtained from the individual patient data pooled together was 40% with excellent accuracy calculated by the area under the ROC (0.946). The 3D-EPI sequences showed both a higher pooled proportion compared to other sequences and explained heterogeneity in the meta-regression analysis of diagnostic performances. The 1.5 Tesla (T) scanners showed a lower (58%) proportion of MS lesions with a CVS compared to both 3T (74%) and 7T (82%). Conclusions: The meta-analysis we have performed shows that the use of the CVS in differentiating MS from other mimicking diseases is encouraged; moreover, the use of dedicated sequences such as 3D-EPI and the high MRI field is beneficial.

Detection of Multiple Sclerosis Biomarkers in Serum by Ganglioside Microarrays and Surface Plasmon Resonance Imaging

Multiple sclerosis (MS) is an autoimmune disease that damages the myelin sheaths of nerve cells in the central nervous system. An individual suffering from MS produces increased levels of antibodies that target cell membrane components, such as phospholipids, gangliosides, and membrane proteins. Among them, anti-ganglioside antibodies are considered as important biomarkers to differentiate MS from other diseases that exhibit similar symptoms. We report here a label-free method for detecting a series of antibodies against gangliosides in serum by surface plasmon resonance imaging (SPRi) in combination with a carbohydrate microarray. The ganglioside array was fabricated with a plasmonically tuned, background-free biochip, and coated with a perfluorodecyltrichlorosilane (PFDTS) layer for antigen attachment as a self-assembled pseudo-myelin sheath. The chip was characterized with AFM and matrix-assisted laser desorption ionization mass spectrometry, demonstrating effective functionalization of the surface. SPRi measurements of patients' mimicking blood samples were conducted. A multiplexed detection of antibodies for anti-GT_1b, anti-GM₁, and anti-GA₁ in serum was demonstrated, with a working range of 1 to 100 ng/mL, suggesting that it is well suited for clinical assessment of antibody abnormality in MS patients. Statistical analyses, including PLS-DA and PCA show the array allows comprehensive characterization of cross reactivity patterns between the MS specific antibodies and can generate a wide range of information compared to traditional end point assays. This work uses PFDTS surface functionalization and enables direct MS biomarker detection in serum, offering a powerful alternative for MS assessment and potentially improved patient care.

Integration of the Extreme Gradient Boosting model with electronic health records to enable the early diagnosis of multiple sclerosis

BACKGROUND

Delayed multiple sclerosis (MS) diagnoses are not uncommon, an early diagnostic tool is urgently warranted. We aimed to develop an effective tool through electronic health records and machine learning techniques to early recognize MS patients from hospital visitors in China.

METHODS

Two case sets were collected from January 2016 to December 2018. The training set had 239 MS and 1142 controls, and the test set had 23 MS and 92 controls. The utility of Extreme Gradient Boosting (XGBoost), Random Forest (RF), Naive Bayes, K-nearest-neighbor (KNN) and Support Vector Machine (SVM) in early diagnosis of MS was evaluated by the area under curve of receiver operating characteristic, precision, recall, specificity, accuracy and F1 score.

RESULTS

The XGBoost performed the best and was used to generate the results. Thirty-four variables which were highly relevant to MS diagnosis were set for the XGBoost model, and their relative importance with MS were ranked. The training set recall was 0.632, with a precision of 0.576, and the test set recall was 0.609, with a precision of 0.609. Our study found that 61%, 51%, and 49% of the patients could be diagnosed with MS, 1, 2, and 3 years earlier than their real diagnostic time point, respectively.

CONCLUSIONS

A diagnostic tool for early MS recognition based on the XGBoost model and electronic health records were developed to help reduce diagnostic delays in MS.

Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study

In multiple sclerosis (MS), a subset of chronic active white matter lesions are identifiable on magnetic resonance imaging by their paramagnetic rims, and increasing evidence supports their association with severity of clinical disease. We studied their potential role in differential diagnosis, screening an international multicenter clinical research-based sample of 438 individuals affected by different neurological conditions (MS, other inflammatory, infectious, and non-inflammatory conditions). Paramagnetic rim lesions, rare in other neurological conditions (52% of MS vs 7% of non-MS cases), yielded high specificity (93%) in differentiating MS from non-MS. Future prospective multicenter studies should validate their role as a diagnostic biomarker. ANN NEUROL 2020;88:1034-1042.

IgG Index Revisited: Diagnostic Utility and Prognostic Value in Multiple Sclerosis

Objective: Early and accurate diagnosis of multiple sclerosis (MS) remains a clinical challenge. The main objective is to evaluate the diagnostic and prognostic value of the routinely performed immunoglobulin G (IgG) index for MS patients in the Asian population.

Methods: A retrospective study was conducted among a cohort of clinically isolated syndrome (CIS) patients in China with known oligoclonal band (OCB) status and IgG index at baseline. We first evaluated the predictive value of IgG index for OCB status. Secondly, the diagnostic utility and prognostic value of IgG index alone were tested. Lastly, we incorporated IgG index into the 2017 McDonald criteria by replacing OCB with either “IgG index or OCB” (modified criteria 1), “IgG index and OCB” (modified criteria 2), or “IgG index” (modified criteria 3). The diagnostic utility of different criteria was calculated and compared.

Results: In a CIS cohort in China (n = 105), IgG index > 0.7 forecasted OCB positivity (X² = 22.90, P < 0.001). An elevated IgG index was highly prognostic of more clinical relapses [1-year adjusted odds ratio [OR] = 1.32, P = 0.015; 2-years adjusted OR = 1.69, P = 0.013] and Expanded Disability Status Scale worsening (1-year adjusted OR = 1.76, P = 0.040; 2-years adjusted OR = 1.85, P = 0.032). Under the 2017 McDonald criteria (Positive Likelihood Ratio = 1.54, Negative Likelihood Ratio = 0.56), an IgG index > 0.7 in CIS patients increased the likelihood of developing MS within 2 years, either when OCB status was unknown (Positive Likelihood Ratio = 2.11) or with OCB positivity (Positive Likelihood Ratio = 2.11) at baseline; An IgG index ≤ 0.7, along with a negative OCB, helped rule out the MS diagnosis (Negative Likelihood Ratio = 0.53).

Conclusions: IgG index > 0.7 predicts OCB positivity at the initial attack of MS and is prognostic of early disease activity. IgG index serves as an easily-obtainable and accurate OCB surrogate for MS diagnosis in the Asian population.

Large-scale informatic analysis to algorithmically identify blood biomarkers of neurological damage

The identification of precision blood biomarkers which can accurately indicate damage to brain tissue could yield molecular diagnostics with the potential to improve how we detect and treat neurological pathologies. However, a majority of candidate blood biomarkers for neurological damage that are studied today are proteins which were arbitrarily proposed several decades before the advent of high-throughput omic techniques, and it is unclear whether they represent the best possible targets relative to the remainder of the human proteome. Here, we leveraged mRNA expression data generated from nearly 12,000 human specimens to algorithmically evaluate over 17,000 protein-coding genes in terms of their potential to produce blood biomarkers for neurological damage based on their expression profiles both across the body and within the brain. The circulating levels of proteins associated with the top-ranked genes were then measured in blood sampled from a diverse cohort of patients diagnosed with a variety of acute and chronic neurological disorders, including ischemic stroke, hemorrhagic stroke, traumatic brain injury, Alzheimer's disease, and multiple sclerosis, and evaluated for their diagnostic performance. Our analysis identifies several previously unexplored candidate blood biomarkers of neurological damage with possible clinical utility, many of which whose presence in blood is likely linked to specific cell-level pathologic processes. Furthermore, our findings also suggest that many frequently cited previously proposed blood biomarkers exhibit expression profiles which could limit their diagnostic efficacy.

Impact of communication on first treatment decisions in people with relapsing-remitting multiple sclerosis

OBJECTIVE

Disease-Modifying Treatments (DMTs) have contributed to a new clinical landscape for people with relapsing-remitting multiple sclerosis (pwRRMS). A challenge for services is how to support DMT decisions with changing clinical evidence, and differing treatment goals. This article investigates how pwRRMS weigh up the pros and cons of DMTs by examining how communication at the point of diagnosis is related to DMT decisions.

METHODS

30 semi-structured interviews with pwRRMS in England were conducted using a theoretical purposive sampling strategy and analysed using the thematic approach to answer: How does communication about RRMS during diagnosis influence decisions about when and which DMT to choose?

RESULTS

Three meta-themes were identified: a) communication context; b) delayed communication and hope for people with "non-active" RRMS at diagnosis; c) people with "active" RRMS at diagnosis: Conflated, generic, selective and simplified information CONCLUSION: At the time of diagnosis, patient-physician interactions are characterised by emotions and information complexity. Clinical, social and psychological DMT filtering mechanisms are activated during first decisions. Personalised evidence is needed to make informed decisions.

PRACTICE IMPLICATIONS

Patient decision aids should consider first and consecutive decisions and should not encourage a false sense of large choices that could add to decision anxiety.

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS⁺ ) and 448 CVS-negative (CVS^- ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS⁺ /CVS^- lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.

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.

Erythrocyte microRNAs show biomarker potential and implicate multiple sclerosis susceptibility genes

BACKGROUND

Multiple sclerosis is a demyelinating autoimmune disease, for which there is no blood-borne biomarker. Erythrocytes may provide a source of such biomarkers as they contain microRNAs. MicroRNAs regulate protein translation through complementary binding to messenger RNA. As erythrocytes are transcriptionally inactive, their microRNA profiles may be less susceptible to variation. The aim of this study was to assess the biomarker potential of erythrocyte microRNAs for multiple sclerosis and assess the potential contribution of erythrocyte-derived extracellular vesicle microRNAs to pathology.

METHODS

Erythrocytes were isolated from whole blood by density gradient centrifugation. Erythrocyte microRNAs of a discovery cohort (23 multiple sclerosis patients and 22 healthy controls) were sequenced. Increased expression of miR-183 cluster microRNAs (hsa-miR-96-5p, hsa-miR-182-5p and hsa-miR-183-5p) was validated in an independent cohort of 42 patients and 45 healthy and pathological (migraine) controls. Erythrocyte-derived extracellular vesicles were created ex vivo and their microRNAs were sequenced. Targets of microRNAs were predicted using miRDIP.

RESULTS

Hsa-miR-182-5p and hsa-miR-183-5p were able to discriminate relapsing multiple sclerosis patients from migraine patients and/or healthy controls with 89-94% accuracy and around 90% specificity. Hsa-miR-182-5p and hsa-miR-183-5p expression correlated with measures of physical disability and hsa-miR-96-5p expression correlated with measures of cognitive disability in multiple sclerosis. Erythrocytes were found to selectively package microRNAs into extracellular vesicles and 34 microRNAs were found to be differentially packaged between healthy controls and multiple sclerosis patients. Several gene targets of differentially expressed and packaged erythrocyte microRNAs overlapped with multiple sclerosis susceptibility genes. Gene enrichment analysis indicated involvement in nervous system development and histone H3-K27 demethylation.

CONCLUSIONS

Erythrocyte miR-183 cluster members may be developed into specific multiple sclerosis biomarkers that could assist with diagnosis and disability monitoring. Erythrocyte and their extracellular microRNAs were shown to target multiple sclerosis susceptibility genes and may be contributing to the pathophysiology via previously identified routes.

Primary progressive multiple sclerosis in a Russian cohort: relationship with gut bacterial diversity

Background

Gut microbiota has been increasingly acknowledged to shape significantly human health, contributing to various autoimmune diseases, both intestinal and non-intestinal, including multiple sclerosis (MS). Gut microbiota studies in patients with relapsing remitting MS strongly suggested its possible role in immunoregulation; however, the profile and potential of gut microbiota involvement in patients with primary progressive MS (PPMS) patients has received much less attention due to the rarity of this disease form. We compared the composition and structure of faecal bacterial assemblage using Illumina MiSeq sequencing of V3-V4 hypervariable region of 16S rRNA genes amplicons in patients with primary progressive MS and in the healthy controls.

Results

Over all samples 12 bacterial phyla were identified, containing 21 classes, 25 orders, 54 families, 174 genera and 1256 operational taxonomic units (OTUs). The Firmicutes phylum was found to be ultimately dominating both in OTUs richness (68% of the total bacterial OTU number) and in abundance (71% of the total number of sequence reads), followed by Bacteroidetes (12 and 16%, resp.) and Actinobacteria (7 and 6%, resp.). Summarily in all samples the number of dominant OTUs, i.e. OTUs with ≥1% relative abundance, was 13, representing much less taxonomic richness (three phyla, three classes, four orders, six families and twelve genera) as compared to the total list of identified OTUs and accounting for 30% of the sequence reads number in the healthy cohort and for 23% in the PPMS cohort. Human faecal bacterial diversity profiles were found to differ between PPMS and healthy cohorts at different taxonomic levels in minor or rare taxa. Marked PPMS-associated increase was found in the relative abundance of two dominant OTUs (Gemmiger sp. and an unclassified Ruminococcaceae). The MS-related differences were also found at the level of minor and rare OTUs (101 OTUs). These changes in OTUs’ abundance translated into increased bacterial assemblage diversity in patients.

Conclusion

The findings are important for constructing a more detailed global picture of the primary progressive MS-associated gut microbiota, contributing to better understanding of the disease pathogenesis.

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.

Suggestions for improving the design of clinical trials in multiple sclerosis-results of a systematic analysis of completed phase III trials

This manuscript reviews the primary and secondary endpoints of pivotal phase III trials with immunomodulatory drugs in multiple sclerosis (MS). Considering the limitations of previous trial designs, we propose new standards for the planning of clinical trials, taking into account latest insights into MS pathophysiology and patient-relevant aspects. Using a systematic overview of published phase III (pivotal) trials performed as part of application for drug market approval, we evaluate the following characteristics: trial duration, number of trial participants, comparators, and endpoints (primary, secondary, magnetic resonance imaging outcome, and patient-reported outcomes). From a patient perspective, the primary and secondary endpoints of clinical trials are only partially relevant. High-quality trial data pertaining to efficacy and safety that stretch beyond the time frame of pivotal trials are almost non-existent. Understanding of long-term benefits and risks of disease-modifying MS therapy is largely lacking. Concrete proposals for the trial designs of relapsing (remitting) multiple sclerosis/clinically isolated syndrome, primary progressive multiple sclerosis, and secondary progressive multiple sclerosis (e.g., study duration, mechanism of action, and choice of endpoints) are presented based on the results of the systematic overview. Given the increasing number of available immunotherapies, the therapeutic strategy in MS has shifted from a mere "relapse-prevention" approach to a personalized provision of medical care as to the choice of the appropriate drugs and their sequential application over the course of the disease. This personalized provision takes patient preferences as well as disease-related factors into consideration such as objective clinical and radiographic findings but also very burdensome symptoms such as fatigue, depression, and cognitive impairment. Future trial designs in MS will have to assign higher relevance to these patient-reported outcomes and will also have to implement surrogate measures that can serve as predictive markers for individual treatment response to new and investigational immunotherapies. This is an indispensable prerequisite to maximize the benefit of individual patients when participating in clinical trials. Moreover, such appropriate trial designs and suitable enrolment criteria that correspond to the mode of action of the study drug will facilitate targeted prevention of adverse events, thus mitigating risks for individual study participants.

Single Test to ARrive at Multiple Sclerosis (STAR-MS) diagnosis: A prospective pilot study assessing the accuracy of the central vein sign in predicting multiple sclerosis in cases of diagnostic uncertainty

Background:

Misdiagnosis is common in multiple sclerosis (MS) as a proportion of patients present with atypical clinical/magnetic resonance imaging (MRI) findings. The central vein sign has the potential to be a non-invasive, MS-specific biomarker.

Objective:

To test the accuracy of the central vein sign in predicting a diagnosis of MS in patients with diagnostic uncertainty at disease presentation using T2*-weighted, 3 T MRI.

Methods:

In this prospective pilot study, we recruited individuals with symptoms unusual for MS but with brain MRI consistent with the disease, and those with a typical clinical presentation of MS whose MRI did not suggest MS. We calculated the proportion of lesions with central veins for each patient and compared the results to the eventual clinical diagnoses. The optimal central vein threshold for diagnosis was established.

Results:

Thirty-eight patients were scanned, 35 of whom have received a clinical diagnosis. Median percentage of lesions with central veins was 51% in MS and 28% in non-MS. A threshold of 40.7% lesions with central veins resulted in 100% sensitivity and 73.9% specificity.

Conclusion:

The central vein sign assessed with a clinically available T2* scan can successfully diagnose MS in cases of diagnostic uncertainty. The central vein sign should be considered as a diagnostic biomarker in MS.

Strengthening the Medical Error "Meme Pool"

The exact number of patients in the USA who die from preventable medical errors each year is highly debated. Despite uncertainty in the underlying science, two very large estimates have spread rapidly through both the academic and popular media. We utilize Richard Dawkins' concept of the "meme" to explore why these imprecise estimates remain so compelling, and examine what potential harms can occur from their dissemination. We conclude by suggesting that instead of simply providing more precise estimates, physicians should encourage nuance in public medical error discussions, and strive to provide narrative context about the reality of the complex biological and social systems in which we practice medicine.