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.

Differential diagnosis of suspected multiple sclerosis: global health considerations

The differential diagnosis of multiple sclerosis can present specific challenges in patients from Latin America, Africa, the Middle East, eastern Europe, southeast Asia, and the Western Pacific. In these areas, environmental factors, genetic background, and access to medical care can differ substantially from those in North America and western Europe, where multiple sclerosis is most common. Furthermore, multiple sclerosis diagnostic criteria have been developed primarily using data from North America and western Europe. Although some diagnoses mistaken for multiple sclerosis are common regardless of location, a comprehensive approach to the differential diagnosis of multiple sclerosis in Latin America, Africa, the Middle East, eastern Europe, southeast Asia, and the Western Pacific regions requires special consideration of diseases that are prevalent in those locations. A collaborative effort has therefore assessed global differences in multiple sclerosis differential diagnoses and proposed recommendations for evaluating patients with suspected multiple sclerosis in regions beyond North America and western Europe.

Diagnostic performance of central vein sign versus oligoclonal bands for multiple sclerosis

BACKGROUND

Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy.

OBJECTIVES

The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS.

METHODS

Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months.

RESULTS

Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status.

DISCUSSION

Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB.

Differentiating multiple sclerosis from non-specific white matter changes using a convolutional neural network image classification model

BACKGROUND

The diagnosis of multiple sclerosis (MS) relies heavily on neuroimaging with magnetic resonance imaging (MRI) and exclusion of mimics. This can be a challenging task due to radiological overlap in several disorders and may require ancillary testing or longitudinal follow up. One of the most common radiological MS mimickers is non-specific white matter disease (NSWMD). We aimed to develop and evaluate models leveraging machine learning algorithms to help distinguish MS and NSWMD.

METHODS

All adult patients who underwent MRI brain using a demyelinating protocol with available electronic medical records between 2015 and 2019 at Cleveland Clinic affiliated facilities were included. Diagnosis of MS and NSWMD were assessed from clinical documentation. Those with a diagnosis of MS and NSWMD were matched using total T2 lesion volume (T2LV) and used to train models with logistic regression and convolutional neural networks (CNN). Performance metrices were reported for each model.

RESULTS

A total of 250 NSWMD MRI scans were identified, and 250 unique MS MRI scans were matched on T2LV. Cross validated logistic regression model was able to use 20 variables (including spinal cord area, regional volumes, and fractions) to predict MS compared to NSWMD with 68.0% accuracy while the CNN model was able to classify MS compared to NSWMD in two independent validation and testing cohorts with 77% and 78% accuracy on average.

CONCLUSION

Automated methods can be used to differentiate MS compared to NSWMD. These methods can be used to supplement currently available diagnostic tools for patients being evaluated for MS.

Multiple Sclerosis Diagnostic Delay and Misdiagnosis

Multiple sclerosis (MS) misdiagnosis in the form of an incorrect diagnosis of MS, as well as delayed diagnosis in patients who do have MS, both influence patient clinical outcomes. Contemporary studies have reported data on factors associated with these diagnostic challenges and their frequency. Expediting diagnosis in patients with MS and reducing MS misdiagnosis in patients who do not have MS may be aided by educational efforts surrounding early MS symptoms and proper application of MS diagnostic criteria. Emerging novel MS diagnostic biomarkers may aid early and accurate diagnosis of MS in the future.

Differences in Brain Atrophy Pattern between People with Multiple Sclerosis and Systemic Diseases with Central Nervous System Involvement Based on Two-Dimensional Linear Measures

Conventional brain magnetic resonance imaging (MRI) in systemic diseases with central nervous system involvement (SDCNS) may imitate MRI findings of multiple sclerosis (MS). In order to better describe the MRI characteristics of these conditions, in our study we assessed brain volume parameters in MS (n = 58) and SDCNS (n = 41) patients using two-dimensional linear measurements (2DLMs): bicaudate ratio (BCR), corpus callosum index (CCI) and width of third ventricle (W3V). In SDCNS patients, all 2DLMs were affected by age (CCI p = 0.005, BCR p < 0.001, W3V p < 0.001, respectively), whereas in MS patients only BCR and W3V were (p = 0.001 and p = 0.015, respectively). Contrary to SDCNS, in the MS cohort BCR and W3V were associated with T1 lesion volume (T1LV) (p = 0.020, p = 0.009, respectively) and T2 lesion volume (T2LV) (p = 0.015, p = 0.009, respectively). CCI was associated with T1LV in the MS cohort only (p = 0.015). Moreover, BCR was significantly higher in the SDCNS group (p = 0.01) and CCI was significantly lower in MS patients (p = 0.01). The best predictive model to distinguish MS and SDCNS encompassed gender, BCR and T2LV as the explanatory variables (sensitivity 0.91; specificity 0.68; AUC 0.86). Implementation of 2DLMs in the brain MRI analysis of MS and SDCNS patients allowed for the identification of diverse patterns of local brain atrophy in these clinical conditions.

Misdiagnosis in multiple sclerosis in a Brazilian reference center: Clinical, radiological, laboratory profile and failures in the diagnostic process-Cohort study

BACKGROUND

Multiple sclerosis misdiagnosis remains a problem despite the well-validated McDonald 2017. For proper evaluation of errors in the diagnostic process that lead to misdiagnosis, it is adequate to incorporate patients who are already under regular follow-up at reference centers of demyelinating diseases.

OBJECTIVES

To evaluate multiple sclerosis misdiagnosis in patients who are on follow-up at a reference center of demyelinating diseases in Brazil.

METHODS

We designed an observational study including patients in regular follow-up, who were diagnosed with multiple sclerosis at our specialized outpatient clinic in the Hospital of Clinics in the University of Sao Paulo, from 1996 to 2021, and were reassessed for misdiagnosis in 2022. We evaluated demographic information, clinical profile, and complementary exams and classified participants as "established multiple sclerosis," "non-multiple sclerosis, diagnosed," and "non-multiple sclerosis, undiagnosed." Failures in the diagnostic process were assessed by the modified Diagnostic Error Evaluation and Research tool.

RESULTS

A total of 201 patients were included. After analysis, 191/201 (95.02%) participants were confirmed as "established multiple sclerosis," 5/201 (2.49%) were defined as "non-multiple sclerosis, diagnosed," and 5/201 (2.49%) were defined as "non-multiple sclerosis, undiagnosed."

CONCLUSIONS

Multiple sclerosis misdiagnosis persists in reference centers, emphasizing the need for careful interpretation of clinical findings to prevent errors.

Identification of demyelinating lesions and application of McDonald criteria when confronted with white matter lesions on brain MRI

INTRODUCTION

White matter lesions (WML) on magnetic resonance imaging (MRI) are common in clinical practice. When analyzing WML, radiologists sometimes propose a pathophysiological mechanism to explain the observed MRI abnormalities, which can be a source of anxiety for patients. In some cases, discordance may appear between the patient's clinical symptoms and the identification of the MRI-appearing WML, leading to extensive diagnostic work-up. To avoid misdiagnosis, the analysis of WML should be standardized, and a consensual MRI reading approach is needed.

OBJECTIVE

To analyze the MRI WML identification process, associated diagnosis approach, and misinterpretations in physicians involved in WML routine practice.

METHODS

Through a survey distributed online to practitioners involved in WML diagnostic work-up, we described the leading causes of MRI expertise misdiagnosis and associated factors: clinical experience, physicians' subspecialty and location of practice, and type of device used to complete the survey. The survey consisted of sixteen T2-weighted images MRI analysis, from which ten were guided (binary response to lesion location identification), four were not shown (multiple possible answers), and two were associated with dissemination in space (DIS) McDonald criteria application. Two independent, experienced practitioners determined the correct answers before the participants' completion.

RESULTS

In total, 364 participants from the French Neuro Radiological (SFNR), French Neurological (SFN), and French Multiple Sclerosis (SFSEP) societies completed the survey entirely. According to lesion identification, 34.3% and 16.9% of the participants correctly identified juxtacortical and periventricular lesions, respectively, whereas 56.3% correctly identified non-guided lesions. Application of the 2017 McDonald's DIS criteria was correct for 35.3% of the participants. According to the global survey scoring, factors independently associated with correct answers in multivariate analysis were MS-expert subspecialty (P<0.001), young clinical practitioners (P=0.02), and the use of a computer instead of a smartphone to perform WML analysis (P=0.03).

CONCLUSION

Our results highlight the difficulties regarding WML analysis in clinical practice and suggest that radiologists and neurologists should rely on each other to ensure the diagnosis of multiple sclerosis and related disorders and limit misdiagnoses.

Laboratory evaluation for the differential diagnosis of possible multiple sclerosis in the United States: A physician survey

BACKGROUND

There is limited evidence and lack of guidelines for diagnostic laboratory evaluation of patients with possible multiple sclerosis (MS).

OBJECTIVE

To survey neurologists on their practice of laboratory testing in patients with possible MS.

METHODS

An online survey was developed to query the frequency of serum and cerebrospinal fluid (CSF) studies ordered in the routine evaluation of patients with possible MS, and in three hypothetical clinical cases. Non-MS specialist neurologists who evaluate patients for MS in their practice were invited to participate by MedSurvey (a medical market research company).

RESULTS

The survey was completed by 190 neurologists. A mean of 17.2 (SD: 17.0) tests in serum and CSF were reported "always" ordered in the evaluation of patients with possible MS. CSF oligoclonal bands was the most frequently selected ("always" among 73.7% of participants). Antinuclear antibody (43.2%), erythrocyte sedimentation rate (34.2%), and thyroid stimulating hormone (31.6%) were also among the most frequently ordered.

DISCUSSION

Extensive laboratory evaluations are often completed in the evaluation of possible MS. However, many of these tests have poor specificity and false positive results could yield unnecessary increased costs, diagnostic delay, and potentially misdiagnosis. Further research is needed to identify optimal laboratory approaches for possible MS.

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.

Differential diagnosis of suspected multiple sclerosis: an updated consensus approach

Accurate diagnosis of multiple sclerosis requires careful attention to its differential diagnosis-many disorders can mimic the clinical manifestations and paraclinical findings of this disease. A collaborative effort, organised by The International Advisory Committee on Clinical Trials in Multiple Sclerosis in 2008, provided diagnostic approaches to multiple sclerosis and identified clinical and paraclinical findings (so-called red flags) suggestive of alternative diagnoses. Since then, knowledge of disorders in the differential diagnosis of multiple sclerosis has expanded substantially. For example, CNS inflammatory disorders that present with syndromes overlapping with multiple sclerosis can increasingly be distinguished from multiple sclerosis with the aid of specific clinical, MRI, and laboratory findings; studies of people misdiagnosed with multiple sclerosis have also provided insights into clinical presentations for which extra caution is warranted. Considering these data, an update to the recommended diagnostic approaches to common clinical presentations and key clinical and paraclinical red flags is warranted to inform the contemporary clinical evaluation of patients with suspected multiple sclerosis.

Absence of Oligoclonal Bands in Multiple Sclerosis: A Call for Differential Diagnosis

BACKGROUND

Immunoglobulin gamma (IgG) oligoclonal bands (OCB) in the cerebrospinal fluid (CSF) are absent in a small group of multiple sclerosis (MS) patients. According to previous research, OCB-negative MS patients differ genetically but not clinically from OCB-positive MS patients. However, whether OCB-negative MS is a unique immunological and clinical entity remains unclear. The absence of OCB poses a significant challenge in diagnosing MS. (1) Objective: The objective of this study was twofold: (1) to determine the prevalence of OCB-negative MS patients in the Uppsala region, and (2) to assess the frequency of misdiagnosis in this patient group. (2) Methods: We conducted a retrospective study using data from the Swedish MS registry (SMSreg) covering 83% of prevalent MS cases up to 20 June 2020 to identify all MS patients in the Uppsala region. Subsequently, we collected relevant information from the medical records of all OCB-negative MS cases, including age of onset, gender, presenting symptoms, MRI features, phenotype, Expanded Disability Status Scale (EDSS) scores, and disease-modifying therapies (DMTs). (3) Results: Out of 759 MS patients identified, 69 had an OCB-negative MS diagnosis. Upon re-evaluation, 46 patients had a typical history and MRI findings of MS, while 23 had unusual clinical and/or radiologic features. An alternative diagnosis was established for the latter group, confirming the incorrectness of the initial MS diagnosis. The average EDSS score was 2.0 points higher in the MS group than in the non-MS group (p = 0.001). The overall misdiagnosis rate in the cohort was 33%, with 22% of misdiagnosed patients having received DMTs. (4) Conclusions: Our results confirm that the absence of OCB in the CSF should raise suspicion of possible misdiagnosis in MS patients and prompt a diagnostic reassessment.

Metal-Organic Frameworks-Based Nanoplatforms for the Theranostic Applications of Neurological Diseases

Neurological diseases are the foremost cause of disability and the second leading cause of death worldwide. Owing to the special microenvironment of neural tissues and biological characteristics of neural cells, a considerable number of neurological disorders are currently incurable. In the past few years, the development of nanoplatforms based on metal-organic frameworks (MOFs) has broadened opportunities for offering sensitive diagnosis/monitoring and effective therapy of neurology-related diseases. In this article, the obstacles for neurotherapeutics, including delayed diagnosis and misdiagnosis, the existence of blood brain barrier (BBB), off-target treatment, irrepressible inflammatory storm/oxidative stress, and irreversible nerve cell death are summarized. Correspondingly, MOFs-based diagnostic/monitoring strategies such as neuroimaging and biosensors (electrochemistry, fluorometry, colorimetry, electrochemiluminescence, etc.) and MOFs-based therapeutic strategies including higher BBB permeability, targeting specific lesion sites, attenuation of neuroinflammation/oxidative stress as well as regeneration of nerve cells, are extensively highlighted for the management of neurological diseases. Finally, the challenges of the present research from perspective of clinical translation are discussed, hoping to facilitate interdisciplinary studies at the intersections between MOFs-based nanoplatforms and neurotheranostics.

Cerebrospinal Fluid Biomarkers in Differential Diagnosis of Multiple Sclerosis and Systemic Inflammatory Diseases with Central Nervous System Involvement

BACKGROUND

Diagnosis of multiple sclerosis (MS) is established on criteria according to clinical and radiological manifestation. Cerebrospinal fluid (CSF) analysis is an important part of differential diagnosis of MS and other inflammatory processes in the central nervous system (CNS).

METHODS

In total, 242 CSF samples were collected from patients undergoing differential MS diagnosis because of the presence of T2-hyperintensive lesions on brain MRI. The non-MS patients were subdivided into systemic inflammatory diseases with CNS involvement (SID) or cerebrovascular diseases (CVD) or other non-inflammatory diseases (NID). All samples were analyzed for the presence of oligoclonal bands and ELISA was performed for detection of: INF gamma, IL-6, neurofilaments light chain (NF-L), GFAP, CHI3L1, CXCL13, and osteopontin.

RESULTS

The level of IL-6 (p = 0.024), osteopontin (p = 0.0002), and NF-L (p = 0.002) was significantly different among groups. IL-6 (p = 0.0350) and NF-L (p = 0.0015) level was significantly higher in SID compared to NID patients. A significantly higher level of osteopontin (p = 0.00026) and NF-L (p = 0.002) in MS compared to NID population was noted. ROC analysis found weak diagnostic power for osteopontin and NFL-L.

CONCLUSIONS

The classical and non-standard markers of inflammatory process and neurodegeneration do not allow for sufficient differentiation between MS and non-MS inflammatory CNS disorders. Weak diagnostic power observed for the osteopontin and NF-L needs to be further investigated.

The borderland of multiple sclerosis and functional neurological disorder: A call for clinical research and vigilance

BACKGROUND AND PURPOSE

Functional neurological disorders (FNDs) have attracted much attention from the neurological medical community over the last decades as new developments in neurosciences have reduced stigma around these by showing brain network dysfunctions. An overlap with other neurological conditions such as multiple sclerosis (MS) is well known by clinicians but there is a lack of clinical and fundamental research in this field to better define diagnosis and therapeutic decisions, as well as a lack of deep understanding of the underlying pathophysiology.

AIM

We aimed to provide a critical commentary on the state of knowledge about the borderland between FNDs and MS.

METHODS

We based our commentary on a joint point of view between an FND specialist and an MS expert.

RESULTS

A brief review of the previous literature and relevant new studies covering the overlap between FNDs and MS is presented, along with suggestions for future research directions.

CONCLUSION

There are clear diagnostic criteria for both FNDs and MS and a strict application of these will help better diagnosis and prevent unnecessary treatment escalation in MS or absence of referral to multimodal therapy in FND. Better teaching of younger neurologists is needed as well as prospective research focusing on pathophysiology.

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.

Early Diagnosis of Multiple Sclerosis Using Swept-Source Optical Coherence Tomography and Convolutional Neural Networks Trained with Data Augmentation

BACKGROUND

The aim of this paper is to implement a system to facilitate the diagnosis of multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network (CNN) to classify images captured with swept-source optical coherence tomography (SS-OCT).

METHODS

SS-OCT images from 48 control subjects and 48 recently diagnosed MS patients have been used. These images show the thicknesses (45 × 60 points) of the following structures: complete retina, retinal nerve fiber layer, two ganglion cell layers (GCL+, GCL++) and choroid. The Cohen distance is used to identify the structures and the regions within them with greatest discriminant capacity. The original database of OCT images is augmented by a deep convolutional generative adversarial network to expand the CNN's training set.

RESULTS

The retinal structures with greatest discriminant capacity are the GCL++ (44.99% of image points), complete retina (26.71%) and GCL+ (22.93%). Thresholding these images and using them as inputs to a CNN comprising two convolution modules and one classification module obtains sensitivity = specificity = 1.0.

CONCLUSIONS

Feature pre-selection and the use of a convolutional neural network may be a promising, nonharmful, low-cost, easy-to-perform and effective means of assisting the early diagnosis of MS based on SS-OCT thickness data.

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.