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: considerations in people from minority ethnic and racial backgrounds in North America, northern Europe, and Australasia

The differential diagnosis of suspected multiple sclerosis has been developed using data from North America, northern Europe, and Australasia, with a focus on White populations. People from minority ethnic and racial backgrounds in regions where prevalence of multiple sclerosis is high are more often negatively affected by social determinants of health, compared with White people in these regions. A better understanding of changing demographics, the clinical characteristics of people from minority ethnic or racial backgrounds, and the social challenges they face might facilitate equitable clinical approaches when considering a diagnosis of multiple sclerosis. Neuromyelitis optica, systemic lupus erythematous, neurosarcoidosis, infections, and cerebrovascular conditions (eg, hypertension) should be considered in the differential diagnosis of multiple sclerosis for people from minority ethnic and racial backgrounds in North America, northern Europe, and Australasia. The diagnosis of multiple sclerosis in people from a minority ethnic or racial background in these regions requires a comprehensive approach that considers the complex interplay of immigration, diagnostic inequity, and social determinants of health.

Consensus-Based Guidelines for Communicating a Misdiagnosis of Multiple Sclerosis to Reduce Psychological Distress

BACKGROUND

Multiple sclerosis (MS) misdiagnosis is common, and when discovered, frequently leads to substantial disruption to patients' lives and anxiety for clinicians. Our objective was to develop expert consensus-based guidelines about how to communicate a misdiagnosis of MS to a patient, to reduce the potential for both psychological distress and litigation.

METHODS

A modified Delphi method using a systematic literature review on doctor and patient experiences of the MS diagnosis communication was used to populate items for a first-round questionnaire. Our Delphi panel represented three perspectives (clinicians, people with MS, and published experts in health communication), and we recruited 18 panelists in total (6 per perspective). Consensus was defined a priori as 75% of panelists giving an item the same rating. A feedback round was undertaken with six external reviewers, naïve to the guideline development process, and the panelists. Items were reviewed by the study team and synthesized to create the finalized guidelines.

RESULTS

Consensus was reached for 45 items rated as "very important" and presented in the feedback round. The study team synthesized the 45 items to 27 items. Ten items related specifically to the communication of the MS misdiagnosis and 17 items to generic guidelines highlighted as important in the MS misdiagnosis appointment. Seven recommendations form the guidelines presented here.

CONCLUSIONS

Seven consensus-based recommendations offer guidance to practising neurologists in their communication with patients in a situation that has the potential to be highly distressing, for both clinician and patient.

Initial Evaluation of lncRNA A2M-AS1 Gene Expression in Multiple Sclerosis Patients

Background

Multiple sclerosis (MS) is one of the three leading neurodegenerative diseases worldwide. Gene expression profile studies play an important role in recognizing and preventing disease. Considering the inherent ability of biomarkers to diagnose and prognose the occurrence of a disease, with the aim of gene therapy and changing gene expression, it can be helped to treat it. In this study, by examining the gene interaction and expression of non-coding genes in patients with MS, using bioinformatics analyses, laboratory research and potential non-coding diagnostic biomarkers of MS were selected for further investigations.

Materials and Methods

First, by using micro-array data analysis of the GEO database, the expression status of the long non-coding ribonucleic acid (RNA) (lncRNA) A2M-AS1 gene was investigated in patients with MS. lncRNA-mRNA interaction analysis was performed in the lncRRisearch database. After sample collection, the total RNA extracted using the RNA extraction kit from 20 patient samples and 20 healthy samples was synthesized into cDNA with the synthesis kit. The quantitative reverse transcriptase polymerase chain reaction experiment was performed for the final validation of expression change.

Results

Based on bioinformatic and laboratory analysis, the expression of the A2M-AS1 gene in MS samples showed a significant decrease in expression compared to healthy samples. Also, based on the receiver operating characteristic analysis, lncRNA A2M-AS1 can be introduced as an acceptable diagnostic biomarker to distinguish MS samples from healthy samples.

Conclusion

lncRNA A2M-AS1, by reducing its expression as an acceptable diagnostic biomarker, can increase the risk of developing MS.

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.

Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis

In the majority of cases, multiple sclerosis (MS) is characterized by reversible episodes of neurological dysfunction, often followed by irreversible clinical disability. Accurate diagnostic criteria and prognostic markers are critical to enable early diagnosis and correctly identify patients with MS at increased risk of disease progression. The 2017 McDonald diagnostic criteria, which include magnetic resonance imaging (MRI) as a fundamental paraclinical tool, show high sensitivity and accuracy for the diagnosis of MS allowing early diagnosis and treatment. However, their inappropriate application, especially in the context of atypical clinical presentations, may increase the risk of misdiagnosis. To further improve the diagnostic process, novel imaging markers are emerging, but rigorous validation and standardization is still needed before they can be incorporated into clinical practice. This Series article discusses the current role of MRI in the diagnosis and prognosis of MS, while examining promising MRI markers, which could serve as reliable predictors of subsequent disease progression, helping to optimize the management of individual patients with MS. We also explore the potential of new technologies, such as artificial intelligence and automated quantification tools, to support clinicians in the management of patients. Yet, to ensure consistency and improvement in the use of MRI in MS diagnosis and patient follow-up, it is essential that standardized brain and spinal cord MRI protocols are applied, and that interpretation of results is performed by qualified (neuro)radiologists in all countries.

Artificial Intelligence and Multiple Sclerosis

In this paper, we analyse the different advances in artificial intelligence (AI) approaches in multiple sclerosis (MS). AI applications in MS range across investigation of disease pathogenesis, diagnosis, treatment, and prognosis. A subset of AI, Machine learning (ML) models analyse various data sources, including magnetic resonance imaging (MRI), genetic, and clinical data, to distinguish MS from other conditions, predict disease progression, and personalize treatment strategies. Additionally, AI models have been extensively applied to lesion segmentation, identification of biomarkers, and prediction of outcomes, disease monitoring, and management. Despite the big promises of AI solutions, model interpretability and transparency remain critical for gaining clinician and patient trust in these methods. The future of AI in MS holds potential for open data initiatives that could feed ML models and increasing generalizability, the implementation of federated learning solutions for training the models addressing data sharing issues, and generative AI approaches to address challenges in model interpretability, and transparency. In conclusion, AI presents an opportunity to advance our understanding and management of MS. AI promises to aid clinicians in MS diagnosis and prognosis improving patient outcomes and quality of life, however ensuring the interpretability and transparency of AI-generated results is going to be key for facilitating the integration of AI into clinical practice.

Diagnostic Criteria for Multiple Sclerosis, Neuromyelitis Optica Spectrum Disorders, and Myelin Oligodendrocyte Glycoprotein-immunoglobulin G-associated Disease

The diagnostic workup of multiple sclerosis (MS) has evolved considerably. The 2017 revision of the McDonald criteria shows high sensitivity and accuracy in predicting clinically definite MS in patients with a typical clinically isolated syndrome and allows an earlier MS diagnosis. Neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein-immunoglobulin G-associated disease (MOGAD) are recognized as separate conditions from MS, with specific diagnostic criteria. New MR imaging markers may improve diagnostic specificity for these conditions, thus reducing the risk of misdiagnosis. This study summarizes the most recent updates regarding the application of MR imaging for the diagnosis of MS, NMOSD, and MOGAD.

Applying the 2022 optic neuritis criteria to noninflammatory optic neuropathies with optic nerve T2-hyperintensity: an observational study

INTRODUCTION

Recent diagnostic criteria for optic neuritis include T2-hyperintensity of the optic nerve (ON), even without associated contrast enhancement. However, isolated ON-T2-hyperintensity is a nonspecific finding found in any optic neuropathy or severe retinopathy. We applied the 2022 optic neuritis diagnostic criteria to a cohort of patients with noninflammatory optic neuropathy and ON-T2-hyperintensity in at least one eye, to assess the rate of optic neuritis misdiagnosis using these criteria.

METHODS

Retrospective study of consecutive patients who underwent brain/orbit MRI with/without contrast between 07/01/2019 and 06/30/2022. Patients with ON-T2-hyperintensity in at least one eye were included. The 2022 optic neuritis diagnostic criteria were applied to patients with noninflammatory optic neuropathies who had an ophthalmologic examination available for review.

RESULTS

Of 150 patients included, 85/150 had compressive optic neuropathy; 32/150 had glaucoma; 12/150 had papilledema; 8/150 had hereditary (3), radiation-induced (3), nutritional (1), traumatic (1) optic neuropathies (none fulfilled the criteria); 13/150 had ischemic optic neuropathy and 4 fulfilled the criteria as definite optic neuritis due to contrast enhancement of the ON head. Seven additional patients would have satisfied the diagnostic criteria if red flags for alternative diagnoses had been overlooked.

DISCUSSION

The application of the 2022 optic neuritis diagnostic criteria in patients with noninflammatory optic neuropathy and ON-T2-hyperintensity in at least one ON resulted in misdiagnosis of optic neuritis in only 4 patients because of ON head enhancement, all with nonarteritic anterior ischemic optic neuropathy. Neuro-ophthalmologic evaluation and exclusion of the ON head as a location in the MRI criteria would have prevented optic neuritis misdiagnosis in our study.

Identification of Y‒linked biomarkers and exploration of immune infiltration of normal-appearing gray matter in multiple sclerosis by bioinformatic analysis

Background

The knowledge of normal‒appearing cortical gray matter (NAGM) in multiple sclerosis (MS) remains unclear. In this study, we aimed to identify diagnostic biomarkers and explore the immune infiltration characteristics of NAGM in MS through bioinformatic analysis and validation in vivo.

Methods

Differentially expressed genes (DEGs) were analyzed. Subsequently, the functional pathways of the DEGs were determined. After screening the overlapping DEGs of MS with two machine learning methods, the biomarkers' efficacy and the expression levels of overlapping DEGs were calculated. Quantitative reverse transcription polymerase chain reaction (qRT‒PCR) identified the robust diagnostic biomarkers. Additionally, infiltrating immune cell populations were estimated and correlated with the biomarkers. Finally, the characteristics of immune infiltration of NAGM from MS were evaluated.

Results

A total of 98 DEGs were identified. They participated in sensory transduction of the olfactory system, synaptic signaling, and immune responses. Nine overlapping genes were screened by machine learning methods. After verified by ROC curve, four genes, namely HLA‒DRB1, RPS4Y1, EIF1AY and USP9Y, were screened as candidate biomarkers. The mRNA expression of RPS4Y1 and USP9Y was significantly lower in MS patients than that in the controls. They were selected as the robust diagnostic biomarkers for male MS patients. RPS4Y1 and USP9Y were both positively correlated with memory B cells. Moreover, naive CD4+ T cells and monocytes were increased in the NAGM of MS patients compared with those in controls.

Conclusions

Low expressed Y‒linked genes, RPS4Y1 and USP9Y, were identified as diagnostic biomarkers for MS in male patients. The inhomogeneity of immune cells in NAGM might exacerbate intricate interplay between the CNS and the immune system in the MS.

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.

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

Importance

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

Objective

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

Design, Setting, and Participants

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

Exposures

MS/CIS vs non-MS conditions.

Main Outcomes and Measures

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

Results

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

Conclusions and Relevance

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

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.

Cellular and Molecular Evidence of Multiple Sclerosis Diagnosis and Treatment Challenges

Multiple sclerosis (MS) is a chronic autoimmune disease that impacts the central nervous system and can result in disability. Although the prevalence of MS has increased in India, diagnosis and treatment continue to be difficult due to several factors. The present study examines the difficulties in detecting and treating multiple sclerosis in India. A lack of MS knowledge among healthcare professionals and the general public, which delays diagnosis and treatment, is one of the significant issues. Inadequate numbers of neurologists and professionals with knowledge of MS management also exacerbate the situation. In addition, MS medications are expensive and not covered by insurance, making them inaccessible to most patients. Due to the absence of established treatment protocols and standards for MS care, India's treatment techniques vary. In addition, India's population diversity poses unique challenges regarding genetic variations, cellular and molecular abnormalities, and the potential for differing treatment responses. MS is more difficult to accurately diagnose and monitor due to a lack of specialized medical supplies and diagnostic instruments. Improved awareness and education among healthcare professionals and the general public, as well as the development of standardized treatment regimens and increased investment in MS research and infrastructure, are required to address these issues. By addressing these issues, it is anticipated that MS diagnosis and treatment in India will improve, leading to better outcomes for those affected by this chronic condition.

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.

[Diagnostic work-up, findings, and documentation of multiple sclerosis]

BACKGROUND

Although multiple sclerosis is the most common chronic inflammatory demyelinating disease of the central nervous system, the rate of misdiagnosis in clinical practice is high. This is usually due to the inadequate application of the McDonald criteria and misinterpretation of images.

OBJECTIVE

This review focuses on typical clinical symptoms, choice of magnetic resonance imaging (MRI) sequences, correct application of the McDonald criteria, and finally interpretation of the images.

Imaging of Central Nervous System Demyelinating Disorders

OBJECTIVE

This article summarizes neuroimaging findings in demyelinating disease, the most common being multiple sclerosis. Revisions to criteria and treatment options have been ongoing, and MRI plays a pivotal role in diagnosis and disease monitoring. The common antibody-mediated demyelinating disorders with their respective classic imaging features are reviewed, as well as the differential diagnostic considerations on imaging.

LATEST DEVELOPMENTS

The clinical criteria of demyelinating disease rely heavily on imaging with MRI. With novel antibody detection, the range of clinical demyelinating syndromes has expanded, most recently with myelin oligodendrocyte glycoprotein-IgG antibodies. Imaging has improved our understanding of the pathophysiology of multiple sclerosis and disease progression, and further research is underway. The importance of increased detection of pathology outside of the classic lesions will have an important role as therapeutic options are expanding.

ESSENTIAL POINTS

MRI has a crucial role in the diagnostic criteria and differentiation among common demyelinating disorders and syndromes. This article reviews the typical imaging features and clinical scenarios that assist in accurate diagnosis, differentiation between demyelinating diseases and other white matter diseases, the importance of standardized MRI protocols in clinical practice, and novel imaging techniques.

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.

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

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

Confirming a Historical Diagnosis of Multiple Sclerosis: Challenges and Recommendations

Patients with a historical diagnosis of multiple sclerosis (MS)-a patient presenting with a diagnosis of MS made previously and by a different clinician-present specific diagnostic and therapeutic challenges in clinical practice. Application of the McDonald criteria is most straightforward when applied contemporaneously with a syndrome typical of an MS attack or relapse; however, retrospective application of the criteria in some patients with a historical diagnosis of MS can be problematic. Limited patient recollection of symptoms and evolution of neurologic examination and MRI findings complicate confirmation of an earlier MS diagnosis and assessment of subsequent disease activity or clinical progression. Adequate records for review of prior clinical examinations, laboratory results, and/or MRI scans obtained at the time of diagnosis or during ensuing care may be inadequate or unavailable. This article provides recommendations for a clinical approach to the evaluation of patients with a historical diagnosis of MS to aid diagnostic confirmation, avoid misdiagnosis, and inform therapeutic decision making.

Do Hungarian multiple sclerosis care units fulfil international criteria?

A patients

Because of the past 3 decades’ extensive research, several disease modifying therapies became available, thus a paradigm change is multiple sclerosis care was necessary. In 2018 a therapeutic guideline was created recommending that treatment of persons with multiple sclerosis should take place in specified care units where the entire spectrum of disease modifying therapies is available, patient monitoring is ensured, and therapy side effects are detected and treated promptly. In 2019 multiple sclerosis care unit criteria were developed, emphasizing personnel and instrumental requirements to provide most professional care. However, no survey was conducted assessing the real-world adaptation of these criteria.

Objective

To assess whether Hungarian care units fulfil international criteria.

Methods

A self-report questionnaire was assembled based on international guidelines and sent to Hungarian care units focusing on 3 main aspects: personnel and instrumental background, disease-modifying therapy use, number of people living with multiple sclerosis receiving care in care units. Data on number of persons with multiple sclerosis were compared to Hungarian prevalence estimates. Descriptive statistics were used to analyse data.

Results

Out of 27 respondent care units, 3 fulfilled minimum requirements and 7 fulfilled minimum and recommended requirements. The least prevalent neighbouring specialties were spasticity and pain specialist, and neuro-ophthalmologist and oto-neurologist. Only 15 centres used all available disease modifying therapies. A total number of 7213 people with multiple sclerosis received care in 27 respondent centres. Compared to prevalence estimates, 2500 persons with multiple sclerosis did not receive multiple sclerosis specific care in Hungary.

Conclusion

Less than half of Hungarian care units provided sufficient care for people living with multiple sclerosis. Care units employing fewer neighbouring specialties, might have difficulties diagnosing and providing appropriate care for persons with multiple sclerosis, especially for people with progressive disease course, contributing to the reported low number of persons living with multiple sclerosis.

Neuroradiological differentiation of white matter lesions in patients with multiple sclerosis and Fabry disease

Objective

White matter lesions (WML) in multiple sclerosis (MS) differ from vascular WML caused by Fabry disease (FD). However, in atypical cases the discrimination can be difficult and may vary between individual raters. The aim of this study was to evaluate interrater reliability of WML differentiation between MS and FD patients.

Materials and methods

Brain MRI scans of 21 patients with genetically confirmed FD were compared to 21 matched patients with MS. Pseudonymized axial FLAIR sequences were assessed by 6 blinded raters and attributed to either the MS or the FD group to investigate interrater reliability. Additionally, localization of WML was compared between the two groups.

Results

The median age of patients was 46 years (IQR 35–58). Interrater reliability was moderate with a Fleiss' Kappa of 0.45 (95%CI 0.3–0.59). Overall, 85% of all ratings in the MS group and 75% in the FD group were correct. However, only 38% of patients with MS and 33% of patients with FD were correctly identified by all 6 raters. WML involving the corpus callosum (p < 0.001) as well as juxtacortical (p < 0.001) and infratentorial lesions (p = 0.03) were more frequently observed in MS patients.

Conclusion

Interrater reliability regarding visual differentiation of WML in MS from vascular WML in FD on standard axial FLAIR images alone is only moderate, despite the distinctive features of lesions in each group.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

KEY POINTS

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

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.

MRI of the Entire Spinal Cord-Worth the While or Waste of Time? A Retrospective Study of 74 Patients with Multiple Sclerosis

Spinal cord lesions are included in the diagnosis of multiple sclerosis (MS), yet spinal cord MRI is not mandatory for diagnosis according to the latest revisions of the McDonald Criteria. We investigated the distribution of spinal cord lesions in MS patients and examined how it influences the fulfillment of the 2017 McDonald Criteria. Seventy-four patients with relapsing-remitting MS were examined with brain and entire spinal cord MRI. Sixty-five patients received contrast. The number and anatomical location of MS lesions were assessed along with the Expanded Disability Status Scale (EDSS). A Chi-square test, Fischer’s exact test, and one-sided McNemar’s test were used to test distributions. MS lesions were distributed throughout the spinal cord. Diagnosis of dissemination in space (DIS) was increased from 58/74 (78.4%) to 67/74 (90.5%) when adding cervical spinal cord MRI to brain MRI alone (p = 0.004). Diagnosis of dissemination in time (DIT) was not significantly increased when adding entire spinal cord MRI to brain MRI alone (p = 0.04). There was no association between the number of spinal cord lesions and the EDSS score (p = 0.71). MS lesions are present throughout the spinal cord, and spinal cord MRI may play an important role in the diagnosis and follow-up of MS patients.

2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis

The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.

Diagnostic approach in multiple sclerosis with MRI: an update

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

Imaging of the Spinal Cord in Multiple Sclerosis: Past, Present, Future

Spinal cord imaging in multiple sclerosis (MS) plays a significant role in diagnosing and tracking disease progression. The spinal cord is one of four key areas of the central nervous system where documenting the dissemination in space in the McDonald criteria for diagnosing MS. Spinal cord lesion load and the severity of cord atrophy are believed to be more relevant to disability than white matter lesions in the brain in different phenotypes of MS. Axonal loss contributes to spinal cord atrophy in MS and its degree correlates with disease severity and prognosis. Therefore, measures of axonal loss are often reliable biomarkers for monitoring disease progression. With recent technical advances, more and more qualitative and quantitative MRI techniques have been investigated in an attempt to provide objective and reliable diagnostic and monitoring biomarkers in MS. In this article, we discuss the role of spinal cord imaging in the diagnosis and prognosis of MS and, additionally, we review various techniques that may improve our understanding of the disease.