Search

The association between trigeminal neuralgia (TN) and multiple sclerosis (MS) is well established. Many MS patients with TN have magnetic resonance imaging (MRI) evidence of a symptomatic demyelinating lesion. Although infratentorial presentations are included in the diagnostic criteria for MS, there remains confusion in clinical practice as to whether TN should be considered a clinically isolated syndrome for the application of McDonald criteria. In this case series, we discuss this diagnostic quandary in patients presenting with TN and additional MRI findings suggestive of MS and highlight the unmet need for data in such patients to optimally guide their care.

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.

Impairment in persons with multiple sclerosis (PwMS) can often be attributed to symptoms of motor instability and fatigue. Symptom monitoring and queued interventions often target these symptoms. Clinical metrics are currently limited to objective physician assessments or subjective patient reported measures. Recent research has turned to wearables for improving the objectivity and temporal resolution of assessment. Our group has previously observed wearable assessment of supervised and unsupervised standing transitions to be predictive of fall-risk in PwMS. Here we extend the application of standing transition quantification to longitudinal home monitoring of symptoms. Subjects (N=23) with varying degrees of MS impairment were recruited and monitored with accelerometry for a total of ~6 weeks each. These data were processed using a deep learning activity classifier to isolate periods of standing transition from which descriptive features were extracted for analysis. Participants completed daily and biweekly assessments describing their symptoms. From these data, Canonical Correlation Analysis was used to derive digital phenotypes of MS instability and fatigue. We find these phenotypes capable of distinguishing fallers from non-fallers, and further that they demonstrate a capacity to characterize symptoms at both daily and sub-daily resolutions. These results represent promising support for future applications of wearables, which may soon augment or replace current metrics in longitudinal monitoring of PwMS.

The clinical evaluation of a new diagnosis of MS typically includes serologic testing to evaluate for its many mimics, yet there is little data to guide approaches to such testing.To evaluate for the frequency and clinical significance of serologic testing for MS diagnostic evaluations.In a single MS subspeciality center retrospective study, new patient evaluations for MS over the course of a year were identified, and the results of serologic testing and diagnostic evaluation extracted. Retrospective longitudinal diagnostic assessment was performed to confirm the accuracy of initial serological testing assessments.150 patients had 823 serologic tests. 40 (5%) tests were positive, and resulted in 117 additional serologic tests, 10 radiographs, and 2 biopsies. 77 (51%) patients were diagnosed with a non-demyelinating disorder. Serologic testing results did not change any diagnosis, yet in some patients, it resulted in unnecessary additional testing and diagnostic delay.Serologic testing in the clinical assessment for routine MS resulted in unnecessary diagnostic delay, additional testing, and considerable healthcare cost.

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.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.

BACKGROUND The aim of this study was to assess how frequently epileptologists discuss advance directives regarding intubation and mechanical ventilation with patients with epilepsy. A secondary aim was to understand the attitudes of neurologists toward discussion and implementation of such advance directives in epilepsy care. METHODS An online study survey was developed and distributed by email invitation to 210 neurologists at academic epilepsy and neurophysiology programs in the United States in December 2018. RESULTS Seventy-seven neurologists, 95% with a clinical practice focus of epilepsy in adults, participated in the study (37% response rate). Three percent reported discussion of risk of intubation with "every" or a "majority" of patients newly diagnosed with epilepsy. Seventy-seven percent indicated a neurologist was the "most appropriate provider to have discussions concerning mechanical ventilation with patients with epilepsy." Twenty-five percent "strongly agreed" that "every patient with epilepsy should have an advance directive specifying their preferences concerning mechanical ventilation in the setting of treatment for seizures." A majority favored overriding a hypothetical patient's advance directive specifying no intubation in the context of airway compromise as a consequence of status epilepticus and its treatment. CONCLUSIONS Epileptologists infrequently discuss the risk of intubation and mechanical ventilation with patients with epilepsy. Many felt that such discussions are unnecessary with most patients, but also best led by a neurologist. Neurologists with expertise in epilepsy may favor overriding advance directives in the setting of status epilepticus. Further data is needed surrounding discussion and implementation of advance care planning in patients with epilepsy.

ImportanceAutoimmune encephalitis misdiagnosis can lead to harm.ObjectiveTo determine the diseases misdiagnosed as autoimmune encephalitis and potential reasons for misdiagnosis.Design, Setting, and ParticipantsThis retrospective multicenter study took place from January 1, 2014, to December 31, 2020, at autoimmune encephalitis subspecialty outpatient clinics including Mayo Clinic (n = 44), University of Oxford (n = 18), University of Texas Southwestern (n = 18), University of California, San Francisco (n = 17), Washington University in St Louis (n = 6), and University of Utah (n = 4). Inclusion criteria were adults (age ≥18 years) with a prior autoimmune encephalitis diagnosis at a participating center or other medical facility and a subsequent alternative diagnosis at a participating center. A total of 393 patients were referred with an autoimmune encephalitis diagnosis, and of those, 286 patients with true autoimmune encephalitis were excluded.Main Outcomes and MeasuresData were collected on clinical features, investigations, fulfillment of autoimmune encephalitis criteria, alternative diagnoses, potential contributors to misdiagnosis, and immunotherapy adverse reactions.ResultsA total of 107 patients were misdiagnosed with autoimmune encephalitis, and 77 (72%) did not fulfill diagnostic criteria for autoimmune encephalitis. The median (IQR) age was 48 (35.5-60.5) years and 65 (61%) were female. Correct diagnoses included functional neurologic disorder (27 [25%]), neurodegenerative disease (22 [20.5%]), primary psychiatric disease (19 [18%]), cognitive deficits from comorbidities (11 [10%]), cerebral neoplasm (10 [9.5%]), and other (18 [17%]). Onset was acute/subacute in 56 (52%) or insidious (>3 months) in 51 (48%). Magnetic resonance imaging of the brain was suggestive of encephalitis in 19 of 104 patients (18%) and cerebrospinal fluid (CSF) pleocytosis occurred in 16 of 84 patients (19%). Thyroid peroxidase antibodies were elevated in 24 of 62 patients (39%). Positive neural autoantibodies were more frequent in serum than CSF (48 of 105 [46%] vs 7 of 91 [8%]) and included 1 or more of GAD65 (n = 14), voltage-gated potassium channel complex (LGI1 and CASPR2 negative) (n = 10), N-methyl-d-aspartate receptor by cell-based assay only (n = 10; 6 negative in CSF), and other (n = 18). Adverse reactions from immunotherapies occurred in 17 of 84 patients (20%). Potential contributors to misdiagnosis included overinterpretation of positive serum antibodies (53 [50%]), misinterpretation of functional/psychiatric, or nonspecific cognitive dysfunction as encephalopathy (41 [38%]).Conclusions and RelevanceWhen evaluating for autoimmune encephalitis, a broad differential diagnosis should be considered and misdiagnosis occurs in many settings including at specialized centers. In this study, red flags suggesting alternative diagnoses included an insidious onset, positive nonspecific serum antibody, and failure to fulfill autoimmune encephalitis diagnostic criteria. Autoimmune encephalitis misdiagnosis leads to morbidity from unnecessary immunotherapies and delayed treatment of the correct diagnosis.

BackgroundCortical demyelinated lesions are prevalent in multiple sclerosis (MS) and associated with disability; their presence on MRI has recently been incorporated into MS diagnostic criteria. Presently, advanced and ultra-high-field MRI — not routinely available in clinical practice — are the most sensitive methods for detection of cortical lesions, and approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need.ObjectiveTo assess the sensitivity of the ratio of T1-weighted and T2-weighted (T1/T2) signal intensity for focal cortical lesions in comparison to other established, sensitive, advanced and high-field imaging methods.Methods3-tesla (3T) and 7-tesla (7T) MRI collected from 10 adults with MS participating in a natural history study at the National Institutes of Health were included in the study. T1/T2 images were calculated by dividing 3T T1w images by 3T T2w fluid-attenuated inversion recovery (FLAIR) images for each participant. Cortical lesions were identified using 7T T2*w and T1w images and corresponding voxels were assessed on registered 3T images. For each participant, ratios derived from the median signal intensity of nonlesional tissue in the cortical region of the lesion and the median lesional voxel intensity were computed. These values were compared across 3T imaging sequences, including the calculated T1/T2 image, as well as T1w, T2w, and Inversion Recovery Susceptibility Weighted Imaging with Enhanced T2 weighting (IR-SWIET) images.Results614 cortical lesions were identified on 7T images. 3T T1/T2 images demonstrated a larger contrast between median nonlesional cortical signal intensity and median cortical lesion signal intensity (median ratio = 1.29, range 1.19 – 1.38) when compared to T1w (1.01, 0.97 – 1.10, p2w (1.17, 1.07 – 1.26, pConclusionT1/T2 images are sensitive to cortical lesions. Approaches incorporating T1/T2 could improve the accessibility of cortical lesion detection in research settings and clinical practice.

BACKGROUND: One in two people with multiple sclerosis (PwMS) will fall in a three-month period. Predicting which patients will fall remains a challenge for clinicians. Standardized functional assessments provide insight into balance deficits and fall risk but their use has been limited to supervised visits. RESEARCH QUESTION: The study aim was to characterize unsupervised 30-second chair stand test (30CST) performance using accelerometer-derived metrics and assess its ability to classify fall status in PwMS compared to supervised 30CST. METHODS: Thirty-seven PwMS (21 fallers) performed instrumented supervised and unsupervised 30CSTs with a single wearable sensor on the thigh. In unsupervised conditions, participants performed bi-hourly 30CSTs and rated their balance confidence and fatigue over 48-hours. ROC analysis was used to classify fall status for 30CST performance. RESULTS: Non-fallers (p=0.02) but not fallers (p=0.23) differed in their average unsupervised 30CST performance (repetitions) compared to their supervised performance. The unsupervised maximum number of 30CST repetitions performed optimized ROC classification AUC (0.79), accuracy (78.4%) and specificity (90.0%) for fall status with an optimal cutoff of 17 repetitions. SIGNIFICANCE: Brief durations of instrumented unsupervised monitoring as an adjunct to routine clinical assessments could improve the ability for predicting fall risk and fluctuations in functional mobility in PwMS.

Background Approximately half of the 2.3 million people with multiple sclerosis (PwMS) will fall in any three-month period. Currently clinicians rely on self-report measures or simple functional assessments, administered at discrete time points, to assess fall risk. Wearable inertial sensors are a promising technology for increasing the sensitivity of clinical assessments to accurately predict fall risk, but current accelerometer-based approaches are limited. Research question Will metrics derived from wearable accelerometers during a 30-second chair stand test (30CST) correlate with clinical measures of disease severity, balance confidence and fatigue in PwMS, and can these metrics be used to accurately discriminate fallers from non-fallers? Methods Thirty-eight PwMS (21 fallers) completed self-report outcome measures then performed the 30CST while triaxial acceleration data were collected from inertial sensors adhered to the thigh and chest. Accelerometer metrics were derived for the sit-to-stand and stand-to-sit transitions and relationships with clinical metrics were assessed. Finally, the metrics were used to develop a logistic regression model to classify fall status. Results Accelerometer-derived metrics were significantly associated with multiple clinical metrics that capture disease severity, balance confidence and fatigue. Performance of a logistic regression for classifying fall status was enhanced by including accelerometer features (accuracy 74%, AUC 0.78) compared to the standard of care (accuracy 68%, AUC 0.74) or patient reported outcomes (accuracy 71%, AUC 0.75). Significance Accelerometer derived metrics were associated with clinically relevant measures of disease severity, fatigue and balance confidence during a balance challenging task. Inertial sensors could feasibly be utilized to enhance the accuracy of functional assessments to identify fall risk in PwMS. Simplicity of these accelerometer-based metrics could facilitate deployment for community-based monitoring.

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.

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.

Lipoic acid (alpha lipoic acid, thioctic acid) is a popular over-the-counter antioxidant and insulin-mimetic supplement under investigation in a variety of conditions including multiple sclerosis, diabetes, and schizophrenia. Unfortunately, high-grade proteinuria was an unexpected adverse event specific to the treatment arm of our clinical trial investigating lipoic acid supplementation in patients with multiple sclerosis. This observation led to detection of similar patients in our nephrology practice. Here, we describe four biopsy-proven cases of neural epidermal growth factor-like 1 (NELL1)-associated membranous nephropathy following lipoic acid supplementation and a fifth suspected case. Discontinuation of lipoic acid and supportive therapy resulted in remission.

Multiple sclerosis (MS) is a "3C" (complex, chronic, costly) condition that is a common and disabling neurological illness affecting approximately 1 million adults in the United States. MS has been studied at the basic science, individual, and population levels, but not at the system level to assess small-area variation effects on MS population health outcomes. System-level effects have been observed in other 3C conditions including cystic fibrosis, rheumatoid arthritis, and inflammatory bowel disease. The authors report here on system-level variation findings from the baseline period during the first year of the Multiple Sclerosis Continuous Quality Improvement (MS-CQI) study. Stepwise binary logistic regression analyses were conducted to investigate system-level (small-area variation) effects on MS relapses (exacerbations), disease-modifying therapy (DMT) utilization, and brain MRI utilization, controlling for demographics (age and sex) and other potential confounders. Significant differences were observed in people with MS (PwMS) between centers for a number of demographic and disease characteristics, including sex, age, and MS subtype. Controlling for these factors, significant system-level effects were observed on outcomes, including DMT utilization, MRI utilization, and relapses. Significant relationships also were observed between outcomes and urgent care utilization, including emergency department visits and hospitalizations. This initial study provides evidence establishing the presence of system-level variation effects on MS outcomes in a multicenter population study - where PwMS get their care can influence their outcomes. Results support continued systems-level research and improvement initiatives to optimize MS population health outcomes in this challenging and costly complex chronic condition.

Fatigue is the most common symptom and a leading cause of disability multiple sclerosis (MS). Despite the lack of evidence, several medications are frequently prescribed by physicians to ameliorate fatigue in patients with MS. However, a recent study demonstrated that improvement in fatigue severity with these medications appears to be due to placebo effect and is also is associated with more frequent adverse events than the placebo. These findings raise ethical concerns surrounding the initiation and discontinuation of these treatments for fatigue in MS. Starting these medications for the treatment of MS fatigue for their placebo effect may not be justified. However, stopping the medications in patients who report symptomatic benefits and have no side effects may also not be ethical. In MS care non-pharmacological approaches for fatigue treatment, such as exercise and cognitive behavioral therapy, should now be prioritized. Novel study designs may be necessary to address placebo response in future clinical trials evaluating interventions for fatigue in MS.

Background:We developed a preference assessment tool to help assess patient goals, values, and preferences for multiple sclerosis (MS) management. All preference items in the tool were generated by people with MS. The aim of this study was to evaluate this tool in a national sample of people with MS.Methods:English-speaking patients with MS aged 21 to 75 years with access to the internet were recruited. Participants completed the preference tool online, which included separate modules assessing three core preference areas: treatment goals, preferences for attributes of disease-modifying therapies, and factors influencing a change in treatment. The tool generated a summary of participants' treatment goals and preferences. Immediately after viewing the summary, participants were asked to evaluate the tool. Rankings of preference domains were compared with rankings obtained in another study.Results:In 135 people with MS who completed the tool and evaluation, the highest ranked goal was brain health (memory, thinking, brain), followed by disability concerns (walking, strength, vision). Rankings were highly similar to those in the referent study. Nearly all participants reported that the tool helped them understand their goals and priorities regarding MS and that the summary appropriately reflected what is important to them. Most participants (87%) wanted to discuss their treatment goals and priorities with their clinician.Conclusions:This preference assessment tool successfully captured patients' goals, values, and preferences for MS treatment and could potentially be used to help patients communicate their preferences to their clinician.

Misdiagnosis of multiple sclerosis (MS) (the incorrect assignment of a diagnosis of MS) remains a problem in contemporary clinical practice. Studies indicate that misdiagnosed patients are often exposed to prolonged unnecessary health care risks and morbidity. The recently published 2017 revision of the McDonald criteria for the diagnosis of MS provides an opportunity to consider the effect of these revisions on the problem of MS misdiagnosis. The 2017 McDonald criteria include several new recommendations to reduce potential for misdiagnoses. The criteria should be used for the types of patients in which validation studies were performed, specifically those patients who present with typical demyelinating syndromes. MRI lesion characteristics were defined for which McDonald criteria would be expected to perform with accuracy. However, 2017 revisions, which now include assessment for cortical lesions, and the inclusion of symptomatic lesions and positive oligoclonal bands for the fulfillment of diagnostic criteria, may have the potential to lead to misdiagnosis of MS if not applied appropriately. While the 2017 McDonald criteria integrate issues relating to MS misdiagnosis and incorporate specific recommendations for its prevention more prominently than prior criteria, the interpretation of clinical and radiologic assessments upon which these criteria depend will continue to allow misdiagnoses. In patients with atypical clinical presentations, the revised McDonald criteria may not be readily applied. In those situations, further evaluation or monitoring rather than immediate diagnosis of MS is prudent.

The term prodrome often refers to symptoms indicating disease onset before diagnostically specific signs or symptoms emerge. Data from several recent studies have pointed toward a possible prodromal phase of multiple sclerosis (MS).1 These studies have retrospectively identified increased prevalence of symptoms, diagnoses, and health care use in patients years before a new diagnosis of MS.1 An increased prevalence of fatigue, depression, anxiety, headache, sleep disturbances, pain, musculoskeletal disorders, gastrointestinal disorders, and genitourinary disorders, even when patients with diagnoses compatible with concurrent neurologic syndromes were excluded, appeared to precede diagnosis of MS. These data suggest a potential window of opportunity to affect disease trajectory if prodromal symptoms attributable MS could be recognized at the time of onset, or through screening efforts, because earlier treatment is associated with better clinical outcomes. An important limitation of earlier studies was the inclusion of cases reported since the 1980s, when MRI was not available to facilitate earlier diagnosis. The unusually older median age at diagnosis in these investigations indicates that many MS cases escaped early recognition and were diagnosed years later and that reported prodromal symptoms may not have preceded neurologic symptoms diagnostically specific for MS.

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.

Falls are a significant problem for persons with multiple sclerosis (PwMS). Yet fall prevention interventions are not often prescribed until after a fall has been reported to a healthcare provider. While still nascent, objective fall risk assessments could help in prescribing preventative interventions. To this end, retrospective fall status classification commonly serves as an intermediate step in developing prospective fall risk assessments. Previous research has identified measures of gait biomechanics that differ between PwMS who have fallen and those who have not, but these biomechanical indices have not yet been leveraged to detect PwMS who have fallen. Moreover, they require the use of laboratory-based measurement technologies, which prevent clinical deployment. Here we demonstrate that a bidirectional long short-term (BiLSTM) memory deep neural network was able to identify PwMS who have recently fallen with good performance (AUC of 0.88) based on accelerometer data recorded from two wearable sensors during a one-minute walking task. These results provide substantial improvements over machine learning models trained on spatiotemporal gait parameters (21% improvement in AUC), statistical features from the wearable sensor data (16%), and patient-reported (19%) and neurologist-administered (24%) measures in this sample. The success and simplicity (two wearable sensors, only one-minute of walking) of this approach indicates the promise of inexpensive wearable sensors for capturing fall risk in PwMS.

Background and purpose Assess the incidence of enhancing lesions on follow-up MRIs in patients with multiple sclerosis (MS) to determine the utility of intravenous, gadolinium-based contrast agent (IV-GBCA) use in routine follow-up imaging. Methods We retrospectively identified head MRIs associated with an MS diagnosis acquired between January 1, 2015and January 10, 2018. Final reports were reviewed to determine the presence of (1) a new or larger lesion, (2) at least one enhancing lesion, and (3) if at least one enhancing lesion was new or larger on Fluid-Attenuation Inversion Recovery (FLAIR). For MRIs with at least one enhancing lesion, but no new or larger enhancing lesions, reports and images of the preceding MRI were reviewed. Results A total of 1,805 MRIs performed on 920 patients were included. 354/1,805 (20%) MRIs reported new or enlarging lesions. 138/1,805 (8%) MRIs reported at least one enhancing lesion. Of these, 117/138 (85%) reported at least one enhancing lesion that was new or larger. In the remaining 21 MRIs which contained an enhancing lesion but none of the enhancing lesions were reported as new or enlarging, at least one enhancing lesion was present on preceding MRI. Conclusions Enhancing lesions are uncommon on follow-up MRIs in MS patients. Our data suggest that new enhancing lesions are not present on a follow-up MRI when two conditions are met: (1) preceding MRI does not demonstrate any enhancing lesions and (2) there is no interval change of the lesions on the current 3D-T2-FLAIR sequence compared to the preceding 3D-T2-FLAIR sequence. IV-GBCA should be reserved for instances when temporal knowledge of lesion formation is needed.

Background: Misdiagnosis of multiple sclerosis (MS) is common and often occurs due to misattribution of non-MS magnetic resonance imaging (MRI) lesions to MS demyelination. A recently developed MRI biomarker, the central vein sign (CVS), has demonstrated high specificity for MS lesions and may thus help prevent misdiagnosis. Objective: This study explores the potential “real world” diagnostic value of CVS by comparing CVS in patients with MS and patients previously misdiagnosed with MS. Methods: Fifteen patients with MS and 15 misdiagnosed with MS were prospectively recruited to undergo 3T brain MRI. T2-weighted fluid-attenuated inversion recovery (FLAIR) and T2*-weighted segmented echo-planar-imaging (T2*-EPI) were acquired. The generated FLAIR* images were analyzed by two independent raters. The percentage of lesions with CVS was calculated for each patient. Results: A CVS lesion threshold of 29% or higher resulted in high sensitivity (0.79) and specificity (0.88) for MS and correctly identified 87% of patients previously misdiagnosed with MS. Interrater reliability for CVS was high with a Cohen's kappa coefficient of 0.86. Conclusion: This study demonstrates the ability of CVS to differentiate between patients with MS and patients with an MS misdiagnosis resulting from standard MRI and clinical evaluation. Clinical application of CVS may reduce MS misdiagnosis.

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.

Background: The importance of supporting pregnancy-related decisions in multiple sclerosis (MS) patients has increasingly been recognized and hence the need for prospective data on pregnancy and pediatric outcomes in this patient population. Objective: To assess prospective growth and developmental outcomes of infants born to mothers with multiple sclerosis (IMS). Methods: PREG-MS is a prospective multicenter cohort study in New England, United States. We followed 65 women with MS and their infants with up to 12 months consistent pediatric follow-up. Pediatric, neurologic, and demographic information was obtained via structured telephone interviews and validated with medical records. Results: No differences in infant weights and lengths with World Health Organization (WHO) 50th percentile standards were observed ( p > 0.05). However, larger head circumference (HC) measurements than WHO standards were reported in cohort infants ( p Conclusion: This first prospective study on pediatric anthropometry in IMS suggests a possible increase in HC compared to WHO standards without an increase in irreversible developmental abnormalities. The observations are exploratory and require confirmation with larger prospective studies in diverse groups of MS patients.

Background. Most people with multiple sclerosis (MS) want to be involved in medical decision making about disease-modifying therapies (DMTs), but new approaches are needed to overcome barriers to participation. Objectives. We sought to develop a shared decision-making (SDM) tool for MS DMTs, evaluate patient and provider responses to the tool, and address challenges encountered during development to guide a future trial. Methods. We created a patient-centered design process informed by image theory to develop the MS-SUPPORT SDM tool. Development included semistructured interviews and alpha and beta testing with MS patients and providers. Beta testing assessed dissemination and clinical integration strategies, decision-making processes, communication, and adherence. Patients evaluated the tool before and after a clinic visit. Results. MS-SUPPORT combines self-assessment with tailored feedback to help patients identify their treatment goals and preferences, correct misperceptions, frame decisions, and promote adherence. MS-SUPPORT generates a personal summary of their responses that patients can share with their provider to facilitate communication. Alpha testing (14 patients) identified areas needing improvement, resulting in reorganization and shortening of the tool. MS-SUPPORT was highly rated in beta testing (15 patients, 4 providers) on patient-provider communication, patient preparation, adherence, and other endpoints. Dissemination through both patient and provider networks appeared feasible. All patient testers wanted to share the summary report with their provider, but only 60% did. Limitations. Small sample size, no comparison group. Conclusions. The development process resulted in a patient-centered SDM tool for MS that may facilitate patient involvement in decision making, help providers understand their patients’ preferences, and improve adherence, though further testing is needed. Beta testing in real-world conditions was critical to prepare the tool for future testing and inform the design of future studies.

Medication reconciliation (MedRec) is a mission-critical process which can serve to reduce adverse drug events (ADEs) in surgical settings. However, providing quality care is limited by current health information technology (IT), which is often inefficient and unintuitive due to poor usability, resulting in high cognitive burden. We have been characterizing EHR mediated workflow in the Mayo Clinic enterprise prior to a system-wide electronic health records (EHR) conversion in order to harmonize workflows. We compared and evaluated MedRec processes in pre-operative nursing assessments across two different EHRs in place in different locales at baseline. The interfaces differed both in their modes of interaction and cognitive support. Analyses surfaced interface elements that were unintuitive and inefficient, creating unnecessary complexities in clinicians’ interactive behavior. Keystroke level models (KLM), a modeling tool for predicting task completion time, showed that to access medication lists required a different series of operations across the two systems. Different designs can differentially mediate task performance, which can aid in the mitigation of errors for complex cognitive tasks. Identification of barriers in EHR-mediated workflow and barriers to interface usability could lead to system redesigns that minimize cognitive load while improving patient safety and efficiency.

Background: Detection of a “central vein sign” (CVS) on FLAIR* magnetic resonance imaging (MRI) is highly specific and sensitive for multiple sclerosis (MS). We evaluated the specificity and sensitivity of simplified CVS algorithms for MS diagnosis. Methods: MRIs from 10 participants with MS without additional comorbidities for MRI white matter abnormalities; 10 with MS and additional comorbidities for white matter abnormalities; 10 with migraine, white matter abnormalities, and no additional comorbidities; and 10 who had previously been erroneously diagnosed with MS were evaluated. 3T MRI T2-FLAIR and T2*-weighted sequences were acquired to create FLAIR* images. Three MS physician reviewers, blinded to diagnosis, evaluated two different algorithms: (1) three lesions pre-selected on FLAIR were subsequently evaluated for CVS on FLAIR*( select3). (2) FLAIR* was evaluated for up to three lesions with CVS ( select3*). Results: For select3, average specificity across reviewers for MS was 0.98 and sensitivity 0.52 and a correct prediction of diagnosis demonstrated kappa = 0.29. For select3*, specificity was 0.81, sensitivity was 0.83, and kappa was 0.31. Conclusion: A simplified determination of CVS in three white matter lesions on 3T FLAIR* MRI demonstrated good specificity and sensitivity and fair inter-rater reliability for a diagnosis of MS and with further study, may be a candidate for clinical application.

The benefits of early treatment for multiple sclerosis (MS) place pressure on physicians to make the diagnosis early, thereby increasing the risk of misdiagnosis, which can have considerable consequences for patients and health-care systems. Solomon and Corboy examine the problem of MS misdiagnosis, including the probable causes and associated risks, and discuss how the tension between early diagnosis and misdiagnosis might be addressed. Diagnosis of multiple sclerosis (MS) can be challenging, and misdiagnosis remains a persistent problem with considerable consequences for patients and health-care systems. Common syndromes are frequently mistaken for MS. Misapplication of MS diagnostic criteria in patients with abnormal radiographic findings and clinical presentations that are atypical for MS is a frequent cause of misdiagnosis. Delays in diagnosis of MS and initiation of disease-modifying therapy (DMT) are associated with an increased risk of disability, putting pressure on physicians to make therapeutic decisions for patients whose diagnosis remains uncertain. DMT is associated with unnecessary risks and morbidity in misdiagnosed patients. This tension between the benefits of an early diagnosis and the risk of misdiagnosis is a pressing problem. For patients who present with brain MRI abnormalities and clinical syndromes that are atypical for MS, strict adherence to MS diagnostic criteria and further clinical, laboratory and radiographic evaluation is prudent and likely to clarify a diagnosis.

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

Summary A great deal of neuroimaging research focuses on voxel-wise analysis or segmentation of damaged tissue, yet many diseases are characterized by diffuse or non-regional neuropathology. In simple cases, these processes can be quantified using summary statistics of voxel intensities. However, the manifestation of a disease process in imaging data is often unknown, or appears as a complex and nonlinear relationship between the voxel intensities on various modalities. When the relevant pattern is unknown, summary statistics are often unable to capture differences between disease groups, and their use may encourage post hoc searches for the optimal summary measure. In this study, we introduce the multi-modal density testing (MMDT) framework for the naive discovery of group differences in voxel intensity profiles. MMDT operationalizes multi-modal magnetic resonance imaging (MRI) data as multivariate subject-level densities of voxel intensities and utilizes kernel density estimation to develop a local two-sample test for individual points within the density space. Through simulations, we show that this method controls type I error and recovers relevant differences when applied to a specified point. Additionally, we demonstrate the ability to maintain power while controlling the family-wise error rate and false discovery rate when applying the test over a grid of points within the density space. Finally, we apply this method to a study of subjects with either multiple sclerosis (MS) or conditions that tend to mimic MS on MRI, and find significant differences between the two groups in their voxel intensity profiles within the thalamus.