A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis.

BACKGROUND: The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE: The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS: Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS: Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION: A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.

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.

Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis.

BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.

The prevalence of radiological cerebral amyloid angiopathy-related inflammation in patients with cerebral amyloid angiopathy.

OBJECTIVES: Cerebral amyloid angiopathy (CAA) related inflammation (CAA-RI) is an autoimmune inflammatory condition occurring in patients with CAA. We aimed to determine the prevalence of radiological CAA-RI amongst patients with CAA and to describe their presenting clinical features. METHODS: We performed a retrospective review of electronic medical records across multiple centers within a single healthcare network. Patients who met radiological modified Boston 2.0 criteria for CAA and had white matter hyperintensity (WMH) were included. Scans were analyzed by a vascular neurologist and confirmed by a neuroradiologist blinded to clinical information for meeting criteria for possible or probable radiographic CAA-RI. RESULTS: Out of 1100 patients reviewed, 511 patients met radiological modified Boston criteria for CAA and 193 patients had WMH on MRI. A total of 55 (28.5 % of those with CAA and WMH, and 10.8 % of all CAA with or without WMH) patients had MRI brain imaging suggestive of possible or probable radiographic CAA-RI. The diagnosis of CAA-RI was reported in only 10 (18.2 %) patients initially while 20 (36.4 %) were diagnosed up to 74 months later (median 0, IQR 0-9 months). At the time of earliest probable CAA-RI findings on imaging, the most common concurrent findings were cognitive impairment (74.5 %), macro-hemorrhages (52.7 %), headache (30.9 %), seizures (14.5 %), and ischemic infarcts (14.5 %). Only 18 (32.7 %) patients were treated with immunosuppression. CONCLUSIONS: The prevalence of radiographic CAA-RI was high, and most cases were unrecognized and untreated. Further studies are needed to assess if earlier detection and treatment of radiologic CAA-RI may halt disease progression and prevent cognitive decline in these patients.

Personalized model to predict seizures based on dynamic and static continuous EEG monitoring data.

BACKGROUND/OBJECTIVE: Early recognition of patients who may be at risk of developing acute symptomatic seizures would be useful. We aimed to determine whether continuous electroencephalography (cEEG) data using machine learning techniques such as neural networks and decision trees could predict seizure occurrence in hospitalized patients. METHODS: This was a single center retrospective cohort analysis of cEEG data in patients aged 18-90 years who were admitted and underwent cEEG monitoring between 2010 and 2019 limited to 72 h excluding those who were seizing at the onset of recording. A total of 41,491 patients were reviewed; of these, 3874 were used to develop the static model and 1687 to develop the dynamic model (half with seizure and half without seizure in each cohort). Of these, 80% were randomly selected as derivation cohorts for each model and 20% were randomly selected as validation cohorts. Dynamic and static machine learning models (long short term memory (LSTM) and Extreme Gradient Boosting algorithm (XGBoost)) based on day-to-day dynamic EEG changes and binary static EEG features over the prior 72 h or until seizure, which ever was earlier, were used. RESULTS: The static model was able to predict seizure occurrence based on cEEG data with sensitivity and specificity of 0.81 and 0.59, respectively, with an AUC of 0.70. The dynamic model was able to predict seizure occurrence with sensitivity and specificity of 0.72 and 0.80, respectively, and AUC of 0.81. CONCLUSIONS: Machine learning models could be applied to cEEG data to predict seizure occurrence based on available cEEG data. Dynamic day-to-day EEG data are more useful in predicting seizures than binary static EEG data. These models could potentially be used to determine the need for ongoing cEEG monitoring and to prioritize resources.

Does Targeted Temperature Management Improve Neurological Outcome in Extracorporeal Cardiopulmonary Resuscitation (ECPR)?

PURPOSE: Targeted temperature management (TTM) is a standard of care in patients after cardiac arrest for neuroprotection. Currently, the effectiveness and efficacy of TTM after extracorporeal cardiopulmonary resuscitation (ECPR) is unknown. We aimed to compare neurological and survival outcomes between TTM vs non-TTM in patients undergoing ECPR for refractory cardiac arrest. METHODS: We searched PubMed and 5 other databases for randomized controlled trials and observational studies reporting neurological outcomes or survival in adult patients undergoing ECPR with or without TTM. Good neurological outcome was defined as cerebral performance category <3. Two independent reviewers extracted the data. Random-effects meta-analyses were used to pool data. RESULTS: We included 35 studies (n = 2,643) with the median age of 56 years (interquartile range [IQR]: 52-59). The median time from collapse to ECMO cannulation was 58 minutes (IQR: 49-82) and the median ECMO duration was 3 days (IQR: 2.0-4.1). Of 2,643, 1,329 (50.3%) patients received TTM and 1,314 (49.7%) did not. There was no difference in the frequency of good neurological outcome at any time between TTM (29%, 95% confidence interval [CI]: 23%-36%) vs. without TTM (19%, 95% CI: 9%-31%) in patients with ECPR (P = 0.09). Similarly, there was no difference in overall survival between patients with TTM (30%, 95% CI: 22%-39%) vs. without TTM (24%, 95% CI: 14%-34%) (P = 0.31). A cumulative meta-analysis by publication year showed improved neurological and survival outcomes over time. CONCLUSIONS: Among ECPR patients, survival and neurological outcome were not different between those with TTM vs. without TTM. Our study suggests that neurological and survival outcome are improving over time as ECPR therapy is more widely used. Our results were limited by the heterogeneity of included studies and further research with granular temperature data is necessary to assess the benefit and risk of TTM in ECPR population.

Determination of Brain Death in Patients Undergoing Short-Term Mechanical Circulatory Support Devices.

OBJECTIVE: To describe apnoea test (AT) and ancillary study performance for brain death (BD) determination among patients undergoing short-term mechanical circulatory support (MCS) devices, including extracorporeal membrane oxygenation (ECMO) and intra-aortic balloon pump (IABP). METHODS: We retrospectively analysed data regarding use of AT and ancillary study in consecutive adult patients who were diagnosed with BD while on MCS devices (including ECMO and IABP) over a 10-year period. RESULTS: Out of 140 patients, eight were on MCS devices at the time of BD (four ECMO, two ECMO and IABP, two IABP). The most common aetiology of BD was hypoxic ischaemic brain injury (6/8, 75%). In four patients (50%), the AT was not attempted because of haemodynamic instability and ECMO; in the remaining four (50%), both AT and ancillary studies were used. In three patients on ECMO, AT was performed by reducing the ECMO sweep flow rate to a range 0.5-2.7 L/min in order to achieve hypercarbia. One patient underwent AT while on IABP which was complicated by hypotension. All patients underwent ancillary tests, most commonly transcranial Doppler ultrasonography (TCD) (7/8, 88%); among those, cerebral circulatory arrest was confirmed in six of seven patients (86%), all of whom had left ventricular ejection fracture (LVEF) ≥20% and/or were supported with IABP. CONCLUSIONS: There are multiple uncertainties regarding BD diagnosis while on MCS, prompting the need for ancillary studies in most patients. Our study shows that TCD can be used to support BD diagnosis in patients on ECMO who have sufficient cardiac contractility and/or IABP to produce pulsatile flow. TCD use in ECMO patients low LVEF needs further study.

Outcomes, Time-Trends, and Factors Associated With Ancillary Study Use for the Determination of Brain Death.

OBJECTIVES: Brain death determination often requires ancillary studies when clinical determination cannot be fully or safely completed. We aimed to analyze the results of ancillary studies, the factors associated with ancillary study performance, and the changes over time in number of studies performed at an academic health system. DESIGN: Retrospective cohort. SETTING: Multihospital academic health system. PATIENTS: Consecutive adult patients declared brain dead between 2010 and 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 140 brain death patients, ancillary studies were performed in 84 (60%). The false negative rate of all ancillary studies was 4% (5% of transcranial Doppler ultrasounds, 4% of nuclear studies, 0% of electroencephalograms, and 17% of CT angiography). In univariate analysis, ancillary study use was associated with female sex (odds ratio, 2.4; 95% CI, 1.21-5.01; p = 0.013) and the etiology of brain death being hypoxic-ischemic brain injury (odds ratio, 2.9; 95% CI, 1.43-5.88; p = 0.003), nontraumatic intracranial hemorrhage (odds ratio, 0.45; 95% CI, 0.21-0.96; p = 0.039), or traumatic brain injury (odds ratio, 0.22; 95% CI, 0.04-0.8; p = 0.031). In multivariable analysis, female sex (odds ratio, 5.7; 95% CI, 2.56-15.86; p = 0.004), the etiology of brain death being hypoxic-ischemic brain injury (odds ratio, 3.2; 95% CI, 1.3-8.8; p = 0.015), and the neurologists performing brain death declaration (odds ratio, 0.08; 95% CI, 0.004-0.64; p = 0.034) were factors independently associated with use of ancillary studies. Over the study period, the total number of ancillary studies performed each year did not significantly change; however, the number of electroencephalograms significantly decreased with time (odds ratio per 1-yr increase, 0.67; 95% CI, 0.49-0.90; p = 0.014). CONCLUSIONS: A large number of ancillary studies were performed despite a clinical determination of brain death; patients with hypoxic-ischemic brain injury are more likely to undergo ancillary studies for brain death determination, and neurologists were less likely to use ancillary studies for brain death. Recently, the use of electroencephalograms for brain death determination has decreased, likely reflecting significant concerns regarding its validity and reliability.

Juxtacortical susceptibility changes in progressive multifocal leukoencephalopathy at the gray-white matter junction correlates with iron-enriched macrophages.

OBJECTIVE: Describe magnetic resonance imaging (MRI) susceptibility changes in progressive multifocal leukoencephalopathy (PML) and identify neuropathological correlates. METHODS: PML cases and matched controls with primary central nervous system lymphoma (PCNSL) were retrospectively identified. MRI brain at 3 T and 7 T were reviewed. MRI-pathology correlations in fixed brain autopsy tissue were conducted in three subjects with confirmed PML. RESULTS: With PML (n = 26 total, n = 5 multiple sclerosis natalizumab-associated), juxtacortical changes on susceptibility-weighted imaging (SWI) or gradient echo (GRE) sequences were noted in 3/3 cases on 7 T MRI and 14/22 cases (63.6%) on 1.5 T or 8/22 (36.4%) 3 T MRI. Similar findings were only noted in 3/25 (12.0%) of PCNSL patients (odds ratio (OR) 12.83, 95% confidence interval (CI), 2.9-56.7, p < 0.001) on 1.5 or 3 T MRI. On susceptibility sequences available prior to diagnosis of PML, 7 (87.5%) had changes present on average 2.7 ± 1.8 months (mean ± SD) prior to diagnosis. Postmortem 7 T MRI showed SWI changes corresponded to areas of increased iron density along the gray-white matter (GM-WM) junction predominantly in macrophages. CONCLUSION: Susceptibility changes in PML along the GM-WM junction can precede noticeable fluid-attenuated inversion recovery (FLAIR) changes and correlates with iron accumulation in macrophages.

Current perspectives of mi-RNA in oesophageal adenocarcinoma: Roles in predicting carcinogenesis, progression and values in clinical management.

Aberrant expressions of micro-ribonucleic acids (miRs) are closely associated with the pathogenesis in many human cancers. In oesophageal adenocarcinomas, altered expressions of different sets of miRs are noted to be associated with the development of adenocarcinoma from Barrett's oesophagus. In different studies, miRs such as miR-192, miR-196 and miR-21 were frequently noted to up-regulated whereas miR-203, miR-205 and miR-let-7 were commonly down-regulated during the development of Barrett's oesophagus to oesophageal adenocarcinoma. In addition, changes in the expression of miRs are associated with the predication of metastasis, prognosis and response to chemo-radiation in the patients with oesophageal adenocarcinoma. Experimental studies in manipulating the miRs in cancer cell lines could provide hints for therapeutics for the cancer. However, the number of studies reported on these aspects of oesophageal adenocarcinoma was limited and the miRs noted needed to be confirmed by additional studies. Overall, the mechanisms of involvements of miRs in pathogenesis and progression of oesophageal adenocarcinoma are complex. Although miRs have the potential to act as prognostic and clinical biomarkers for cancer therapy in oesophageal adenocarcinoma, more works in larger populations and clinical trials are needed to validate these clinical implications.

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.

Drugs Targeting CD20 in Multiple Sclerosis: Pharmacology, Efficacy, Safety, and Tolerability.

Currently, there are four monoclonal antibodies (mAbs) that target the cluster of differentiation (CD) 20 receptor available to treat multiple sclerosis (MS): rituximab, ocrelizumab, ofatumumab, and ublituximab. B-cell depletion therapy has changed the therapeutic landscape of MS through robust efficacy on clinical manifestations and MRI lesion activity, and the currently available anti-CD20 mAb therapies for use in MS are a cornerstone of highly effective disease-modifying treatment. Ocrelizumab is currently the only therapy with regulatory approval for primary progressive MS. There are currently few data regarding the relative efficacy of these therapies, though several clinical trials are ongoing. Safety concerns applicable to this class of therapeutics relate primarily to immunogenicity and mechanism of action, and include infusion-related or injection-related reactions, development of hypogammaglobulinemia (leading to increased infection and malignancy risk), and decreased vaccine response. Exploration of alternative dose/dosing schedules might be an effective strategy for mitigating these risks. Future development of biosimilar medications might make these therapies more readily available. Although anti-CD20 mAb therapies have led to significant improvements in disease outcomes, CNS-penetrant therapies are still needed to more effectively address the compartmentalized inflammation thought to play an important role in disability progression.

Association Between Disease-Modifying Therapy and Information Processing Speed in Multiple Sclerosis.

BACKGROUND: Cognitive impairment (CI) is common in multiple sclerosis (MS). Processing speed (PS) is often affected, making it an ideal target for monitoring CI. This study aims to evaluate the association between disease-modifying therapy (DMT) use and intensity and longitudinal changes in Processing Speed Test (PST) scores for individuals with MS. METHODS: A retrospective analysis of individual PST scores at a single MS center was conducted. Individuals with 2 or more PST assessments were included. Scores on the PST were compared longitudinally between those who had been on a DMT for 2 or more years and those who had been off a DMT for 2 or more years and between those on high-efficacy DMTs and those on low-/moderate-efficacy DMTs. A linear regression model was approximated to evaluate the rate of cognitive change over time. A propensity score adjustment was conducted using a multivariable logistic regression. RESULTS: The cohort was 642 individuals, 539 on DMT and 103 off DMT. Median age and disease duration was 49.7 (IQR 42.4-57.9) and 16.6 years (IQR 9.3-23.0) in the DMT group, and 58.9 (IQR 52.2-65.3) and 20.0 years (IQR 14.1-31.4) in the non-DMT group. Both cohorts were predominantly female (75% DMT, 79.6% non-DMT), with a mean of 4 assessments (IQR 3-5), and an average monitoring duration of 1.9 years (1.2-2.4) in the DMT group, and 1.8 years (1.4-2.4) in the non-DMT group. After adjusting for multiple factors, DMT status and intensity were not found to be significant predictors of longitudinal PST change. CONCLUSIONS: Neither DMT status nor intensity was a significant predictor of cognitive processing speed over a period of approximately 2 years. Future prospective studies are needed to further support these findings.

Associations Between Cognitive Impairment and Neuroimaging in Patients with Multiple Sclerosis.

OBJECTIVE: Multiple sclerosis (MS) is a debilitating inflammatory and neurodegenerative disease which commonly involves cognitive dysfunction. Magnetic resonance imaging (MRI) studies have shown that patients with MS (pwMS) have diffuse patterns of brain atrophy, however, the relationship between the presentation of cognitive dysfunction and brain tissue loss remains understudied. Given the integral function of thalamus as a central nervous system relay center and its involvement in various brain circuits, thalamic atrophy may play a key role in the development and progression of cognitive dysfunction. The purpose of this study is to examine the relationship between cognitive impairment in pwMS and thalamic atrophy. METHODS: A total of 121 pwMS who had neuropsychological testing and quantitative MRI within 1 year of each were retrospectively identified. Grouped LASSO linear regression with 10-fold cross validation was used to estimate each neuropsychological test score with thalamic volume as the focal predictor and all other demographic and MRI metrics as covariates. RESULTS: Rates of impairment ranged from 19% to 44%. Results showed notable associations between thalamic volume and Symbol Digit Modalities Test (ß = 0.11), Brief Visuospatial Memory Test, delayed (ß = 0.12), California Verbal Learning Test, delayed and total (ß = 0.24 and ß = 0.15 respectively), and Trail Making Test Part A (ß = -0.01), after adjusting for covariates. CONCLUSIONS: These findings demonstrate an independent association between thalamic volumes and processing speed and memory performance, after accounting for demographic, clinical, and other MRI variables, among pwMS.

Updates and advances in multiple sclerosis neurotherapeutics.

The multiple sclerosis (MS) neurotherapeutic landscape is rapidly evolving. New disease-modifying therapies (DMTs) with improved efficacy and safety, in addition to an expanding pipeline of agents with novel mechanisms, provide more options for patients with MS. While treatment of MS neuroinflammation is well tailored in the existing DMT armamentarium, concerted efforts are currently underway for identifying neuropathological targets and drug discovery for progressive MS. There is also ongoing research to develop agents for remyelination and neuroprotection. Further insights are needed to guide DMT initiation and sequencing as well as to determine the role of autologous stem cell transplantation in relapsing and progressive MS. This review provides a summary of these updates.

The range of treatment options available for multiple sclerosis (MS) is growing, with the aim of developing safer and more effective therapies. There are ongoing efforts to discover additional mechanisms of MS and create drugs that can target these pathways. A more tailored approach will allow better personalization of drug selection for patients. There is currently a special focus on identifying treatment targets for progressive MS, where there are only a limited number of therapeutic options available to date. In addition, there is ongoing research aimed at developing stem cell therapies, drugs that provide neuroprotection and agents that can potentially reverse the damage caused by MS through remyelination. In this review, these topics are summarized.

Central Nervous System Vasculitis: Primary Angiitis of the Central Nervous System and Central Nervous System Manifestations of Systemic Vasculitis.

Central nervous system vasculitis (CNSV) is a group of disorders leading to inflammatory vasculopathy within the brain, spinal cord, and leptomeninges. CNSV is divided into primary angiitis of the central nervous system (PACNS) and secondary CNSV based on the underlying etiology. PACNS is a rare inflammatory disorder with poorly understood pathophysiology and heterogeneous and highly variable clinical features. The diagnosis depends on a combination of clinical and laboratory variables, multimodal imaging, and histopathological examination as well as exclusion of mimics. Several systemic vasculitides, infectious etiologies and connective tissue disorders have been shown to cause secondary CNSV and require prompt recognition.

Pearls & Oy-sters: Mitral Annular Calcification as a Cause of Ischemic Stroke: A Case Report.

Evaluation of stroke etiology is an important aspect of stroke care affecting secondary prevention measures. Despite recent advances in diagnostic testing, determining the stroke etiology can remain a challenging task particularly for less common causes of stroke such as mitral annular calcification. This case will review the benefit of histopathologic clot evaluation after thrombectomy to identify uncommon causes of embolic stroke which may change management.

Pearls & Oy-sters: Hemorrhagic Myelitis Following SARS-CoV-2 Infection.

Hemorrhage in the setting of myelitis is rarely seen in clinical practice. We report a series of 3 women aged 26, 43, and 44 years, who presented with acute hemorrhagic myelitis within 4 weeks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Two required intensive care, and 1 had severe disease with multiorgan failure. Serial MRI of the spine demonstrated T2-weighted hyperintensity with T1-weighted postcontrast enhancement in the medulla and cervical spine (patient 1) and thoracic spine (patients 2 and 3). Hemorrhage was identified on precontrast T1-weighted, susceptibility-weighted, and gradient echo sequences. Distinct from typical inflammatory or demyelinating myelitis, clinical recovery was poor in all cases, with residual quadriplegia or paraplegia, despite immunosuppression. These cases highlight that although hemorrhagic myelitis is rare, it can occur as a post/parainfectious complication of SARS-CoV-2 infection.

New diagnosis of multiple sclerosis in the setting of mRNA COVID-19 vaccine exposure.

BACKGROUND: Multiple sclerosis (MS) with onset in the setting of acute SARS-CoV-2 virus infection has been reported, and reactivation of MS following non-mRNA COVID-19 vaccination has been noted, but there have only been three reports of newly diagnosed MS following exposure to mRNA COVID-19 vaccine. The association cannot be determined to be causal, as latent central nervous system demyelinating disease may unmask itself in the setting of an infection or a systemic inflammatory response. We report a series of 5 cases of newly diagnosed MS following recent exposure to mRNA COVID-19 vaccines. Latency from vaccination to initial presentation varied. Neurological manifestations and clinical course appeared to be typical for MS including response to high dose steroids in 4 cases and additional need for plasmapheresis in one case. CONCLUSION: Acute neurological deficits in the setting of recent mRNA COVID-19 vaccine administration may represent new onset multiple sclerosis.

Prediction in treatment outcomes in multiple sclerosis: challenges and recent advances.

INTRODUCTION: Multiple Sclerosis (MS) is a chronic autoimmune and neurodegenerative disease of the central nervous system with a course dependent on early treatment response. Increasing evidence also suggests that despite eliminating disease activity (relapses and lesions), many patients continue to accrue disability, highlighting the need for a more comprehensive definition of treatment success. Optimizing disability outcome measures, as well as continuously improving our understanding of neuroinflammatory and neurodegenerative biomarkers is required. AREAS COVERED: This review describes the challenges inherent in classifying and monitoring disease phenotype in MS. The review also provides an assessment of clinical, radiological, and blood biomarker tools for current and future practice. EXPERT OPINION: Emerging MRI techniques and standardized patient outcome assessments will increase the accuracy of initial diagnosis and understanding of disease progression.