Objective To describe clinical and radiologic features associated with myelin oligodendrocyte glycoprotein antibodies (MOG-Ab) in a large French nationwide adult cohort, to assess baseline prognostic features of MOG-Ab-associated diseases after a first acute demyelinating syndrome, and to evaluate the clinical value of MOG-Ab longitudinal analysis. Methods Clinical data were obtained from 197 MOG-Ab-positive patients ≥18 years of age. Complete imaging data were available in 108, and 54 serum samples were eligible for longitudinal evaluation. For survival analysis comparison, 169 aquaporin-4 antibody (AQP4-Ab)-positive patients from the NOMADMUS database were included. Results Median age at onset was 36.46 (range 18.0–76.8) years, and patients were predominantly white (92.9%) with male:female ratio, 1.1. Clinical phenotype at onset included optic neuritis or myelitis in 90.86%, isolated brainstem or encephalopathy syndromes in 6.6%, and a combination of syndromes in 2.5%. Distinctive brain MRI findings in MOG-Ab-positive patients were thalamic and pontine lesions. Cortical and leptomeningeal lesions were found in 16.3% and 6.1%, respectively. The probability of reaching a first relapse after 2 and 5 years was 44.8% and 61.8%, respectively. MOG-Ab-positive patients were at lower risk at presentation of further clinical relapse (hazard ratio [HR] 0.45, 95% confidence interval [CI] 0.26–0.79) compared to AQP4-Ab-positive individuals. MOG-Ab-positive individuals had a lower risk of reaching Disability Status Scale score of 3.0 (HR 0.46, 95% CI 0.22–0.94) and visual acuity of 20/100 (HR 0.23, 95% CI 0.07–0.72). Finally, MOG-Ab titers were higher at relapse than in remission (p = 0.009). Conclusion In adults, MOG-Ab-associated disease extends beyond clinical and radiologic abnormalities in the optic nerve and spinal cord. Despite the relapsing course, the overall visual and motor outcome is better compared with AQP4-Ab-positive patients.

Background Brain MRI parenchymal signal abnormalities have been in association with SARS-CoV-2. Purpose Describe the neuroimaging findings (excluding ischemic infarcts) in patients with severe COVI...

We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and independent evaluation of a large range of algorithms in a fair and completely automatic manner. This computing infrastructure was used to evaluate thirteen methods of MS lesions segmentation, exploring a broad range of state-of-theart algorithms, against a high-quality database of 53 MS cases coming from four centers following a common definition of the acquisition protocol. Each case was annotated manually by an unprecedented number of seven different experts. Results of the challenge highlighted that automatic algorithms, including the recent machine learning methods (random forests, deep learning, …), are still trailing human expertise on both detection and delineation criteria. In addition, we demonstrate that computing a statistically robust consensus of the algorithms performs closer to human expertise on one score (segmentation) although still trailing on detection scores.

Background: One of the diagnostic imaging hallmarks of MS is the uptake of IV administered contrast material in new lesions in the brain, signaling blood–brain barrier breakdown and active inflammation. Many clinical drug trials are designed based on the assumption that lesion enhancement on MRI remains visible on average for 1 month. For practical reasons, few serial MRI studies of patients with MS have been performed at intervals shorter than 4 weeks. Methods: The authors performed a year-long longitudinal study in 26 patients with relapsing-remitting MS (RRMS), which comprised an initial phase of MRI follow-up at weekly intervals for 8 weeks, followed by imaging every other week for another 16 weeks, and monthly thereafter. They present a quantitative analysis (using a supervised interactive thresholding procedure) of new enhancing lesions appearing during the first 6 weeks in this cohort and evaluated from the time of first detection until enhancement was no longer seen. Results: The average duration of Gd-DTPA enhancement in individual new lesions was 3.07 weeks (median, 2 weeks). Significant correlations were demonstrated between the duration of contrast enhancement or initial growth rates and lesion volumes. Different lesions in the same patient appeared to develop largely independent of each other and demonstrated a large range in the duration of enhancement during the acute phase of their evolution. Conclusions: The average duration of blood–brain barrier impairment in RRMS is shorter than earlier estimates. Early lesion growth parameters may predict final lesion size. Within-patient heterogeneity of lesion evolution suggests that individual lesions develop independently.

Objective To describe neuroimaging findings and to report the epidemiologic and clinical characteristics of patients with coronavirus disease 2019 (COVID-19) with neurologic manifestations. Methods In this retrospective multicenter study (11 hospitals), we included 64 patients with confirmed COVID-19 with neurologic manifestations who underwent a brain MRI. Results The cohort included 43 men (67%) and 21 women (33%); their median age was 66 (range 20–92) years. Thirty-six (56%) brain MRIs were considered abnormal, possibly related to severe acute respiratory syndrome coronavirus. Ischemic strokes (27%), leptomeningeal enhancement (17%), and encephalitis (13%) were the most frequent neuroimaging findings. Confusion (53%) was the most common neurologic manifestation, followed by impaired consciousness (39%), presence of clinical signs of corticospinal tract involvement (31%), agitation (31%), and headache (16%). The profile of patients experiencing ischemic stroke was different from that of other patients with abnormal brain imaging: the former less frequently had acute respiratory distress syndrome (p = 0.006) and more frequently had corticospinal tract signs (p = 0.02). Patients with encephalitis were younger (p = 0.007), whereas agitation was more frequent for patients with leptomeningeal enhancement (p = 0.009). Conclusions Patients with COVID-19 may develop a wide range of neurologic symptoms, which can be associated with severe and fatal complications such as ischemic stroke or encephalitis. In terms of meningoencephalitis involvement, even if a direct effect of the virus cannot be excluded, the pathophysiology seems to involve an immune or inflammatory process given the presence of signs of inflammation in both CSF and neuroimaging but the lack of virus in CSF. ClinicalTrials.gov identifier NCT04368390.