Identification and measurement of cervical spinal cord atrophy in neuromyelitis optica spectrum disorders (NMOSD) and correlation with clinical characteristics and cervical spinal cord MRI data

Serum neurofilament light chain predicts spinal cord atrophy in neuromyelitis optica spectrum disorder

Levels of serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are useful biomarkers of disease activity and disability in neuromyelitis optica spectrum disorder (NMOSD). Here we investigated the association of sNfL and sGFAP levels with brain and spinal cord volumes in patients with NMOSD. Fifteen patients with NMOSD were enrolled in this prospective study. The median baseline level of sNfL was 42.2 (IQR, 16.1-72.6) pg/mL and decreased to 8.5 (IQR, 7.4-16.6) pg/mL at the end of the study. The reduction in sNfL was associated with a 7.5% loss of cervical spinal cord volume (CSCV) (p = 0.001). The levels of sGFAP reduced from 239.2 (IQR, 139.0-3393.3) pg/mL at baseline to 108.5 (IQR, 74.2-154.6) pg/mL. However, there was no strong correlation between sGFAP levels and CSCV changes during the follow-up period. Our data suggested that sNfL level is a useful biomarker for predicting spinal cord atrophy in patients with NMOSD.

Correlation of IgH-CDR3 Immune Repertoire Diversity Test in Peripheral Blood of Neuromyelitis Spectrum Diseases

Neuroretinitis spectrum disorder (NMOSD) is generally regarded as an acute or subacute inflammatory demyelinating disease of the central nervous system, mainly involving the optic nerve and spinal cord, mediated by humoral immunity. To address these questions, this work established an immunomic library of the heavy chain complementarity determinant 3 (gHI-CDR3) of peripheral blood lymphocyte B cell receptors. The library was established in patients with a spectrum of neurosyphilis-retinitis disorders. Six NMOSD patients and six healthy volunteers were recruited, and the NMOSD group was divided into an early-onset group and a stable group according to treatment conditions. The IgH-CDR3 gene fragment cultured in vitro was amplified by multiplex PCR technology, and the gene was sequenced by the second-generation high-throughput sequencing technology, and the statistical analysis was carried out by the method without reference. The quantity, type, and diversity of IgH-CDR3 in peripheral blood B lymphocytes of NMOSD patients were significantly lower than those of normal group (P > 0.05); the variation of IgH-CDR3 sequence in the initial stage of treatment was higher than that in the stable stage (P > 0.05); the replication frequency of the characteristic gene "CASSICLGSGCGGYYYGMDVW" was significantly increased in patients at the initial stage of NMOSD treatment (P < 0.05). The conclusion was that the gene expression and gene expression analysis of NMOSD patients could accurately judge the condition of NMOSD patients, evaluate their efficacy, and provide new molecular targets and new theoretical basis for clinical application.

Evolution of Neuroimaging Findings in Severe COVID-19 Patients with Initial Neurological Impairment: An Observational Study

BACKGROUND AND OBJECTIVES

Cerebral complications related to the COVID-19 were documented by brain MRIs during the acute phase. The purpose of the present study was to describe the evolution of these neuroimaging findings (MRI and FDG-PET/CT) and describe the neurocognitive outcomes of these patients.

METHODS

During the first wave of the COVID-19 outbreak between 1 March and 31 May 2020, 112 consecutive COVID-19 patients with neurologic manifestations underwent a brain MRI at Strasbourg University hospitals. After recovery, during follow-up, of these 112 patients, 31 (initially hospitalized in intensive care units) underwent additional imaging studies (at least one brain MRI).

RESULTS

Twenty-three men (74%) and eight women (26%) with a mean age of 61 years (range: 18-79) were included. Leptomeningeal enhancement, diffuse brain microhemorrhages, acute ischemic strokes, suspicion of cerebral vasculitis, and acute inflammatory demyelinating lesions were described on the initial brain MRIs. During follow-up, the evolution of the leptomeningeal enhancement was discordant, and the cerebral microhemorrhages were stable. We observed normalization of the vessel walls in all patients suspected of cerebral vasculitis. Four patients (13%) demonstrated new complications during follow-up (ischemic strokes, hypoglossal neuritis, marked increase in the white matter FLAIR hyperintensities with presumed vascular origin, and one suspected case of cerebral vasculitis). Concerning the grey matter volumetry, we observed a loss of volume of 3.2% during an average period of approximately five months. During follow-up, the more frequent FDG-PET/CT findings were hypometabolism in temporal and insular regions.

CONCLUSION

A minority of initially severe COVID-19 patients demonstrated new complications on their brain MRIs during follow-up after recovery.

Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants

•

Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy.

•

Simulate spinal cord atrophy and scan-rescan variability.

•

Fully automated analysis method available on an open access database.

•

Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.

Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases. It is measured by segmenting the spinal cord on an MRI image and computing the average cross-sectional area (CSA) over a few slices. Introduced about 25 years ago, this procedure is highly sensitive to the quality of the segmentation and is prone to rater-bias. Recently, fully-automated spinal cord segmentation methods, which remove the rater-bias and enable the automated analysis of large populations, have been introduced. A lingering question related to these automated methods is: How reliable are they at detecting atrophy? In this study, we evaluated the precision and accuracy of automated atrophy measurements by simulating scan-rescan experiments.

Spinal cord MRI data from the open-access spine-generic project were used. The dataset aggregates 42 sites worldwide and consists of 260 healthy subjects and includes T1w and T2w contrasts. To simulate atrophy, each volume was globally rescaled at various scaling factors. Moreover, to simulate patient repositioning, random rigid transformations were applied. Using the DeepSeg algorithm from the Spinal Cord Toolbox, the spinal cord was segmented and vertebral levels were identified. Then, the average CSA between C3-C5 vertebral levels was computed for each Monte Carlo sample, allowing us to derive measures of atrophy, intra/inter-subject variability, and sample-size calculations.

The minimum sample size required to detect an atrophy of 2% between unpaired study arms, commonly seen in MS studies, was 467 +/− 13.9 using T1w and 467 +/− 3.2 using T2w images. The minimum sample size to detect a longitudinal atrophy (between paired study arms) of 0.8% was 60 +/− 25.1 using T1w and 10 +/− 1.2 using T2w images. At the intra-subject level, the estimated CSA, observed in this study, showed good precision compared to other studies with COVs (across Monte Carlo transformations) of 0.8% for T1w and 0.6% for T2w images.

While these sample sizes seem small, we would like to stress that these results correspond to a “best case” scenario, in that the dataset used here was of particularly good quality and the model for simulating atrophy does not encompass all the variability met in real-life datasets. The simulated atrophy and scan-rescan variability may over-simplify the biological reality. The proposed framework is open-source and available at https://csa-atrophy.readthedocs.io/.