Demortière, Sarah

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Abstract Anti-IgLON5 disease is an autoimmune encephalitis that presents with a heterogenous clinical phenotype, including sleep disorders, movement abnormalities and bulbar involvement. It is characterized by autoantibodies against IgLON5, 85% association with HLA-DQB1*05:∼ and a brainstem-dominant tauopathy. Cellular and murine models report pathogenic effects of the autoantibodies, and neurodegenerative factors suggest progressive atrophy as a common sequela. However, evidence from in vivo patient data and long-term follow-up is limited, and the degree of progression remains elusive. In this multicentre study, clinical and brain MRI data were collected from 127 patients across 12 countries to investigate the relationships between clinical presentations and the development of distinct brain atrophy patterns. Our data show that most patients develop a complex multisystem phenotype as the disease progresses; however, neuromuscular manifestations rarely emerge at later disease stages. By comparison to healthy controls, this disease presents with severe substructure-specific atrophy, especially affecting the hypothalamus, brainstem, accumbens and basal ganglia, which, in age-independent analyses, show significant ventricular enlargement and also suggest progression of brainstem atrophy over the disease course. Moreover, the focality of atrophy was functionally linked to specific symptoms, with more severe involvement of the basal ganglia in patients with movement disorders, and greater atrophy in the hippocampus and thalamus in patients with cognitive impairment. Taken together, our results provide evidence of distinct atrophy patterns in anti-IgLON5 disease, which closely mirror sites of pathophysiologic processes, including autoantibody binding and tau deposition. Our data emphasize the brainstem as the pathophysiological hub of the disease and provide normative data for the incorporation of atrophy measurements into routine clinical assessments and future treatment studies to monitor disease trajectory and evaluate future treatment strategies.

This international multicenter study seeks to determine the frequency and characteristics of meningitis in myelin oligodendrocyte glycoprotein antibody (MOGAD)–associated disease and highlight its pathology.