ArticleQuantitative imaging in medicine and surgery2025
Imaging biomarkers in antibody-mediated autoimmune encephalitis.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Multi-omics integration in autoimmune encephalitis: from novel biomarker discovery to precision therapeutic strategies.Frontiers in immunology · 2026Review
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Authors and funding
7 authors.
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Abstract
Background: Imaging, particularly multimodal magnetic resonance imaging (MRI), serves as an essential auxiliary examination for diagnosing autoimmune encephalitis (AE). The diversity of autoantibodies complicates the imaging presentation of AE, exhibiting both common and individual features across different subtypes of AE. Currently, there is a lack of comprehensive studies on the imaging features of different subtypes of AE. The study aimed to explore imaging biomarkers for AE mediated by various subtypes of antibodies and clarify their significance in disease severity, treatment response, and prognosis. Methods: The clinical and imaging data of 45 patients with AE at The First Affiliated Hospital of Dalian Medical University, collected from January 2013 to August 2022, were analyzed. Patients underwent multi-modal brain MRI. Lesion probability maps were generated, and regions of interest (ROIs) were selected based on lesion location and clinical-electroencephalographic features, for measurement of three-dimensional T1-weighted imaging (3D-T1WI), T2-weighted imaging (T2WI), T2 fluid-attenuated inversion recovery (T2 FLAIR), and apparent diffusion coefficient (ADC) sequences. These values were used for correlating with disease severity, antibody titers, response to treatment, and prognosis. Results: The study included 45 AE patients: 18 with anti-leucine-rich glioma inactivated protein 1 (anti-LGI1), 11 with anti-N-methyl-D-aspartate receptor (anti-NMDAR), 5 with anti-gamma-aminobutyric acid receptor B (anti-GABA Conclusions: Imaging abnormalities are less frequent than those detected by EEG but exhibit distinct features by subtype. Functional imaging enhances diagnostic accuracy. ADC values can serve as a crucial prognostic indicator.
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