Morphometric Similarity Network Abnormalities in epilepsy patients with focal to bilateral tonic-clonic seizures
Abstract number :
1.354
Submission category :
5. Neuro Imaging / 5B. Functional Imaging
Year :
2025
Submission ID :
745
Source :
www.aesnet.org
Presentation date :
12/6/2025 12:00:00 AM
Published date :
Authors :
Presenting Author: Yi Liang, MM – Department of Neurology, West China Hospital of Sichuan University
Chenyang Zhao, MD – Department of Neurology, West China Hospital of Sichuan University
Bo Yan, MD – Department of Neurology, West China Hospital of Sichuan University
Ping Jiang, MD – Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University
Xintong Wu, MD – Department of Neurology, West China Hospital of Sichuan University
Yingying Tang, MD – Department of Neurology, West China Hospital of Sichuan University
Dong Zhou, MD – West China Hospital of Sichuan University, Sichuan, China
Rationale: Focal to bilateral tonic-clonic seizures (FBTCS) are a severe form of epileptic seizures, often associated with poor prognosis, increased risk of injury, and sudden unexpected death in epilepsy. The aim of this study was to explore the gray-matter structural network changes related to FBTCS by constructing morphometric similarity network (MSN).
Methods: Patients with focal epilepsy who underwent preoperative evaluation were enrolled and those with major MRI lesions were excluded. Based on the video-EEG recording, we classified patients with active FBTCS within 1 year prior to scanning to the FBTCS+ group and those never experienced FBTCS to the FBTCS- group. Sex- and age- matched healthy controls (HCs) were recruited. 3D-T1 weighted images were conducted and surface-based analysis was performed to obtain 7 cortical morphological features at the individual level, including gray matter volume, surface area, cortical thickness, intrinsic curvature, mean curvature, curved index and folding index. Based on the Schaefer 2018_400 Parcels template, a 7×1 morphological feature vector was Z-scored across the 400 cortical regions. Pearson correlation coefficient was calculated between each paired brain region, thus constructing a 400×400 MSN matrix for each subject. General linear models with ANOVA and post-hoc analysis were used for comparison among the three groups. False discovery rate (FDR) method was applied for multiple comparison correction, with statistical significance set at p < 0.05.
Neuro Imaging