Mapping grey matter and network abnormalities in seizure-onset patterns via stereotactic EEG

Mapping grey matter and network abnormalities in seizure-onset patterns via stereotactic EEG

Background: Mesial temporal lobe epilepsy (MTLE) is the most common medically refractory focal epilepsy, classified into seizure-onset patterns (SOPs) such as hypersynchronous (HYP) and low-voltage fast (LVF) rhythms. However, the morphological and network differences underlying these SOPs and their...

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Main Authors: Tao Feng, Yanfeng Yang, Yihe Wang, Xiaotong Fan, Tianren Wang, Sichang Chen, Penghu Wei, Yongzhi Shan, Guoguang Zhao
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Neurobiology of Disease
Subjects:
Seizure onset patterns
Drug-resistant epilepsy
Stereotactic EEG
Neuro-electrophysiological biomarkers
Individual structural covariance network
Online Access:http://www.sciencedirect.com/science/article/pii/S0969996125002372
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Summary:Background: Mesial temporal lobe epilepsy (MTLE) is the most common medically refractory focal epilepsy, classified into seizure-onset patterns (SOPs) such as hypersynchronous (HYP) and low-voltage fast (LVF) rhythms. However, the morphological and network differences underlying these SOPs and their prognostic implications remain unclear. Methods: Using voxel-based morphometry (VBM) and individualized structural covariance networks (IDSCNs), we analyzed 55 MTLE patients and 37 healthy controls with high-resolution MRI and stereotactic EEG recordings. VBM identified grey matter volume (GMV) abnormalities, and IDSCNs evaluated patient-specific network disruptions. Hierarchical clustering explored network subtypes, and ROC analysis assessed the predictive value of VBM and IDSCN measures for surgical outcomes. Results: HYP-onset patients exhibited ipsilateral mesial temporal atrophy and widespread bilateral network disruptions centered on the hippocampus and supramarginal gyrus, along with significant interhemispheric connectivity abnormalities. LVF-onset patients showed subcortical abnormalities and hemispheric network disruptions centered on the fusiform gyrus, with limited interhemispheric propagation. Both SOPs displayed basal ganglia abnormalities. Hierarchical clustering revealed SOP-specific network subtypes. IDSCN outperformed VBM in predicting surgical outcomes. Conclusion: This study identifies distinct SOP-related morphological and network abnormalities in MTLE and suggests that IDSCN may offer valuable insights into personalized treatment planning and prognostic evaluation, supporting further exploration of network-based biomarkers.
ISSN:1095-953X

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