Mapping grey matter and network abnormalities in seizure-onset patterns via stereotactic EEG
Tao Feng1, Yanfeng Yang1, Yihe Wang1
1Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China; China International Neuroscience Institute (CHINA-INI), Beijing, China.
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.
