Altered white matter structural network in self-limited epilepsy with centrotemporal spikes

Background: The changes in white matter (WM) structural networks associated with self-limited epilepsy with centrotemporal spikes (SeLECTS) remain poorly understood, despite the established role of WM network changes in elucidating pathological mechanisms underlying epileptic disorders. We aimed to explore the structural network alterations in SeLECTS, and analyze the relationship between structural networks and disease status. Methods: This study enrolled 64 participants, comprising 32 children with SeLECTS and 32 age- and sex-matched typically developing (TD) children. Graph-theoretic methods were applied to characterize the topological organization of WM structural networks derived from diffusion tensor imaging (DTI). Intergroup comparisons of global and nodal network metrics were performed using non-parametric tests with false discovery rate (FDR) correction. Correlation analyses were conducted to examine relationships between network alterations and clinical variables, including seizure duration and intelligence quotients (IQs). Additionally, a support vector machine (SVM) classifier was trained using network metrics to distinguish patients from controls, with model performance evaluated on an independent test set using accuracy (ACC), sensitivity (SEN), specificity (SPE), and area under the curve (AUC). Results: in STG.L showed positive correlations with full-scale (r=0.53, P