Abstracts

Rationale: We previously demonstrated that widespread structural and cognitive abnormalities are present in children at the time of epilepsy onset. It is unknown whether these abnormalities are accompanied by disruptions of large-scale brain structural networks. Specially, new-onset pediatric epilepsy may have a significant neurodevelopmental impact in the remodeling of the brain organizational networks. In this study, we aimed to investigate global structural brain network metrics in patients with localization related epilepsy (LRE) and idiopathic generalized epilepsy (IGE), compared with healthy controls. Methods: We studied sixty-seven subjects: 28 healthy controls (mean age 13.3 ± 3.28 years, 11 males), 39 children with new-onset epilepsy (21 LRE (11.6 ± 2.68 years, 12 males) and 18 IGE (15 ± 3.3 years, 7 males). Patients and controls were similar in age (Chi=1.9, p=0.4) and gender distribution (one way ANOVA F=5.72, with significant group effect p=0.005, with Tukey HSD demonstrating younger age in IGE compared to LRE but not controls). All subjects underwent MRI scanning yielding SPGR images (1.5 Tesla GE Signa MR scanner, TR = 24 ms, TE = 5 ms, flip angle = 40°, Slice thickness 1.5mm). Images underwent volumetric segmentation utilizing FreeSurfer according to the ‘Destrieux Atlas'. Data from 171 regions of interest were utilized for the construction of group-wise adjacency matrices (controls, LRE and IGE) where each one of the 171x171 entries represented the partial correlation between the volumes from each pair of regions, controlled for age, bootstrapped 100 times. The adjacency matrices were then utilized for the evaluation of global graphical metric properties (Global Efficiency, Mean Betweenness Centrality, and Mean Clustering Coefficient) across fixed density threshold binary matrices (ranging from 0.05 to 0.95) through the use of the Brain Connectivity Toolbox. The level of significance for statistical comparison was set a False Discovery Rate corrected q=0.05. Results: The density matrices demonstrated an overall increase pairwise correlation between regions. The upper row in Figure 1 demonstrates the adjacency matrices for each group of patients, and the location of significant increase in pairwise correlation is shown in the bottom row of Figure 1. Global network metrics demonstrated a significant increase in Mean Clustering Coefficient in patients, while Global Efficiency was significantly reduced in patients compared with controls (Figure2). Conclusions: Children with new-onset epilepsy showed abnormal configuration of structural neural networks in the developing brain. Compared with controls, a more segregated (increased clustering coefficient) and less integrated (decreased efficiency) global network was evident in children with epilepsy, indicating a less optimal topological organization. These findings indicate an abnormal global network brain configuration early in the course of epilepsy, which may have significant implications for neurocognitive development.