Epilepsy-Related Brain Network Alterations in Patients With Temporal Lobe Glioma in the Left Hemisphere
Shengyu Fang, Chunyao Zhou, Xing Fan, Tao Jiang, Yinyan Wang
Abstract
Background: Seizures are a common symptom in patients with temporal lobe gliomas and may result in brain network alterations, but brain network changes caused by glioma-related epilepsy remain poorly understood. In this study, we applied graph theory analysis to delineate topological networks with resting-state functional magnetic resonance images and investigated the characteristics of functional networks in patients with glioma-related epilepsy. Methods: Thirty patients with low grade gliomas in the left temporal lobe were enrolled and classified into epileptic (n =15) and non-epileptic groups. Twenty healthy participants matched for age, gender, and education level were enrolled. The whole brain network was divided into sub-networks (including sensorimotor network, visual network, default mode network (DMN), auditory network, and right executive control network) to construct functional-connection matrices. In addition, topological properties (including global efficiency, nodal efficiency, degree centrality, and etc.) of each sub-networks were investigated. Results: Significant alterations were observed only in the visual network. Compared to the epileptic group, the non-epileptic group presented with four edges with higher functional connectivity. Further, 21 edges with higher functional connectivity were identified in the non-epileptic group compared to those in the healthy group. Increased global efficiency and decreased shortest path length were noted in the non-epileptic group compared to the epileptic and healthy groups. Nodal efficiency of three nodes was higher in the epileptic and non-epileptic groups than in the healthy group. Degree centrality of six nodes was altered in the non-epileptic group relative to that in the healthy group. Conclusion: Temporal lobe gliomas in the left hemisphere and glioma-related epilepsy altered visual networks in an opposing manner. These findings provide novel insight into brain network alterations induced by glioma-related epilepsy.