Preoperative Epilepsy Network Distribution Correlates With Seizure Recurrence Following Epilepsy Surgery

Abstract

INTRODUCTION Surgery remains an essential option for the treatment of medically intractable temporal lobe epilepsy. However, only 66% of patients achieve postoperative seizure freedom, perhaps attributable to an incomplete understanding of brain network alterations in surgical candidates. Here, we present a novel network modeling algorithm that may be used to identify key characteristics of epileptic networks correlated with improved surgical outcome. METHODS Twenty-nine patients were prospectively included, and relevant demographic information was attained. Resting-state functional magnetic resonance imaging (MRI) and electroencephalography (EEG) data were recorded and preprocessed. Using our novel algorithm, patient-specific epileptic networks were mapped preoperatively and geographic spread was quantified. Global functional connectivity was also determined using a volumetric functional atlas. Key demographic data and features of epileptic networks were then correlated with surgical outcome using Pearson's product-moment correlation. RESULTS At an average follow-up of 19 mo, 20/29 (69%) patients were seizure-free. Higher rates of seizure recurrence correlated with the localization of the epilepsy network to either temporal lobe (R = –0.415, P = .039), with the stronger correlation found with the localization to the contralateral temporal lobe (R = –0.566, P = .003). When the volumetric functional atlas connectivity was measured, increased connectivity globally was correlated with seizure recurrence (R = –0.541, P = .006). Seizure recurrence also correlated with greater atlas-based connectivity within the contralateral hemisphere (R = –0.390, P = .049). CONCLUSION Network localization to the temporal lobes, in particular the contralateral temporal lobe, and increased atlas-defined connectivity contralateral to the surgery side are associated with seizure recurrence. These findings may reflect network-level disruption that has infiltrated the contralateral temporal lobe contributing to relatively worse surgical outcomes. Further identification of network parameters that predict patient outcomes may aid in patient selection, resection planning, and ultimately the efficacy of epilepsy surgery.