Resting-State SEEG May Help Localize Epileptogenic Brain Regions. Issue 6 (16th September 2019)

• Record Type: Journal Article
• Authors: Goodale, Sarah E; González, Hernán F J; Johnson, Graham W; Gupta, Kanupriya; Rodriguez, William J; Shults, Robert; Rogers, Baxter P; Rolston, John D; Dawant, Benoit M; Morgan, Victoria L; Englot, Dario J
• Is Part Of: Neurosurgery. Volume 86:Issue 6(2020)
• Page Start: 792
• Page End: 801
• Publication Date: 2019-09-16
• Subjects: Brain networks -- Functional connectivity -- Intracranial EEG -- Localization -- Seizure; Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1093/neuros/nyz351
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract: BACKGROUND: Stereotactic electroencephalography (SEEG) is a minimally invasive neurosurgical method to localize epileptogenic brain regions in epilepsy but requires days in the hospital with interventions to trigger several seizures. OBJECTIVE: To make initial progress in the development of network analysis methods to identify epileptogenic brain regions using brief, resting-state SEEG data segments, without requiring seizure recordings. METHODS: In a cohort of 15 adult focal epilepsy patients undergoing SEEG, we evaluated functional connectivity (alpha-band imaginary coherence) across sampled regions using brief (2 min) resting-state data segments. Bootstrapped logistic regression was used to generate a model to predict epileptogenicity of individual regions. RESULTS: Compared to nonepileptogenic structures, we found increased functional connectivity within epileptogenic regions ( P < .05) and between epileptogenic areas and other structures ( P < .01, paired t-tests, corrected). Epileptogenic areas also demonstrated higher clustering coefficient ( P < .01) and betweenness centrality ( P < .01), and greater decay of functional connectivity with distance ( P < .05, paired t-tests, corrected). Our functional connectivity model to predict epileptogenicity of individual regions demonstrated an area under the curve of 0.78 and accuracy of 80.4%. CONCLUSION: Our study represents a preliminary step towards defining resting-state SEEG functional connectivity patterns to help localize epileptogenic brain regions ahead of neurosurgical treatment without requiring seizure recordings.