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Resting-State SEEG May Help Localize Epileptogenic Brain Regions.

Authors :
Goodale SE
González HFJ
Johnson GW
Gupta K
Rodriguez WJ
Shults R
Rogers BP
Rolston JD
Dawant BM
Morgan VL
Englot DJ
Source :
Neurosurgery [Neurosurgery] 2020 Jun 01; Vol. 86 (6), pp. 792-801.
Publication Year :
2020

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.<br />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.<br />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.<br />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%.<br />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.<br /> (Copyright © 2019 by the Congress of Neurological Surgeons.)

Details

Language :
English
ISSN :
1524-4040
Volume :
86
Issue :
6
Database :
MEDLINE
Journal :
Neurosurgery
Publication Type :
Academic Journal
Accession number :
31814011
Full Text :
https://doi.org/10.1093/neuros/nyz351