Journal
CLINICAL NEUROPHYSIOLOGY
Volume 139, Issue -, Pages 49-57Publisher
ELSEVIER IRELAND LTD
DOI: 10.1016/j.clinph.2022.04.009
Keywords
Epilepsy surgery; Pediatric epilepsy; Electrical source imaging; Virtual sensors
Categories
Funding
- National Institute of Neurological Disorders Stroke [RO1NS104116-01A1, R21NS101373-01A1]
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This study examined the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the seizure onset zone (SOZ) and predicting surgical outcome in children with drug resistant epilepsy. The results showed that virtual implantation can approximate the SOZ and predict the outcome of the surgery.
Objective: Delineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome. Methods: We retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome. Results: Twenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57-0.89; sensitivity = 66.7%; specificity = 78. 6%; accuracy = 71.4%). Conclusions: Virtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome. Significance: SOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome. (c) 2022 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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