Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsyShow full item record
Title | Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy |
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Author | Ricci, Lorenzo; Matarrese, Margherita; Peters, Jurriaan M.; Tamilia, Eleonora; Madsen, Joseph R.; Pearl, Phillip L.; Papadelis, Christos |
Date | 2022 |
Abstract | 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. |
Link | https://doi.org/10.1016/j.clinph.2022.04.009
https://repository.tcu.edu/handle/116099117/56996 |
Department | Burnett School of Medicine |
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