Multi-feature localization of epileptic foci from interictal, intracranial EEG.

ABSTRACT:

Objective

When considering all patients with focal drug-resistant epilepsy, as high as 40-50% of patients suffer seizure recurrence after surgery. To achieve seizure freedom without side effects, accurate localization of the epileptogenic tissue is crucial before its resection. We investigate an automated, fast, objective mapping process that uses only interictal data.

Methods

We propose a novel approach based on multiple iEEG features, which are used to train a support vector machine (SVM) model for classification of iEEG electrodes as normal or pathologic using 30 min of inter-ictal recording.

Results

The tissue under the iEEG electrodes, classified as epileptogenic, was removed in 17/18 excellent outcome patients and was not entirely resected in 8/10 poor outcome p

SUBMITTER: Cimbalnik J 

PROVIDER: S-EPMC6759804 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature