Abstract
Electrical Source Imaging (ESI) is a non-invasive technique of reconstructing brain activities using EEG data. This technique has been applied to evaluate epilepsy patients being evaluated for epilepsy surgery, showing encouraging results for mapping interictal epileptiform discharges (IED). However, ESI is underused in planning epilepsy surgery. This is basically due to the wide availability of methods for solving the electromagnetism inverse problem (e-IP) associated to few studies using EEG setups similar to those most commonly used in clinical setting. In this study, we applied six different methods of solving the e-IP based on IEDs of 20 focal epilepsy patients that presented abnormalities in their MRI. We compared the ESI maps obtained by each method with the location of the abnormality, calculating the Euclidian distances from the center of the lesion to the closest border of the method solution (CL-BM) and also to the solution’s maxima (CL-MM). We also applied a score system in order to allow us to evaluate the sensitivity of each method for temporal and extra temporal patients. In our patients, the Bayesian Model Averaging method had a sensitivity of 86% and the shortest CL-MM. This method also had more restricted solutions that were more representative of epileptogenic activities than those obtained by the other methods.
Highlights
Epilepsy surgery may be a plausible option for drug resistant patients
In the current paper we discuss one patient more detailed, and two more patients are presented in Supplementary Material, in order to highlight how the Electrical Source Imaging (ESI) methods can be useful for the clinical routine related to epilepsy
We found that the application of ESI for reconstructing interictal epileptiform discharges (IED) activities is sensitivity for EEG acquired by few numbers of electrodes (
Summary
Epilepsy surgery may be a plausible option for drug resistant patients. the surgical planning has to be a very cautious procedure, based on information obtained by the agreement among different techniques, such as the ictal and interictal electroencephalogram (EEG), magnetic resonance imaging (MRI), positron emission tomography (PET), single photon emission computerized tomography (SPECT) and magnetoencephalogram (MEG). In some patients the information available by these non-invasive techniques is not enough to identify the epileptogenic area, and the brain area needed to be resected in a surgery in order to make the patient seizure-free. In such patients further investigation is needed, which is generally done by invasive methods, such as intracranial or foramen ovale electrodes, which carry considerable morbidity and cost. A non-invasive method based on the application of the electromagnetism inverse problem (e-IP) [1] on EEG data is the Electrical Source Imaging (ESI). Other methods as Minimum Norm (MN) [3], Low Resolution Electromagnetic Tomography (LORETA) [4], Local Auto-Regressive (LAURA) [5], Classical LORETA Analysis Recursively Applied (CLARA) [6] and Bayesian Model Averaging (BMA) [7] consider the source responsible for generating the electrical currents with a finite extension
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