Localizing and studying epileptogenic sources in patients with focal epilepsy in pre-surgical planning

• Ano de defesa: 2016
• Autor(a) principal: Maziero, Danilo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Correção de artefatos de Movimento; EEG; EEG-fMRI; Electrical Source Imaging; Epilepsia; Epilepsy; Imagens de Fontes Elétricas; Motion-induced Artefacts Correction
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/59/59135/tde-27072016-151155/

The simultaneous acquisitions of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been applied to improve the surgery planning of patients with drug resistant epilepsy. However, the classical approach of analyzing the EEG-fMRI data is inefficient in patients whom only few or non interictal epileptiforms discharges (IEDs) are detected during the simultaneous acquisition. Another issue of EEG-fMRI acquisition is related to its high sensitivity to motion, which decreases the quality of both data, even worse in non-cooperative patients. In this work we propose and discuss the application of two methods of analyzing fMRI data of patients with focal epilepsy: Independent component analysis (ICA) and two-dimensional temporal clustering (2dTCA). Each method was applied in a distinct group of patients and the results were compared to those obtained by the classic EEG-fMRI analysis. We have also proposed a method to improve the quality of EEG data using the head position measurements obtained, by a prospective motion correction (PMC) system, during the EEG-fMRI acquisitions. In the ICA study, we have used the electrical source images for selecting independent components (ICs) in EEG data of 13 patients with different spiking frequency. The method detected epilepsy-related BOLD activity in all the patients. Comparatively, the classic EEG-fMRI could be applied in 11 patients and epilepsy-related BOLD activities were found in seven of them. In the 2dTCA study, we have evaluated 20 patients and found epilepsy-related maps in 14 of them. Thirteen of the twenty patients have IEDs detected during the simultaneous acquisition; the classic EEG-fMRI provided maps related to the epileptogenic region in six of them. Finally we have verified in three health subjects that the proposed method for correcting motion-induced artefacts in the EEG data is effective for high amplitude and velocities (~1cm and 55mm/s). We concluded that the ICA and 2dTCA methods increase the sensitivity of using fMRI for mapping the epileptogenic region, mainly in patients presenting few or no IEDs in the EEG data simultaneously acquired to the fMRI. The PMC use during the fMRI acquisition does not degrade the quality of the EEG data acquired simultaneously. In fact, the motion information can be used for improving its quality by correcting motion-induced artefacts.