Localization of Seizure Onset Zone based on Spatio-Temporal Independent Component Analysis on fMRI

TL;DR

This study introduces a spatiotemporal independent component analysis method on rs-fMRI data to accurately localize seizure onset zones in epilepsy patients, aiding presurgical planning with high spatial precision and reliability.

Contribution

The paper presents a novel spatiotemporal ICA approach for localizing epileptic foci using interictal rs-fMRI data, improving accuracy and clinical applicability over existing methods.

Findings

High spatial accuracy in localizing epileptic foci.

Method achieved concordance with surgical resection areas.

Reliable results suitable for clinical use.

Abstract

Localizing the seizure onset zone (SOZ) as a step of presurgical planning leads to higher efficiency in surgical and stimulation treatments. However, the clinical localization including structural, ictal, and invasive data acquisition and assessment is a difficult and long procedure with increasing challenges in patients with complex epileptic foci. The interictal methods are proposed to assist in presurgical planning with simpler data acquisition and higher speed. This study presents a spatiotemporal component classification for the localization of epileptic foci using resting-state functional magnetic resonance imaging data. This method is based on spatiotemporal independent component analysis on rsfMRI with a component-sorting procedure upon dominant power frequency, biophysical constraints, spatial lateralization, local connectivity, temporal energy, and functional non-Gaussianity. This method utilized the rs-fMRI potential to reach a high spatial accuracy in localizing epileptic foci from interictal data while retaining the reliability of results for clinical usage. Thirteen patients with temporal lobe epilepsy who underwent surgical resection and had seizure-free surgical outcomes after a 12-month follow-up were included in this study. All patients had presurgical structural MRI and rsfMRI while postsurgical MRI images were available for ten. Based on the relationship between the localized foci and resection, the results were classified into three groups fully concordant, partially concordant, and discordant. These groups had the resulting cluster aligned with, in the same lobe with, and outside the lobe of the resection area, respectively.