Temporal Lobe Epilepsy Lateralization Based on MR Image Intensity and Registration Features

Abstract

In the context of MR imaging, explicit segmentation followed by stereologic volumetry of the hippocampus (HC) has been the standard approach toward temporal lobe epilepsy (TLE) lateralization of the seizure focus. The novelty of the method presented here resides in its analysis of characteristics of large, non-specific Volumes of Interest from T1 MRI data aiming to lateralize the seizure focus in patients with TLE without segmentation. For this purpose, Principal Components Analysis (PCA) of two image features are united to create a multi-dimensional space representative of a training set population composed of 150 normal subjects. The feature instances consist of grey-level intensity and an approximation of the Jacobian matrix of non-linear registration-derived dense deformation fields. New data for TLE subjects are projected in this space, under the assumption that the distributions of the projections of normal and patients are not identical and can be used for lateralization. Results are presented following PCA modeling of the left medial temporal lobe only for all subjects. It is shown that linear discriminant analysis of the eigencoordinates can be used to lateralize the seizure focus in TLE patients with a 75% accuracy. It is expected that adding a right temporal lobe model will improve lateralization results beyond those of HC volumetry.