Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy.

Farnaz Farokhian,Hiroshi Matsuda,Daichi Sone,Iman Beheshti

doi:10.3389/fneur.2017.00428

Abstract

The identification of the brain morphological alterations that play important roles in neurodegenerative/neurological diseases will contribute to our understanding of the causes of these diseases. Various automated software programs are designed to provide an automatic framework to detect brain morphological changes in structural magnetic resonance imaging (MRI) data. A voxel-based morphometry (VBM) analysis can also be used for the detection of brain volumetric abnormalities. Here, we compared gray matter (GM) and white matter (WM) abnormality results obtained by a VBM analysis using the Computational Anatomy Toolbox (CAT12) via the current version of Statistical Parametric Mapping software (SPM12) with the results obtained by a VBM analysis using the VBM8 toolbox implemented in the older software SPM8, in adult temporal lobe epilepsy (TLE) patients with (n = 51) and without (n = 57) hippocampus sclerosis (HS), compared to healthy adult controls (n = 28). The VBM analysis using CAT12 showed that compared to the healthy controls, significant GM and WM reductions were located in ipsilateral mesial temporal lobes in the TLE-HS patients, and slight GM amygdala swelling was present in the right TLE-no patients (n = 27). In contrast, the VBM analysis via the VBM8 toolbox showed significant GM and WM reductions only in the left TLE-HS patients (n = 25) compared to the healthy controls. Our findings thus demonstrate that compared to VBM8, a VBM analysis using CAT12 provides a more accurate volumetric analysis of the brain regions in TLE. Our results further indicate that a VBM analysis using CAT12 is more robust and accurate against volumetric alterations than the VBM8 toolbox.

Highlights

Identifying brain morphological changes is a challenging task in neuroimaging studies
The voxel-based morphometry (VBM) analysis results obtained with the VBM8 toolbox showed only a slight reduction in gray matter (GM) volume at the right hippocampus region in the RTLE-hippocampus sclerosis (HS) patients compared to the healthy controls
The VBM analyses using the VBM8 and CAT12 procedures each revealed a significant increase in the GM in the right amygdala in the right TLE patients without HS (RTLE-no) patients compared to the healthy controls

Summary

Introduction

Identifying brain morphological changes is a challenging task in neuroimaging studies. Voxelbased morphometry (VBM), introduced by Ashburner and Friston [1], is an advanced and powerful quantitative magnetic resonance imaging (MRI) procedure used to detect the brain morphological/volumetric changes in brain diseases. VBM assesses whole-brain structures with voxel-by-voxel comparisons, and it was developed to analyze tissue concentrations or volumes between subject groups in order to distinguish the structural abnormalities in the brain. The brain volumetric changes in Alzheimer’s disease [3], Parkinson disease [4], epilepsy [5], and the aging process [6] have been subjected to VBM analyses. Tissue segmentation: the aim of this step is to classify the MRI scans into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) images A standard VBM analysis incorporates the following preprocessing steps: 1. Tissue segmentation: the aim of this step is to classify the MRI scans into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) images

Methods

Results

Discussion

Conclusion