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

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 morp...

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Autores principales: Farokhian, Farnaz, Beheshti, Iman, Sone, Daichi, Matsuda, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573734/
https://www.ncbi.nlm.nih.gov/pubmed/28883807
http://dx.doi.org/10.3389/fneur.2017.00428
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author Farokhian, Farnaz
Beheshti, Iman
Sone, Daichi
Matsuda, Hiroshi
author_facet Farokhian, Farnaz
Beheshti, Iman
Sone, Daichi
Matsuda, Hiroshi
author_sort Farokhian, Farnaz
collection PubMed
description 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.
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spelling pubmed-55737342017-09-07 Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy Farokhian, Farnaz Beheshti, Iman Sone, Daichi Matsuda, Hiroshi Front Neurol Neuroscience 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. Frontiers Media S.A. 2017-08-24 /pmc/articles/PMC5573734/ /pubmed/28883807 http://dx.doi.org/10.3389/fneur.2017.00428 Text en Copyright © 2017 Farokhian, Beheshti, Sone and Matsuda. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Farokhian, Farnaz
Beheshti, Iman
Sone, Daichi
Matsuda, Hiroshi
Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title_full Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title_fullStr Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title_full_unstemmed Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title_short Comparing CAT12 and VBM8 for Detecting Brain Morphological Abnormalities in Temporal Lobe Epilepsy
title_sort comparing cat12 and vbm8 for detecting brain morphological abnormalities in temporal lobe epilepsy
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573734/
https://www.ncbi.nlm.nih.gov/pubmed/28883807
http://dx.doi.org/10.3389/fneur.2017.00428
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