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A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages

BACKGROUND: Cortical parcellation is an essential neuroimaging tool for identifying and characterizing morphometric and connectivity brain changes occurring with age and disease. A variety of software packages have been developed for parcellating the brain’s cortical surface into a variable number o...

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Autores principales: Mikhael, Shadia S., Pernet, Cyril
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6348615/
https://www.ncbi.nlm.nih.gov/pubmed/30691385
http://dx.doi.org/10.1186/s12859-019-2609-8
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author Mikhael, Shadia S.
Pernet, Cyril
author_facet Mikhael, Shadia S.
Pernet, Cyril
author_sort Mikhael, Shadia S.
collection PubMed
description BACKGROUND: Cortical parcellation is an essential neuroimaging tool for identifying and characterizing morphometric and connectivity brain changes occurring with age and disease. A variety of software packages have been developed for parcellating the brain’s cortical surface into a variable number of regions but interpackage differences can undermine reproducibility. Using a ground truth dataset (Edinburgh_NIH10), we investigated such differences for grey matter thickness (GM(th)), grey matter volume (GM(vol)) and white matter surface area (WM(sa)) for the superior frontal gyrus (SFG), supramarginal gyrus (SMG), and cingulate gyrus (CG) from 4 parcellation protocols as implemented in the FreeSurfer, BrainSuite, and BrainGyrusMapping (BGM) software packages. RESULTS: Corresponding gyral definitions and morphometry approaches were not identical across the packages. As expected, there were differences in the bordering landmarks of each gyrus as well as in the manner in which variability was addressed. Rostral and caudal SFG and SMG boundaries differed, and in the event of a double CG occurrence, its upper fold was not always addressed. This led to a knock-on effect that was visible at the neighbouring gyri (e.g., knock-on effect at the SFG following CG definition) as well as gyral morphometric measurements of the affected gyri. Statistical analysis showed that the most consistent approaches were FreeSurfer’s Desikan-Killiany-Tourville (DKT) protocol for GM(th) and BrainGyrusMapping for GM(vol). Package consistency varied for WM(sa), depending on the region of interest. CONCLUSIONS: Given the significance and implications that a parcellation protocol will have on the classification, and sometimes treatment, of subjects, it is essential to select the protocol which accurately represents their regions of interest and corresponding morphometrics, while embracing cortical variability. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2609-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-63486152019-01-31 A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages Mikhael, Shadia S. Pernet, Cyril BMC Bioinformatics Research Article BACKGROUND: Cortical parcellation is an essential neuroimaging tool for identifying and characterizing morphometric and connectivity brain changes occurring with age and disease. A variety of software packages have been developed for parcellating the brain’s cortical surface into a variable number of regions but interpackage differences can undermine reproducibility. Using a ground truth dataset (Edinburgh_NIH10), we investigated such differences for grey matter thickness (GM(th)), grey matter volume (GM(vol)) and white matter surface area (WM(sa)) for the superior frontal gyrus (SFG), supramarginal gyrus (SMG), and cingulate gyrus (CG) from 4 parcellation protocols as implemented in the FreeSurfer, BrainSuite, and BrainGyrusMapping (BGM) software packages. RESULTS: Corresponding gyral definitions and morphometry approaches were not identical across the packages. As expected, there were differences in the bordering landmarks of each gyrus as well as in the manner in which variability was addressed. Rostral and caudal SFG and SMG boundaries differed, and in the event of a double CG occurrence, its upper fold was not always addressed. This led to a knock-on effect that was visible at the neighbouring gyri (e.g., knock-on effect at the SFG following CG definition) as well as gyral morphometric measurements of the affected gyri. Statistical analysis showed that the most consistent approaches were FreeSurfer’s Desikan-Killiany-Tourville (DKT) protocol for GM(th) and BrainGyrusMapping for GM(vol). Package consistency varied for WM(sa), depending on the region of interest. CONCLUSIONS: Given the significance and implications that a parcellation protocol will have on the classification, and sometimes treatment, of subjects, it is essential to select the protocol which accurately represents their regions of interest and corresponding morphometrics, while embracing cortical variability. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2609-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-28 /pmc/articles/PMC6348615/ /pubmed/30691385 http://dx.doi.org/10.1186/s12859-019-2609-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Mikhael, Shadia S.
Pernet, Cyril
A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title_full A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title_fullStr A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title_full_unstemmed A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title_short A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
title_sort controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6348615/
https://www.ncbi.nlm.nih.gov/pubmed/30691385
http://dx.doi.org/10.1186/s12859-019-2609-8
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