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Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)

Longitudinal studies measuring changes in cortical morphology over time are best facilitated by parcellation schemes compatible across all life stages. The Melbourne Children’s Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases provide voxel-based parcellations of the cerebral cortex compatible w...

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Autores principales: Adamson, Chris L., Alexander, Bonnie, Ball, Gareth, Beare, Richard, Cheong, Jeanie L. Y., Spittle, Alicia J., Doyle, Lex W., Anderson, Peter J., Seal, Marc L., Thompson, Deanne K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062836/
https://www.ncbi.nlm.nih.gov/pubmed/32152381
http://dx.doi.org/10.1038/s41598-020-61326-2
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author Adamson, Chris L.
Alexander, Bonnie
Ball, Gareth
Beare, Richard
Cheong, Jeanie L. Y.
Spittle, Alicia J.
Doyle, Lex W.
Anderson, Peter J.
Seal, Marc L.
Thompson, Deanne K.
author_facet Adamson, Chris L.
Alexander, Bonnie
Ball, Gareth
Beare, Richard
Cheong, Jeanie L. Y.
Spittle, Alicia J.
Doyle, Lex W.
Anderson, Peter J.
Seal, Marc L.
Thompson, Deanne K.
author_sort Adamson, Chris L.
collection PubMed
description Longitudinal studies measuring changes in cortical morphology over time are best facilitated by parcellation schemes compatible across all life stages. The Melbourne Children’s Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases provide voxel-based parcellations of the cerebral cortex compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes. This study introduces surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), with a pipeline for automated parcellation utilizing FreeSurfer and developing Human Connectome Project (dHCP) tools. Using T(2)-weighted magnetic resonance images of healthy neonates (n = 58), we created average spherical templates of cortical curvature and sulcal depth. Manually labelled regions in a subset (n = 10) were encoded into the spherical template space to construct M-CRIB-S(DK) and M-CRIB-S(DKT) atlases. Labelling accuracy was assessed using Dice overlap and boundary discrepancy measures with leave-one-out cross-validation. Cross-validated labelling accuracy was high for both atlases (average regional Dice = 0.79–0.83). Worst-case boundary discrepancy instances ranged from 9.96–10.22 mm, which appeared to be driven by variability in anatomy for some cases. The M-CRIB-S atlas data and automatic pipeline allow extraction of neonatal cortical surfaces labelled according to the DK or DKT parcellation schemes.
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spelling pubmed-70628362020-03-18 Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S) Adamson, Chris L. Alexander, Bonnie Ball, Gareth Beare, Richard Cheong, Jeanie L. Y. Spittle, Alicia J. Doyle, Lex W. Anderson, Peter J. Seal, Marc L. Thompson, Deanne K. Sci Rep Article Longitudinal studies measuring changes in cortical morphology over time are best facilitated by parcellation schemes compatible across all life stages. The Melbourne Children’s Regional Infant Brain (M-CRIB) and M-CRIB 2.0 atlases provide voxel-based parcellations of the cerebral cortex compatible with the Desikan-Killiany (DK) and the Desikan-Killiany-Tourville (DKT) cortical labelling schemes. This study introduces surface-based versions of the M-CRIB and M-CRIB 2.0 atlases, termed M-CRIB-S(DK) and M-CRIB-S(DKT), with a pipeline for automated parcellation utilizing FreeSurfer and developing Human Connectome Project (dHCP) tools. Using T(2)-weighted magnetic resonance images of healthy neonates (n = 58), we created average spherical templates of cortical curvature and sulcal depth. Manually labelled regions in a subset (n = 10) were encoded into the spherical template space to construct M-CRIB-S(DK) and M-CRIB-S(DKT) atlases. Labelling accuracy was assessed using Dice overlap and boundary discrepancy measures with leave-one-out cross-validation. Cross-validated labelling accuracy was high for both atlases (average regional Dice = 0.79–0.83). Worst-case boundary discrepancy instances ranged from 9.96–10.22 mm, which appeared to be driven by variability in anatomy for some cases. The M-CRIB-S atlas data and automatic pipeline allow extraction of neonatal cortical surfaces labelled according to the DK or DKT parcellation schemes. Nature Publishing Group UK 2020-03-09 /pmc/articles/PMC7062836/ /pubmed/32152381 http://dx.doi.org/10.1038/s41598-020-61326-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Adamson, Chris L.
Alexander, Bonnie
Ball, Gareth
Beare, Richard
Cheong, Jeanie L. Y.
Spittle, Alicia J.
Doyle, Lex W.
Anderson, Peter J.
Seal, Marc L.
Thompson, Deanne K.
Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title_full Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title_fullStr Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title_full_unstemmed Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title_short Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S)
title_sort parcellation of the neonatal cortex using surface-based melbourne children’s regional infant brain atlases (m-crib-s)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062836/
https://www.ncbi.nlm.nih.gov/pubmed/32152381
http://dx.doi.org/10.1038/s41598-020-61326-2
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