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A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography

The characterization of developmental phenotypes often relies on the accurate linear measurement of structures that are small and require laborious preparation. This is tedious and prone to errors, especially when repeated for the multiple replicates that are required for statistical analysis, or wh...

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Autores principales: Beltran Diaz, Santiago, H’ng, Chee Ho, Qu, Xinli, Doube, Michael, Nguyen, John Tan, de Veer, Michael, Panagiotopoulou, Olga, Rosello-Diez, Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8427701/
https://www.ncbi.nlm.nih.gov/pubmed/34513850
http://dx.doi.org/10.3389/fcell.2021.736574
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author Beltran Diaz, Santiago
H’ng, Chee Ho
Qu, Xinli
Doube, Michael
Nguyen, John Tan
de Veer, Michael
Panagiotopoulou, Olga
Rosello-Diez, Alberto
author_facet Beltran Diaz, Santiago
H’ng, Chee Ho
Qu, Xinli
Doube, Michael
Nguyen, John Tan
de Veer, Michael
Panagiotopoulou, Olga
Rosello-Diez, Alberto
author_sort Beltran Diaz, Santiago
collection PubMed
description The characterization of developmental phenotypes often relies on the accurate linear measurement of structures that are small and require laborious preparation. This is tedious and prone to errors, especially when repeated for the multiple replicates that are required for statistical analysis, or when multiple distinct structures have to be analyzed. To address this issue, we have developed a pipeline for characterization of long-bone length using X-ray microtomography (XMT) scans. The pipeline involves semi-automated algorithms for automatic thresholding and fast interactive isolation and 3D-model generation of the main limb bones, using either the open-source ImageJ plugin BoneJ or the commercial Mimics Innovation Suite package. The tests showed the appropriate combination of scanning conditions and analysis parameters yields fast and comparable length results, highly correlated with the measurements obtained via ex vivo skeletal preparations. Moreover, since XMT is not destructive, the samples can be used afterward for histology or other applications. Our new pipelines will help developmental biologists and evolutionary researchers to achieve fast, reproducible and non-destructive length measurement of bone samples from multiple animal species.
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spelling pubmed-84277012021-09-10 A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography Beltran Diaz, Santiago H’ng, Chee Ho Qu, Xinli Doube, Michael Nguyen, John Tan de Veer, Michael Panagiotopoulou, Olga Rosello-Diez, Alberto Front Cell Dev Biol Cell and Developmental Biology The characterization of developmental phenotypes often relies on the accurate linear measurement of structures that are small and require laborious preparation. This is tedious and prone to errors, especially when repeated for the multiple replicates that are required for statistical analysis, or when multiple distinct structures have to be analyzed. To address this issue, we have developed a pipeline for characterization of long-bone length using X-ray microtomography (XMT) scans. The pipeline involves semi-automated algorithms for automatic thresholding and fast interactive isolation and 3D-model generation of the main limb bones, using either the open-source ImageJ plugin BoneJ or the commercial Mimics Innovation Suite package. The tests showed the appropriate combination of scanning conditions and analysis parameters yields fast and comparable length results, highly correlated with the measurements obtained via ex vivo skeletal preparations. Moreover, since XMT is not destructive, the samples can be used afterward for histology or other applications. Our new pipelines will help developmental biologists and evolutionary researchers to achieve fast, reproducible and non-destructive length measurement of bone samples from multiple animal species. Frontiers Media S.A. 2021-08-26 /pmc/articles/PMC8427701/ /pubmed/34513850 http://dx.doi.org/10.3389/fcell.2021.736574 Text en Copyright © 2021 Beltran Diaz, H’ng, Qu, Doube, Nguyen, de Veer, Panagiotopoulou and Rosello-Diez. https://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) and the copyright owner(s) 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 Cell and Developmental Biology
Beltran Diaz, Santiago
H’ng, Chee Ho
Qu, Xinli
Doube, Michael
Nguyen, John Tan
de Veer, Michael
Panagiotopoulou, Olga
Rosello-Diez, Alberto
A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title_full A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title_fullStr A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title_full_unstemmed A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title_short A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography
title_sort new pipeline to automatically segment and semi-automatically measure bone length on 3d models obtained by computed tomography
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8427701/
https://www.ncbi.nlm.nih.gov/pubmed/34513850
http://dx.doi.org/10.3389/fcell.2021.736574
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