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Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice

Micro-computed tomography (μCT) is currently the gold standard for determining trabecular bone microstructure in small animal models. Numerous parameters associated with scanning and evaluation of μCT scans can strongly affect morphologic results obtained from bone samples. However, the effect of th...

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Autor principal: Christiansen, Blaine A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4926804/
https://www.ncbi.nlm.nih.gov/pubmed/27430011
http://dx.doi.org/10.1016/j.bonr.2016.05.006
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author Christiansen, Blaine A.
author_facet Christiansen, Blaine A.
author_sort Christiansen, Blaine A.
collection PubMed
description Micro-computed tomography (μCT) is currently the gold standard for determining trabecular bone microstructure in small animal models. Numerous parameters associated with scanning and evaluation of μCT scans can strongly affect morphologic results obtained from bone samples. However, the effect of these parameters on specific trabecular bone outcomes is not well understood. This study investigated the effect of μCT scanning with nominal voxel sizes between 6–30 μm on trabecular bone outcomes quantified in mouse vertebral body trabecular bone. Additionally, two methods for determining a global segmentation threshold were compared: based on qualitative assessment of 2D images, or based on quantitative assessment of image histograms. It was found that nominal voxel size had a strong effect on several commonly reported trabecular bone parameters, in particular connectivity density, trabecular thickness, and bone tissue mineral density. Additionally, the two segmentation methods provided similar trabecular bone outcomes for scans with small nominal voxel sizes, but considerably different outcomes for scans with larger voxel sizes. The Qualitatively Selected segmentation method more consistently estimated trabecular bone volume fraction (BV/TV) and trabecular thickness across different voxel sizes, but the Histogram segmentation method more consistently estimated trabecular number, trabecular separation, and structure model index. Altogether, these results suggest that high-resolution scans be used whenever possible to provide the most accurate estimation of trabecular bone microstructure, and that the limitations of accurately determining trabecular bone outcomes should be considered when selecting scan parameters and making conclusions about inter-group variance or between-group differences in studies of trabecular bone microstructure in small animals.
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spelling pubmed-49268042017-03-21 Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice Christiansen, Blaine A. Bone Rep Article Micro-computed tomography (μCT) is currently the gold standard for determining trabecular bone microstructure in small animal models. Numerous parameters associated with scanning and evaluation of μCT scans can strongly affect morphologic results obtained from bone samples. However, the effect of these parameters on specific trabecular bone outcomes is not well understood. This study investigated the effect of μCT scanning with nominal voxel sizes between 6–30 μm on trabecular bone outcomes quantified in mouse vertebral body trabecular bone. Additionally, two methods for determining a global segmentation threshold were compared: based on qualitative assessment of 2D images, or based on quantitative assessment of image histograms. It was found that nominal voxel size had a strong effect on several commonly reported trabecular bone parameters, in particular connectivity density, trabecular thickness, and bone tissue mineral density. Additionally, the two segmentation methods provided similar trabecular bone outcomes for scans with small nominal voxel sizes, but considerably different outcomes for scans with larger voxel sizes. The Qualitatively Selected segmentation method more consistently estimated trabecular bone volume fraction (BV/TV) and trabecular thickness across different voxel sizes, but the Histogram segmentation method more consistently estimated trabecular number, trabecular separation, and structure model index. Altogether, these results suggest that high-resolution scans be used whenever possible to provide the most accurate estimation of trabecular bone microstructure, and that the limitations of accurately determining trabecular bone outcomes should be considered when selecting scan parameters and making conclusions about inter-group variance or between-group differences in studies of trabecular bone microstructure in small animals. Elsevier 2016-05-27 /pmc/articles/PMC4926804/ /pubmed/27430011 http://dx.doi.org/10.1016/j.bonr.2016.05.006 Text en © 2016 The Author. Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Christiansen, Blaine A.
Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title_full Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title_fullStr Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title_full_unstemmed Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title_short Effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
title_sort effect of micro-computed tomography voxel size and segmentation method on trabecular bone microstructure measures in mice
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4926804/
https://www.ncbi.nlm.nih.gov/pubmed/27430011
http://dx.doi.org/10.1016/j.bonr.2016.05.006
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