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The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm

The application of micro-CT in small animal research, especially on bone health, has risen exponentially in recent years. However, its application in egg-laying hen bone analysis was still limited. This review introduces the technical aspects of micro-CT in egg-laying hen bone analysis, especially w...

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Autores principales: Chen, C., Kim, W.K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647928/
https://www.ncbi.nlm.nih.gov/pubmed/33142433
http://dx.doi.org/10.1016/j.psj.2020.08.047
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author Chen, C.
Kim, W.K.
author_facet Chen, C.
Kim, W.K.
author_sort Chen, C.
collection PubMed
description The application of micro-CT in small animal research, especially on bone health, has risen exponentially in recent years. However, its application in egg-laying hen bone analysis was still limited. This review introduces the technical aspects of micro-CT in egg-laying hen bone analysis, especially with the medullary bones presented in the cavity. In order to acquate application of micro-CT for laying hen bone research, image acquisition, reconstruction, and analysis settings need to be adjusted properly. The key difference regarding the application of micro-CT in laying hen bone compared to other small animals such as mice and rats was the larger bone size and more complex structures of medullary and trabecular bones. In order to analyze the details of laying hen bone structures, the volume of interest for laying hen should be selected at a region where all 3 bones are present (critical, trabecular, and medullary bone). Owing to the complexity of bone structures, the conventional techniques are not useful to distinguish the trabecular bone and medullary bone in laying hens accurately. In the current review, an automated segmentation algorithm is described to allow researchers to segment bone compartments without human bias. The algorithm is designed according to the morphology difference of medullary bones compared to trabecular and cortical bones. In this procedure, the loosely woven bones were separated by applying dual thresholds. The medullary calcium chunks were separated by opening or closing procedures, where we defined the diameter of medullary chunks being higher than the trabecular bone thickness as a separation trait. The application of micro-CT in laying hen bone health assessment will significantly expand our understanding of chicken bone physiology and osteoporosis, contributing to improve welfare in laying hens.
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spelling pubmed-76479282020-11-16 The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm Chen, C. Kim, W.K. Poult Sci Animal Well-Being and Behavior The application of micro-CT in small animal research, especially on bone health, has risen exponentially in recent years. However, its application in egg-laying hen bone analysis was still limited. This review introduces the technical aspects of micro-CT in egg-laying hen bone analysis, especially with the medullary bones presented in the cavity. In order to acquate application of micro-CT for laying hen bone research, image acquisition, reconstruction, and analysis settings need to be adjusted properly. The key difference regarding the application of micro-CT in laying hen bone compared to other small animals such as mice and rats was the larger bone size and more complex structures of medullary and trabecular bones. In order to analyze the details of laying hen bone structures, the volume of interest for laying hen should be selected at a region where all 3 bones are present (critical, trabecular, and medullary bone). Owing to the complexity of bone structures, the conventional techniques are not useful to distinguish the trabecular bone and medullary bone in laying hens accurately. In the current review, an automated segmentation algorithm is described to allow researchers to segment bone compartments without human bias. The algorithm is designed according to the morphology difference of medullary bones compared to trabecular and cortical bones. In this procedure, the loosely woven bones were separated by applying dual thresholds. The medullary calcium chunks were separated by opening or closing procedures, where we defined the diameter of medullary chunks being higher than the trabecular bone thickness as a separation trait. The application of micro-CT in laying hen bone health assessment will significantly expand our understanding of chicken bone physiology and osteoporosis, contributing to improve welfare in laying hens. Elsevier 2020-09-03 /pmc/articles/PMC7647928/ /pubmed/33142433 http://dx.doi.org/10.1016/j.psj.2020.08.047 Text en © 2020 Published by Elsevier Inc. on behalf of Poultry Science Association Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Animal Well-Being and Behavior
Chen, C.
Kim, W.K.
The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title_full The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title_fullStr The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title_full_unstemmed The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title_short The application of micro-CT in egg-laying hen bone analysis: introducing an automated bone separation algorithm
title_sort application of micro-ct in egg-laying hen bone analysis: introducing an automated bone separation algorithm
topic Animal Well-Being and Behavior
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647928/
https://www.ncbi.nlm.nih.gov/pubmed/33142433
http://dx.doi.org/10.1016/j.psj.2020.08.047
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