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微 CT 在蛋鸡骨骼分析中的应用:介绍一种自动化的骨骼分离算法。

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

机构信息

Department of Poultry Science, University of Georgia, Athens, GA 30602.

Department of Poultry Science, University of Georgia, Athens, GA 30602.

出版信息

Poult Sci. 2020 Nov;99(11):5175-5183. doi: 10.1016/j.psj.2020.08.047. Epub 2020 Sep 3.

Abstract

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.

摘要

微计算机断层扫描在小动物研究中的应用,特别是在骨骼健康方面,近年来呈指数级增长。然而,其在蛋鸡骨骼分析中的应用仍然有限。本文介绍了微计算机断层扫描在蛋鸡骨骼分析中的技术方面,特别是针对腔体内的髓骨。为了适当应用微计算机断层扫描进行蛋鸡骨骼研究,需要适当调整图像采集、重建和分析的设置。与其他小型动物(如小鼠和大鼠)相比,微计算机断层扫描在蛋鸡骨骼应用中的关键区别在于骨骼尺寸较大且骨髓和小梁骨的结构更为复杂。为了分析蛋鸡骨骼结构的细节,应在存在所有 3 种骨骼(皮质骨、小梁骨和髓骨)的感兴趣区域选择蛋鸡的感兴趣区域。由于骨骼结构的复杂性,传统技术无法准确区分蛋鸡的小梁骨和髓骨。在本综述中,描述了一种自动化分割算法,允许研究人员在没有人为偏见的情况下分割骨骼区域。该算法是根据与皮质骨和小梁骨相比髓骨的形态差异设计的。在该程序中,通过应用双重阈值将疏松编织的骨骼分开。通过开闭操作将髓骨钙块分开,其中我们将髓骨块的直径定义为高于小梁骨厚度的分离特征。微计算机断层扫描在蛋鸡骨骼健康评估中的应用将极大地扩展我们对鸡骨骼生理学和骨质疏松症的理解,有助于提高蛋鸡福利。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2f0/7647928/9222dea46c33/gr1.jpg

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