Assessment of axial bone rigidity in rats with metabolic diseases using CT-based structural rigidity analysis

利用基于CT的结构刚度分析评估代谢性疾病大鼠的轴向骨刚度

阅读:1

Abstract

OBJECTIVES: This study aims to assess the correlation of CT-based structural rigidity analysis with mechanically determined axial rigidity in normal and metabolically diseased rat bone. METHODS: A total of 30 rats were divided equally into normal, ovariectomized, and partially nephrectomized groups. Cortical and trabecular bone segments from each animal underwent micro-CT to assess their average and minimum axial rigidities using structural rigidity analysis. Following imaging, all specimens were subjected to uniaxial compression and assessment of mechanically-derived axial rigidity. RESULTS: The average structural rigidity-based axial rigidity was well correlated with the average mechanically-derived axial rigidity results (R(2) = 0.74). This correlation improved significantly (p < 0.0001) when the CT-based Structural Rigidity Analysis (CTRA) minimum axial rigidity was correlated to the mechanically-derived minimum axial rigidity results (R(2) = 0.84). Tests of slopes in the mixed model regression analysis indicated a significantly steeper slope for the average axial rigidity compared with the minimum axial rigidity (p = 0.028) and a significant difference in the intercepts (p = 0.022). The CTRA average and minimum axial rigidities were correlated with the mechanically-derived average and minimum axial rigidities using paired t-test analysis (p = 0.37 and p = 0.18, respectively). CONCLUSIONS: In summary, the results of this study suggest that structural rigidity analysis of micro-CT data can be used to accurately and quantitatively measure the axial rigidity of bones with metabolic pathologies in an experimental rat model. It appears that minimum axial rigidity is a better model for measuring bone rigidity than average axial rigidity.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。