Hodgskinson R, Currey J D
Department of Biology, University of York.
Proc Inst Mech Eng H. 1990;204(2):115-21. doi: 10.1243/PIME_PROC_1990_204_240_02.
The Young's modulus of cubes of human cancellous bone was measured in three orthogonal directions. Apparent density and mineral volume fraction were also measured, as were two architectural variables, fabric and connectivity, which were determined using image analysis techniques. Multiple regression was used to relate the Young's modulus to the four explanatory variables. The results from this study are compared with those obtained from a previous investigation using non-human cancellous bone. The relationships revealed by the two studies are very similar. It was possible to explain approximately 93 per cent of the variance in Young's modulus using the four variables in this present study. Apparent density is the major explanatory variable in both studies and shows a strong correlation with connectivity. In common with the non-human study the measure of fabric is a worthwhile explanatory variable; however, connectivity and mineral volume fraction are relatively unimportant. The four explanatory variables contribute to a successful model for the prediction of Young's modulus. Any other candidate variables are likely to be unimportant or be highly correlated with those already investigated.
在三个正交方向上测量了人类松质骨立方体的杨氏模量。还测量了表观密度和矿物质体积分数，以及两个结构变量——结构和连通性，这两个变量是使用图像分析技术确定的。使用多元回归将杨氏模量与这四个解释变量联系起来。将本研究的结果与先前使用非人类松质骨的调查结果进行了比较。两项研究揭示的关系非常相似。在本研究中，使用这四个变量可以解释约93%的杨氏模量方差。表观密度在两项研究中都是主要的解释变量，并且与连通性显示出很强的相关性。与非人类研究一样，结构测量是一个有价值的解释变量；然而，连通性和矿物质体积分数相对不重要。这四个解释变量有助于建立一个预测杨氏模量的成功模型。任何其他候选变量可能不重要，或者与已经研究过的变量高度相关。
