Department of Mechanical Engineering, University of Alberta, Canada.
Comput Methods Programs Biomed. 2010 Aug;99(2):154-71. doi: 10.1016/j.cmpb.2009.11.009. Epub 2009 Dec 21.
Properly representing the heterogeneous distribution of bone tissue material properties is a key step in constructing subject-specific finite element (FE) bone models from computed tomography (CT) data. Conventional methods represent heterogeneity by subjectively grouping bone of similar attenuation together. A new technique characterizing the level of heterogeneity with an objective metric is presented. This technique identifies the minimal level of heterogeneity needed for an accurate FE model. Subject-specific models of the distal femur and proximal tibia were used in this study. An innovative application of an image processing technique in the context of material properties modeling was introduced to facilitate an objective grouping strategy, which gathered together bone based not only on density but also on location thus capturing the natural variation of bone density seen in CT images. A fully heterogeneous model containing unique material properties for each finite element was not necessary to generate an appropriate solution. Von Mises stress, strain energy density, and nodal displacements were predicted within 5% accuracy using a simplified FE femur model containing less than half the number of bone groups of the fully heterogeneous model. Each group contained attenuations varying less than 20% from the group mean. A substantial computational time savings of 60% was gained with the application of the new technique to assign bone mechanical properties.
从 CT 数据构建特定于个体的有限元 (FE) 骨骼模型的关键步骤是正确表示骨骼组织材料属性的异质性分布。传统方法通过主观地将相似衰减的骨骼分组来表示异质性。提出了一种用客观指标来描述异质性程度的新技术。该技术确定了构建准确 FE 模型所需的最小异质程度。本研究使用了特定于个体的股骨远端和胫骨近端模型。本文创新性地将图像处理技术应用于材料属性建模中，以促进一种客观的分组策略，该策略不仅基于密度，还基于位置对骨骼进行分组，从而捕捉到 CT 图像中观察到的骨骼密度的自然变化。使用简化的 FE 股骨模型，其中包含的骨骼组数量不到全异质模型的一半，并且每个组的衰减值与组平均值相差小于 20%，即可在预测的 Von Mises 应力、应变能密度和节点位移的精度在 5%以内，生成适当的解决方案。通过应用新技术来分配骨骼力学特性，可节省 60%的计算时间。
