Ulrich D, van Rietbergen B, Laib A, Rüegsegger P
Institute for Biomedical Engineering, University of Zürich and Swiss Federal Institute of Technology (ETH).
J Biomech. 1999 Aug;32(8):821-8. doi: 10.1016/s0021-9290(99)00062-7.
Prevention of osteoporotic bone fractures requires accurate diagnostic methods to detect the increase in bone fragility at an early stage of osteoporosis. However, today's bone fracture risk prediction, primarily based on bone density measurement, is not sufficiently precise. There is increasing evidence that, in addition to bone density, also the bone microarchitecture and its mechanical loading conditions are important factors determining the fracture risk. Recently, it has been shown that new high-resolution imaging techniques in combination with new computer modeling techniques based on the finite-element (FE) method can account for these additional factors. These techniques might provide information that is more relevant for the prediction of bone fracture risk. So far, however, these new imaged-based FE techniques have not been feasible in-vivo. The objectives of this study were to quantify the load transfer through the trabecular network in a distal radius using a computer model based on in-vivo high-resolution images and to determine if common regions of fractures can be explained as a result of high tissue loading in these regions. The left distal radius and the two adjacent carpal bones of a healthy volunteer were imaged using a high-resolution three-dimensional CT system providing an isotropic resolution of 165 microm. The bone representation was converted into a FE-model that was used to calculate stresses and strains in the trabecular network. The two carpal bones were loaded using different load ratios (for each load case 1000 N in total) representing impact forces on the hand either in near-neutral position or ulnar/radial deviation. The load transfer through the trabecular network of the radius was characterized by the tissue strain energy density (SED) distribution for all load cases. It was found that the distribution of the tissue loading depends on the ratio of the forces acting on the carpal bones. For all load cases the higher SED values (on average: 0.02 +/- 0.08 (S.D.) N mm(-2)) are found in a 10 mm region adjacent to the articular surface which corresponds well with the region where Colles- or Chauffeur-fractures occur. We expect that, eventually, this new approach can lead to a better prediction of the fracture risk than methods based on bone density alone since it accounts for the bone microstructure as well as its loading conditions.
预防骨质疏松性骨折需要准确的诊断方法,以便在骨质疏松症的早期阶段检测到骨脆性增加。然而,当今主要基于骨密度测量的骨折风险预测不够精确。越来越多的证据表明,除了骨密度外,骨微结构及其机械负荷条件也是决定骨折风险的重要因素。最近的研究表明,基于有限元(FE)方法的新的高分辨率成像技术与新的计算机建模技术相结合,可以考虑这些额外因素。这些技术可能会提供与骨折风险预测更相关的信息。然而,到目前为止,这些基于成像的新有限元技术尚未在体内实现。本研究的目的是使用基于体内高分辨率图像的计算机模型量化桡骨远端小梁网络的负荷传递,并确定骨折的常见区域是否可以解释为这些区域的高组织负荷所致。使用高分辨率三维CT系统对一名健康志愿者的左桡骨远端和两个相邻腕骨进行成像,该系统提供165微米的各向同性分辨率。将骨模型转换为有限元模型,用于计算小梁网络中的应力和应变。使用不同的负荷比(每种负荷情况总计1000 N)对两个腕骨进行加载,分别代表手部在接近中立位置或尺侧/桡侧偏斜时的冲击力。通过所有负荷情况下的组织应变能密度(SED)分布来表征桡骨小梁网络的负荷传递。结果发现,组织负荷的分布取决于作用在腕骨上的力的比例。在所有负荷情况下,在与关节面相邻的10毫米区域内发现较高的SED值(平均:0.02±0.08(标准差)N·mm-2),这与Colles骨折或Chauffeur骨折发生的区域非常吻合。我们预计,最终这种新方法能够比仅基于骨密度的方法更好地预测骨折风险,因为它考虑了骨微结构及其负荷条件。