Levchuk Alina, Zwahlen Alexander, Weigt Claudia, Lambers Floor M, Badilatti Sandro D, Schulte Friederike A, Kuhn Gisela, Müller Ralph
Institute for Biomechanics, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland.
Institute for Biomechanics, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich, Switzerland.
Clin Biomech (Bristol). 2014 Apr;29(4):355-62. doi: 10.1016/j.clinbiomech.2013.12.019. Epub 2014 Jan 10.
Microstructural simulations of bone remodeling are particularly relevant in the clinical management of osteoporosis. Before a model can be applied in the clinics, a validation against controlled in vivo data is crucial. Here we present a strain-adaptive feedback algorithm for the simulation of trabecular bone remodeling in response to loading and pharmaceutical treatment and report on the results of the large-scale validation against in vivo data.
The algorithm follows the mechanostat principle and incorporates mechanical feedback, based on the local strain-energy density. For the validation, simulations of bone remodeling and adaptation in 180 osteopenic mice were performed. Permutations of the conditions for early (20th week) and late (26th week) loading of 8N or 0N, and treatments with bisphosphonates, or parathyroid hormone were simulated. Static and dynamic morphometry and local remodeling sites from in vivo and in silico studies were compared.
For each study an individual set of model parameters was selected. Trabecular bone volume fraction was chosen as an indicator of the accuracy of the simulations. Overall errors for this parameter were 0.1-4.5%. Other morphometric indices were simulated with errors of less than 19%. Dynamic morphometry was more difficult to predict, which resulted in significant differences from the experimental data.
We validated a new algorithm for the simulation of bone remodeling in trabecular bone. The results indicate that the simulations accurately reflect the effects of treatment and loading seen in respective experimental data, and, following adaptation to human data, could be transferred into clinics.
骨重塑的微观结构模拟在骨质疏松症的临床管理中尤为重要。在模型应用于临床之前，与受控的体内数据进行验证至关重要。在此，我们提出一种应变自适应反馈算法，用于模拟小梁骨对加载和药物治疗的重塑，并报告针对体内数据进行大规模验证的结果。
该算法遵循机械稳态原理，并基于局部应变能密度纳入机械反馈。为进行验证，对180只骨质减少小鼠的骨重塑和适应性进行了模拟。模拟了8N或0N的早期（第20周）和晚期（第26周）加载条件，以及双膦酸盐或甲状旁腺激素治疗的各种组合。比较了体内和计算机模拟研究中的静态和动态形态计量学以及局部重塑部位。
针对每项研究选择了一组单独的模型参数。选择小梁骨体积分数作为模拟准确性的指标。该参数的总体误差为0.1 - 4.5%。其他形态计量指标的模拟误差小于19%。动态形态计量学更难预测，这导致与实验数据存在显著差异。
我们验证了一种用于模拟小梁骨重塑的新算法。结果表明，模拟准确反映了各自实验数据中所见的治疗和加载效果，并且在适应人类数据后，可应用于临床。
