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Stochastic porous model of a bone-implant healing process using polynomial chaos expansion

机译:使用多项式混沌展开的骨-植入物愈合过程的随机多孔模型

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Porous material is used in engineering and biomedical structures, where the solid phase is the frame of the material and dissipation effects occur in the pores of the material. This work proposes a stochastic model of porous material to predict the bone tissue healing process in the early period after the implantation surgery. The bone implant is assumed to be axisymmetric and the healing process is evaluated up to 8 weeks after the implantation, which is validated by the canine experiments. The porous dynamic model is coupled with biochemical equations to take into account the osteoblast cells migration and the growth factors diffusion. Using the polynomial chaos expansion method, the effects of uncertain biochemical factors on the distribution of the new-formed tissue around the bone implant are examined. Compared with Monte Carlo simulations, the stochastic model can obtain high accuracy with greatly improved computational cost. The spatial-temporal model presented here provides a tool to evaluate the highly complex implant healing process and the influences of different biochemical factors.
机译:多孔材料用于工程和生物医学结构,其中固相是材料的框架,耗散效应发生在材料的孔中。这项工作提出了一种多孔材料的随机模型,以预测植入手术后早期骨组织的愈合过程。假定骨植入物是轴对称的,并且在植入后长达8周的时间内对愈合过程进行了评估,这已通过犬实验得到了验证。多孔动力学模型与生化方程式耦合,以考虑成骨细胞的迁移和生长因子的扩散。使用多项式混沌扩展方法,研究了不确定的生化因素对骨植入物周围新组织分布的影响。与蒙特卡洛模拟相比,该随机模型可以获得较高的精度,并且大大提高了计算成本。本文介绍的时空模型提供了一种评估高度复杂的植入物愈合过程以及不同生化因素影响的工具。

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