Predicting cortical bone adaptation to axial loading in the mouse tibia.
Predicting cortical bone adaptation to axial loading in the mouse tibia.
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DOI：
10.1098/rsif.2015.0590
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发表时间：
2015-09-06
期刊：
影响因子：
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通讯作者：
Shefelbine SJ
中科院分区：
文献类型：
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作者：
Pereira AF;Javaheri B;Pitsillides AA;Shefelbine SJ
预测数学模型的发展有助于更深入地了解骨机械生物学的特定阶段和骨适应机械力的过程。这项工作的目的是预测，空间精度，皮质骨适应机械负荷，以更好地了解可能是驱动适应的机械线索。使用轴向胫骨载荷模型来触发C57 BL/6小鼠中的皮质骨适应，并提供相关的生物学和生物力学信息。开发了一种绘制小鼠胫骨骨干皮质厚度的方法，可以对骨适应发生的位置进行全面的空间描述。使用多孔弹性有限元（FE）模型确定胫骨在轴向载荷和间质流体速度作为机械刺激时的结构响应。有限元模型与机械生物学控制方程相耦合，该方程考虑了非静态载荷，并假设骨骼以开-关方式对局部机械提示立即做出响应。所提出的公式能够模拟适应区域并准确地再现实验数据中观察到的皮质增厚分布，且具有统计学显着的正相关性（肯德尔τ等级系数τ = 0.51，p < 0.001）。这项工作表明，计算模型可以在空间上预测皮质骨mechanoadaptation随时间变化的刺激。这种模型可以用于设计更有效的加载方案和靶向相关生理机制的药物治疗。
The development of predictive mathematical models can contribute to a deeper understanding of the specific stages of bone mechanobiology and the process by which bone adapts to mechanical forces. The objective of this work was to predict, with spatial accuracy, cortical bone adaptation to mechanical load, in order to better understand the mechanical cues that might be driving adaptation. The axial tibial loading model was used to trigger cortical bone adaptation in C57BL/6 mice and provide relevant biological and biomechanical information. A method for mapping cortical thickness in the mouse tibia diaphysis was developed, allowing for a thorough spatial description of where bone adaptation occurs. Poroelastic finite-element (FE) models were used to determine the structural response of the tibia upon axial loading and interstitial fluid velocity as the mechanical stimulus. FE models were coupled with mechanobiological governing equations, which accounted for non-static loads and assumed that bone responds instantly to local mechanical cues in an on–off manner. The presented formulation was able to simulate the areas of adaptation and accurately reproduce the distributions of cortical thickening observed in the experimental data with a statistically significant positive correlation (Kendall's τ rank coefficient τ = 0.51, p < 0.001). This work demonstrates that computational models can spatially predict cortical bone mechanoadaptation to a time variant stimulus. Such models could be used in the design of more efficient loading protocols and drug therapies that target the relevant physiological mechanisms.