Isaksson Hanna, van Donkelaar Corrinus C, Huiskes Rik, Ito Keita
AO Research Institute, Clavadelerstrasse, 87270 Davos Platz, Switzerland.
J Orthop Res. 2006 May;24(5):898-907. doi: 10.1002/jor.20118.
Several mechanoregulation algorithms proposed to control tissue differentiation during bone healing have been shown to accurately predict temporal and spatial tissue distributions during normal fracture healing. As these algorithms are different in nature and biophysical parameters, it raises the question of which reflects the actual mechanobiological processes the best. The aim of this study was to resolve this issue by corroborating the mechanoregulatory algorithms with more extensive in vivo bone healing data from animal experiments. A poroelastic three-dimensional finite element model of an ovine tibia with a 2.4 mm gap and external callus was used to simulate the course of tissue differentiation during fracture healing in an adaptive model. The mechanical conditions applied were similar to those used experimentally, with axial compression or torsional rotation as two distinct cases. Histological data at 4 and 8 weeks, and weekly radiographs, were used for comparison. By applying new mechanical conditions, torsional rotation, the predictions of the algorithms were distinguished successfully. In torsion, the algorithms regulated by strain and hydrostatic pressure failed to predict healing and bone formation as seen in experimental data. The algorithm regulated by deviatoric strain and fluid velocity predicted bridging and healing in torsion, as observed in vivo. The predictions of the algorithm regulated by deviatoric strain alone did not agree with in vivo data. None of the algorithms predicted patterns of healing entirely similar to those observed experimentally for both loading modes. However, patterns predicted by the algorithm based on deviatoric strain and fluid velocity was closest to experimental results. It was the only algorithm able to predict healing with torsional loading as seen in vivo.
为控制骨愈合过程中的组织分化而提出的几种机械调节算法，已被证明能准确预测正常骨折愈合过程中的时间和空间组织分布。由于这些算法在性质和生物物理参数上有所不同，这就引发了一个问题：哪种算法最能反映实际的机械生物学过程。本研究的目的是通过将机械调节算法与来自动物实验的更广泛的体内骨愈合数据进行对比，来解决这个问题。使用一个具有2.4毫米间隙和外骨痂的绵羊胫骨的多孔弹性三维有限元模型，在一个自适应模型中模拟骨折愈合过程中的组织分化过程。所施加的力学条件与实验中使用的条件相似，以轴向压缩或扭转旋转作为两种不同情况。使用4周和8周时的组织学数据以及每周的X光片进行比较。通过应用新的力学条件——扭转旋转，算法的预测结果得到了成功区分。在扭转情况下，由应变和静水压力调节的算法未能预测出实验数据中所见的愈合和骨形成情况。由偏应变和流体速度调节的算法预测出了扭转情况下的骨桥形成和愈合情况，这与体内观察结果一致。仅由偏应变调节的算法的预测结果与体内数据不一致。对于两种加载模式，没有一种算法预测出的愈合模式与实验观察到的完全相似。然而，基于偏应变和流体速度的算法预测的模式最接近实验结果。它是唯一能够预测出体内所见扭转加载情况下愈合情况的算法。
