Giorgi M, Dall'Ara E
Department of Oncology and Metabolism, Mellanby Centre for Bone Research, University of Sheffield, UK; INSIGNEO Institute for in Silico Medicine, University of Sheffield, UK; Certara QSP, Certara UK Limited, Simcyp Division, Sheffield, UK.
Department of Oncology and Metabolism, Mellanby Centre for Bone Research, University of Sheffield, UK; INSIGNEO Institute for in Silico Medicine, University of Sheffield, UK.
Med Eng Phys. 2018 Dec;62:7-16. doi: 10.1016/j.medengphy.2018.09.001. Epub 2018 Sep 20.
It is well known that bone has an enormous adaptive capacity to mechanical loadings, and to this extent, several in vivo studies on mouse tibia use established cyclic compressive loading protocols to investigate the effects of mechanical stimuli. In these experiments, the applied axial load is well controlled but the positioning of the hind-limb between the loading endcaps may dramatically affect the strain distribution induced on the tibia. In this study, the full field strain distribution induced by a typical in vivo setup on mouse tibiae was investigated through a combination of in situ compressive testing, µCT scanning and a global digital volume correlation (DVC) approach. The precision of the DVC method and the effect of repositioning on the strain distributions were evaluated. Acceptable uncertainties of the DVC approach for the analysis of loaded tibiae (411 ± 58µɛ) were found for nodal spacing of approximately 50 voxels (520 µm). When pairs of in situ preloaded and loaded images were registered, low variability of the strain distributions within the tibia were seen (range of mean differences in principal strains: 585-1800µɛ). On contrary, larger differences were seen after repositioning (range of mean differences in principal strains: 2500-5500µɛ). To conclude, these preliminary results on thee specimens showed that the DVC approach applied to the mouse tibia can be precise enough to evaluate local strain distributions under loads, and that repositioning of the hind-limb within the testing machine can induce large differences in the strain distributions that should be accounted for when modelling this system.
众所周知,骨骼对机械负荷具有巨大的适应能力,在这个层面上,多项针对小鼠胫骨的体内研究采用既定的循环压缩负荷方案来研究机械刺激的影响。在这些实验中,施加的轴向负荷得到了很好的控制,但后肢在加载端盖之间的定位可能会极大地影响胫骨上诱导的应变分布。在本研究中,通过原位压缩测试、μCT扫描和全局数字体积相关(DVC)方法相结合,研究了典型体内设置在小鼠胫骨上诱导的全场应变分布。评估了DVC方法的精度以及重新定位对应变分布的影响。对于大约50体素(520μm)的节点间距,发现DVC方法用于分析加载胫骨时的可接受不确定性为(411±58µɛ)。当对原位预加载和加载图像进行配准时,胫骨内应变分布的变异性较低(主应变平均差异范围:585 - 1800µɛ)。相反,重新定位后差异更大(主应变平均差异范围:2500 - 5500µɛ)。总之,这些对三个样本的初步结果表明,应用于小鼠胫骨的DVC方法能够精确到足以评估负荷下的局部应变分布,并且后肢在测试机内的重新定位会在应变分布中引起很大差异,在对该系统进行建模时应予以考虑。