用微计算机层析导出的有限元分析预测小鼠椎体强度。

BoneKEy reports Pub Date : 2015-04-22 eCollection Date: 2015-01-01 DOI:10.1038/bonekey.2015.31
Jeffry S Nyman, Sasidhar Uppuganti, Alexander J Makowski, Barbara J Rowland, Alyssa R Merkel, Julie A Sterling, Todd L Bredbenner, Daniel S Perrien
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引用次数: 24

摘要

在临床研究中,基于计算机断层扫描(CT)图像的有限元分析(FEA)在临床前啮齿动物研究中评估治疗对椎体(VB)强度的影响是有用的。由于microct衍生的有限元分析(μFEA)的强度预测尚未与小鼠VB强度的实验测量相验证,因此进行了一项参数分析,探索材料和破坏定义,以确定具有线性破坏标准的弹性μFEA是否可以合理地评估两项研究中的VB强度,治疗和遗传,对照组和实验组之间的骨体积分数差异。VBs以12 μm体素大小扫描,体素直接转换为8节点六面体元。当所有元素均质组织模量(E t)为18 GPa,破坏体积为2%,等效破坏应变为0.007时,从压缩试验中确定的预测VB强度与实验VB强度之间的决定系数或R(2)为62.3%,遗传研究为85.3%。当故障量降低到0.1%或增加到4%时,预测和测量之间的差异(即误差)增加。使用非均匀组织密度特异性模量,与均匀E =18 GPa相比,提高了预测强度与实验强度之间的R(2)。此外,非均匀材料的最佳破坏体积高于均匀材料定义。无论模型假设如何,μFEA都可以评估实验组之间小鼠VB强度的差异,当强度预期差异至少为20%时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Predicting mouse vertebra strength with micro-computed tomography-derived finite element analysis.

As in clinical studies, finite element analysis (FEA) developed from computed tomography (CT) images of bones are useful in pre-clinical rodent studies assessing treatment effects on vertebral body (VB) strength. Since strength predictions from microCT-derived FEAs (μFEA) have not been validated against experimental measurements of mouse VB strength, a parametric analysis exploring material and failure definitions was performed to determine whether elastic μFEAs with linear failure criteria could reasonably assess VB strength in two studies, treatment and genetic, with differences in bone volume fraction between the control and the experimental groups. VBs were scanned with a 12-μm voxel size, and voxels were directly converted to 8-node, hexahedral elements. The coefficient of determination or R (2) between predicted VB strength and experimental VB strength, as determined from compression tests, was 62.3% for the treatment study and 85.3% for the genetic study when using a homogenous tissue modulus (E t) of 18 GPa for all elements, a failure volume of 2%, and an equivalent failure strain of 0.007. The difference between prediction and measurement (that is, error) increased when lowering the failure volume to 0.1% or increasing it to 4%. Using inhomogeneous tissue density-specific moduli improved the R (2) between predicted and experimental strength when compared with uniform E t=18 GPa. Also, the optimum failure volume is higher for the inhomogeneous than for the homogeneous material definition. Regardless of model assumptions, μFEA can assess differences in murine VB strength between experimental groups when the expected difference in strength is at least 20%.

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