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首页> 美国卫生研究院文献>Springer Open Choice >Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments
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Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments

机译：使用从DXA图像重建的3D有限元模型预测股骨强度：针对实验的验证

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Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.
机译：基于计算机断层扫描（CT）的有限元（FE）模型可以通过提供股骨强度的估计来改善当前的骨质疏松症诊断和骨折风险的预测。然而，与传统的双能X线骨密度仪（DXA）用于骨质疏松症诊断的常规使用相反，CT扫描被认为是主要障碍。可以使用统计形状和外观模型（SSAM）和股骨的DXA图像重建股骨的3D形状和骨矿物质密度（BMD）分布。然后，可以使用重建的形状和BMD建立FE模型来预测骨骼强度。由于分析的所有步骤都需要高精度，因此本研究旨在评估由一张2D DXA图像构建的3D FE模型预测人类股骨的应变和骨折负荷的能力。取回了三具尸体股骨，可以进行离体力学测试的实验测量。 FE模型是使用基于SSAM的重建构建的：仅使用SSAM重建的形状，仅使用SSAM重建的BMD分布以及完整的基于SSAM的重建（包括形状和BMD分布）。与实验数据比较时，基于SSAM的模型可以准确预测主要应变（测定系数> 0.83，归一化均方根误差<16％）和股骨强度（估计值的标准误差1215 N）。这些结果仅略逊于基于CT的有限元模型，但具有从DXA图像构建的模型的显着优势。总而言之，结果支持基于SSAM的模型作为在当前骨折风险诊断中引入基于FE的骨强度估计的实用工具的可行性。

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