Department of Applied Physics, University of Eastern Finland, PO Box 1627, 70211 Kuopio, Finland.
Biomech Model Mechanobiol. 2012 Jul;11(6):791-800. doi: 10.1007/s10237-011-0352-9. Epub 2011 Oct 11.
Measurement of bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA) alone is only a moderate predictor of fracture risk. Finite element analysis (FEA) of bone mechanics, based on DXA images, may improve the prediction of fracture risk. We developed a method to estimate the 3D shape and density distribution of the proximal femur, using a 2D BMD image and a femur shape template. Proximal femurs of eighteen human cadavers were imaged using computed tomography and divided into two sets (N = 9 + 9). The template was created from the samples in first set by using 3D generalized Procrustes analysis and thin-plate splines. Subsequently, the template and 2D BMD image were utilized to estimate the shape and internal density distribution of the femurs in the second set. Finally, FEA was conducted based on the original and the estimated bone models to evaluate the effect of geometrical and density distributional errors on the mechanical strength. The volumetric errors induced by the estimation itself were low (<1.4%). In the estimation of bones in the second set, the mean distance difference between the estimated and the original bone surfaces was 0.80 ± 0.19 mm, suggesting feasible estimation of the femoral shape. The mean absolute error in voxel-by-voxel BMD was 120±8 mg cm⁻³. In FEA, the stiffness of the proximal femur differed by -7±16% between the original and estimated bones. The present method, in comparison with methods used in previous studies, improved the prediction of the geometry, the BMD distribution and the mechanical characteristics of the proximal femur. Potentially, the proposed method could ultimately improve the determination of bone fracture risk.
仅通过双能 X 射线吸收法（DXA）测量骨密度（BMD），仅能对骨折风险进行中等程度的预测。基于 DXA 图像的骨力学有限元分析（FEA），可能会提高骨折风险预测的准确性。我们开发了一种方法，通过使用二维 BMD 图像和股骨形状模板，来估计股骨近端的三维形状和密度分布。对 18 个人体尸体股骨进行计算机断层扫描成像，并将其分为两组（N = 9 + 9）。模板由第一组样本通过三维广义 Procrustes 分析和薄板样条法创建。随后，使用模板和二维 BMD 图像来估计第二组股骨的形状和内部密度分布。最后，基于原始和估计的骨骼模型进行 FEA，以评估几何形状和密度分布误差对机械强度的影响。估计本身引起的体积误差较低（<1.4%）。在第二组骨骼的估计中，估计骨骼表面与原始骨骼表面之间的平均距离差异为 0.80 ± 0.19mm，这表明股骨形状的估计是可行的。体素内 BMD 的平均绝对误差为 120±8mg cm⁻³。在 FEA 中，原始和估计骨骼之间的近端股骨刚度差异为-7±16%。与以前的研究中使用的方法相比，本方法提高了对近端股骨几何形状、BMD 分布和力学特性的预测能力。该方法有望最终提高对骨骨折风险的确定。
