University of Michigan and Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai, China.
Department of Automation, Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China.
Med Eng Phys. 2019 Sep;71:3-9. doi: 10.1016/j.medengphy.2019.06.022. Epub 2019 Jul 19.
Computational foot models have significant application in surgical decision making, injury and disease diagnosis and prevention, sports performance analysis and footwear engineering. However, due to the substantial time in model building and the heavy computational costs from the complexity of the models, daily clinical application of these foot models has yet to be achieved. Much of the previous research adopted a detailed-geometry approach in modeling bones that potentially contributed to the heavy computational costs. In this research, we developed a computational talus model based on CT section image data, image reconstruction and segmentation, contact surface identification, standard shape fitting, and finite element auto meshing algorithms. Modeling the bones as rigid is common, and modeling the contact surfaces only for the rigid body saves additional computational resources. Priority, therefore, in the shape fitting with optimization is given to the contact surfaces of the talus. Thirteen sets (9 males and 4 females) of CT section data were obtained. Image reconstruction, segmentation and bone labeling were conducted on each set of CT data to identify talus and its adjacent bones. Contact surfaces of the talus were then identified based on bone spatial relationships. Apart from the talar dome surface which was fitted by a 3rd-order polynomial, standard shapes such as ellipsoids and planes were used to fit the selected contact surfaces so that the geometrical parameters maintain physical significance. Based on these parameters, we automatically recreated and meshed the least-squares fitted shapes rapidly with limited elements. Last, mean major contact surfaces of the talus were obtained and fitted by standard shapes. Although the number of samples in this study was relatively small, our method provides sufficient and accurate geometric parameters of these contact surfaces to completely describe and reproduce the talus, on both a subject specific and average basis. The method for describing the talus here helps to parametrize computational models using planes and ellipsoids, improves surgical decision making and implants with a more precise and physically significant measures, and the description provides bone geometric parameters which can later be used to relate risk analysis for bone shape specific injury rates.
计算足部模型在手术决策、损伤和疾病诊断与预防、运动表现分析和鞋类工程中具有重要应用。然而，由于模型构建需要大量时间，且模型的复杂性导致计算成本高昂，这些足部模型目前还无法在日常临床中应用。之前的许多研究在建模骨骼时采用了详细几何形状的方法，这可能导致了计算成本的增加。在本研究中，我们基于 CT 切片图像数据、图像重建和分割、接触面识别、标准形状拟合以及有限元自动网格划分算法，开发了一种计算距骨模型。将骨骼建模为刚性是常见的，仅对刚体建模接触面可以节省额外的计算资源。因此，在优化形状拟合时，距骨的接触面是优先考虑的。我们获得了 13 组（9 名男性和 4 名女性）CT 切片数据。对每一组 CT 数据进行图像重建、分割和骨骼标记，以识别距骨及其相邻骨骼。然后根据骨骼的空间关系识别距骨的接触面。除了用三次多项式拟合距骨穹顶表面外，还使用标准形状（如椭圆和平面）拟合选定的接触面，使几何参数保持物理意义。基于这些参数，我们使用有限元自动快速重建和网格拟合最小二乘拟合形状。最后，获得距骨的平均主要接触面，并使用标准形状进行拟合。虽然本研究的样本数量相对较少，但我们的方法提供了足够和准确的这些接触面的几何参数，可以完整地描述和再现距骨，无论是基于特定个体还是平均情况。本研究中描述距骨的方法有助于使用平面和椭圆对计算模型进行参数化，以更精确和具有物理意义的测量值来改善手术决策和植入物，并提供骨骼几何参数，这些参数可以用于与特定骨骼形状的损伤率相关的风险分析。
