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A Combined Geometric Morphometric and Discrete Element Modeling Approach for Hip Cartilage Contact Mechanics

机译:髋关节软骨接触力学的组合几何形态学和离散元素建模方法

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Finite element analysis (FEA) provides the current reference standard for estimation of hip cartilage contact mechanics. Unfortunately, the development of subject-specific FEA models is a laborious process. Owed to its simplicity, Discrete Element Analysis (DEA) provides an attractive alternative to FEA. Advancements in computational morphometrics, specifically statistical shape modeling (SSM), provide the opportunity to predict cartilage anatomy without image segmentation, which could be integrated with DEA to provide an efficient platform to predict cartilage contact stresses in large populations. The objective of this study was, first, to validate linear and non-linear DEA against a previously validated FEA model and, second, to present and evaluate the applicability of a novel population-averaged cartilage geometry prediction method against previously used methods to estimate cartilage anatomy. The root mean squared error of the population-averaged cartilage geometry predicted by SSM as compared to the manually segmented cartilage geometry was 0.31 ± 0.08 mm. Identical boundary and loading conditions were applied to the DEA and FEA models. Predicted DEA stress distribution patterns and magnitude of peak stresses were in better agreement with FEA for the novel cartilage anatomy prediction method as compared to commonly used parametric methods. Still, contact stress was overestimated and contact area was underestimated for all cartilage anatomy prediction methods. Linear and nonlinear DEA methods differed mainly in peak stress results with the nonlinear definition being more sensitive to detection of high peak stresses. In conclusion, DEA in combination with the novel population-averaged cartilage anatomy prediction method provided more accurate predictions as compared to earlier methods, thus offering an efficient platform to conduct population-wide analyses of hip contact mechanics.
机译:有限元分析(FEA)提供了估计髋关节软骨接触力学的电流参考标准。不幸的是,特定主题的FEA模型的发展是一种艰苦的过程。欠其简单性,离散元素分析(DEA)为FEA提供了有吸引力的替代品。计算形态化学,特别是统计形状建模(SSM)的进步,提供了预测没有图像分割的软骨解剖学的机会,这可以与DEA集成,以提供一种有效的平台,以预测大群中的软骨接触应力。本研究的目的首先是针对先前验证的FEA模型验证线性和非线性DEA,而第二,以呈现和评估新颖的人口平均软骨几何形状预测方法对以前使用的方法来估算软骨的适用性解剖学。与手动分段的软骨几何形状相比,SSM预测的人口平均软骨几何形状的根部平均平方误差为0.31±0.08mm。将相同的边界和装载条件应用于DEA和FEA模型。与常用的参数化方法相比,预测的DEA应力分布模式和峰值应力的峰值应力更好地与FEA相一致。尽管如此,对所有软骨解剖预测方法低估接触应力并低估接触区域。线性和非线性DEA方法主要在峰值应力中不同,非线性定义对高峰应力的检测更敏感。总之,DEA与新颖的人口平均软骨解剖预测方法相结合,与前面的方法相比,提供了更准确的预测,从而提供了一种有效的平台,用于开展髋关节接触力学的人群分析。

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