Chen Xingyu, Zimmerman Brandon K, Lu X Lucas
Department of Mechanical Engineering, University of Delaware, Newark, Delaware.
Department of Mechanical Engineering, University of Delaware, Newark, Delaware.
J Biomech. 2015 Jan 2;48(1):176-80. doi: 10.1016/j.jbiomech.2014.10.036. Epub 2014 Nov 12.
Indentation testing is widely used to evaluate the mechanical properties of articular cartilage. However, most curve-fitting solutions for indentation analysis require the deformation data of cartilage at the equilibrium state, which often takes the tissue hours to reach. The lengthy testing time reduces the efficiency of indentation, increases the chance of tissue deterioration, and prevents in vivo applications. To overcome these limitations, a novel technique based on principal component analysis (PCA) was developed in this study, which can predict the full indentation creep curve based on the first few minutes' deformation history and the principal components. The accuracy of this technique was confirmed using the indentation data from 40 temporomandibular joint condylar cartilage samples and 17 bovine knee joint samples. The mechanical properties determined by biphasic curve-fitting using predicted and experimental data are in good agreement, with the difference between the two less than 5%. For TMJ and knee cartilages, it is found that any number of full tests beyond eight will not lead to any increase larger than 1% in the accuracy, indicating a low sample number required for prediction. In addition, the principal components of indentation creep curves are consistent for the same type of cartilage tested with identical protocols, but significantly different between two distinct cartilages. Therefore PCA may also represent a new method to compare the mechanical behaviors of different cartilages, as it avoids the assumptions associated with mechanical constitutive models and relies purely on the experimental data.
压痕测试被广泛用于评估关节软骨的力学性能。然而,大多数用于压痕分析的曲线拟合解决方案需要软骨在平衡状态下的变形数据,而这通常需要数小时才能达到。漫长的测试时间降低了压痕测试的效率,增加了组织退化的可能性,并阻碍了其在体内的应用。为了克服这些限制,本研究开发了一种基于主成分分析(PCA)的新技术,该技术可以根据最初几分钟的变形历史和主成分预测完整的压痕蠕变曲线。使用来自40个颞下颌关节髁突软骨样本和17个牛膝关节样本的压痕数据证实了该技术的准确性。使用预测数据和实验数据通过双相曲线拟合确定的力学性能吻合良好,两者之间的差异小于5%。对于颞下颌关节和膝关节软骨,发现超过8次的任何完整测试次数都不会使准确性提高超过1%,这表明预测所需的样本数量较少。此外,对于使用相同方案测试的同一类型软骨,压痕蠕变曲线的主成分是一致的,但在两种不同的软骨之间存在显著差异。因此,主成分分析也可能代表一种比较不同软骨力学行为的新方法,因为它避免了与力学本构模型相关联的假设,并且纯粹依赖于实验数据。