Depth-dependent compressive equilibrium properties of articular cartilage explained by its composition

Depth-dependent compressive equilibrium properties of articular cartilage explained by its composition
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DOI:
10.1007/s10237-006-0044-z
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发表时间:
2007-01-01
影响因子:
3.5
通讯作者:
van Donkelaar, C. C.
van Donkelaar, C. C.
中科院分区:
工程技术2区
文献类型:
--
作者:
Wilson, W.;Huyghe, J. M.;van Donkelaar, C. C.

文献摘要

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在这项研究中,我们假设关节软骨的深度依赖性压缩平衡特性是其深度依赖性组成的固有结果,而不是深度依赖性材料特性的结果。为了验证这一假设,我们最近开发的原纤维增强多孔粘弹性膨胀模型扩展到包括内和外原纤维水含量的影响,和组织的压缩性能上的固体分数的影响。利用该模型,确定了关节软骨的深度相关压缩平衡特性,并与文献中的实验数据进行了比较。该模型预测了关节软骨典型的深度依赖行为。有效骨料模量是高度应变依赖性。在低应变下,它随应变的增大而减小,在高应变下,它随应变的增大而增大。随着与关节面距离的增加,这种效应更加明显。这项研究的主要见解是,关节软骨的深度依赖性材料行为可以从其深度依赖性成分获得。这就消除了假设不同组分的材料性质随深度变化的需要。这些见解对于理解软骨力学行为、软骨损伤机制和组织工程研究具有重要意义。
For this study, we hypothesized that the depth-dependent compressive equilibrium properties of articular cartilage are the inherent consequence of its depth-dependent composition, and not the result of depth-dependent material properties. To test this hypothesis, our recently developed fibril-reinforced poroviscoelastic swelling model was expanded to include the influence of intra- and extra-fibrillar water content, and the influence of the solid fraction on the compressive properties of the tissue. With this model, the depth-dependent compressive equilibrium properties of articular cartilage were determined, and compared with experimental data from the literature. The typical depth-dependent behavior of articular cartilage was predicted by this model. The effective aggregate modulus was highly strain-dependent. It decreased with increasing strain for low strains, and increases with increasing strain for high strains. This effect was more pronounced with increasing distance from the articular surface. The main insight from this study is that the depth-dependent material behavior of articular cartilage can be obtained from its depth-dependent composition only. This eliminates the need for the assumption that the material properties of the different constituents themselves vary with depth. Such insights are important for understanding cartilage mechanical behavior, cartilage damage mechanisms and tissue engineering studies.