Should a native depth-dependent distribution of human meniscus constitutive components be considered in FEA-models of the knee joint?

The depth-dependent matrix composition of articular cartilage is important for its mechanical behavior. It is unknown whether the depth-dependent matrix composition of a meniscus is similarly important for its load-bearing function. The present objective was to determine whether it is necessary to account for the native distribution of matrix components in the cross-sectional plane of the meniscus, when studying its mechanical behavior in numerical models. To address this objective, measured depth-dependent distribution of matrix contents in the human meniscus, and fitted visco-elastic mechanical properties of the collagen were used as input in FEA simulations of a knee joint. The importance of including the depth-dependent matrix component constitution in the meniscus was determined by comparing simulations with an axisymmetric representation of the knee joint, which incorporated either the depth-dependent matrix composition or homogenized matrix. Depth-dependent differences in water, collagen and proteoglycan contents were observed, but these were not significantly different. The anterior region, with significantly higher collagen content, was statistically stiffer than the posterior region. However, depth wise, stiffness did not correlate to the constitution of the tissue. GAG content was significantly higher in the posterior than in the anterior region. Visco-elastic properties of meniscus collagen were fitted against tensile test data. Simulations show that the distribution of stresses and strains in the cartilage is slightly low when the meniscus contains a depth-dependent constitution, but this difference is only modest. Therefore, this study suggests that knee joint mechanics is rather insensitive to the distribution of constitutive components in the cross section of the meniscus, and that the depth-dependent matrix distribution of the meniscus is not essential to be included in axisymmetric computational models of the knee joint.