The meniscus is crucial in maintaining knee function and protecting the joint from secondary pathologies, including osteoarthritis. The meniscus has been shown to absorb up to 75% of the total load on the knee joint. Mechanical behavior of meniscal tissue in compression can be predicted by quantifying the mechanical parameters including; aggregate modulus (H) and Poisson modulus (ν), and the fluid transport parameter: hydraulic permeability (K). These parameters are crucial to develop a computational model of the tissue and for the design and development of tissue engineered scaffolds mimicking the native tissue. Hence, the objective of this study was to characterize the mechanical and fluid transport properties of human meniscus and relate them to the tissue composition. Specimens were prepared from the axial and the circumferential anatomical planes of the tissue. Stress relaxation tests yielded the H, while finite element modeling was used to curve fit for ν and K. Correlations of moduli with water and glycosaminoglycans (GAGs) content were investigated. On average H was found to be 0.11 ± 0.078 MPa, ν was 0.32 ± 0.057, and K was 2.9 ± 2.27 × 10−15 m4N−1s−1. The parameters H, ν, and K were not found to be statistically different across compression orientation or compression level. Water content of the tissue was 77 ± 3.3% while GAG content was 8.79 ± 1.1%. Interestingly, a weak negative correlation was found between H and water content (R2 ~ 34%) and a positive correlation between K and GAG content (R2 ~ 53%). In conclusion, while no significant differences in transport and compressive properties can be found across sample orientation and compression levels, data trends suggest potential relationships between magnitudes of H and K, and GAG content.
CITATION STYLE
Morejon, A., Norberg, C. D., De Rosa, M., Best, T. M., Jackson, A. R., & Travascio, F. (2021). Compressive Properties and Hydraulic Permeability of Human Meniscus: Relationships With Tissue Structure and Composition. Frontiers in Bioengineering and Biotechnology, 8. https://doi.org/10.3389/fbioe.2020.622552
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