Human articular cartilage is orthotropic where microstructure, micromechanics, and chemistry vary with depth and split-line orientation. Issue 10 (October 2020) - Fischenich, K.M.; Wahlquist, J.A.; Wilmoth, R.L.; Cai, L.; Neu, C.P.; Ferguson, V.L.
Summary: Objective: Quantitative, micrometer length scale assessment of human articular cartilage is essential to enable progress toward new functional tissue engineering approaches, including utilization of emerging 3D bioprinting technologies, and for improved computational modeling of the osteochondral unit. Thus the objective of this study was to characterize the structural organization, material properties, and chemical composition of human skeletally mature articular cartilage with respect to depth and defined morphological features: normal to the articulating surface, parallel to the split-line, and transverse to the split-line. Method: Three samples from the lateral femoral condyles of 4 healthy adult donors (55–61 years old) were evaluated via histology, second harmonic generation, microindentation, and Raman spectroscopy. All metrics were evaluated as a function of depth and direction relative to the split-line. Results: All donors presented with intact and healthy tissue. Collagen fiber orientation varied significantly between testing directions and with increasing depth from the articular surface. Both compressive and tensile modulus increased significantly with depth and differed across the middle and deep zones and depended on orthogonal direction relative to the split-line. Similarly, matrix components varied with both depth and direction, where chondroitin sulfate steadily increased with depth while collagen prevalence was highest in the surface layer. Conclusions: Microscale measurements of human articular cartilage demonstrate that properties are both depth-dependent and orthotropic and depend on the underlying tissue structure and composition. These findings improve upon existing knowledge establishing more accurate measurements, with greater degree of depth and spatial specificity, as inputs for tissue engineering and computational modeling.