Biphasic Finite Element Modeling Reconciles Mechanical Properties of Engineered Cartilage Constructs Derived from Different Testing Modalities

Introduction Cartilage is a hydrated, load bearing and specialized tissue with unique biomechanical properties. Given its poor healing capacity, a number of tissue engineering and regenerative medicine strategies have emerged to address the repair of large cartilage defects. There has been significant Progress in this field, with various scaffolds, preconditioning bioreactors, and cell types generating cartilage-like tissue in vitro whose bulk properties approach that of native cartilage. Attention has now turned towards fabrication of engineered cartilage with anatomic curvature to reconstitute complex joint geometries, as well as evaluation of biophysical properties of engineered constructs in vivo. While a number of standard mechanical assays (e.g., confined and unconfined compression) are used to assess mechanical function of native tissue and engineered constructs, these assays generally require samples of regular geometry and assume homogenous material properties across the test specimen. These are generally not compatible with complex anatomic constructs maturing in an in vivo setting. As a consequence, indentation testing, using either spherical or plane-ended indenters, is the standard analysis tool for in vivo analysis. Given the dissimilarity in testing profiles and boundary conditions across these testing configurations, however, reported ‘moduli’ can differ by as much as an order of magnitude. To address this disconnect, we developed a biphasic finite element model using the freeware FEBio representing two common testing configurations (indentation and unconfined compression). The goal of this study was to develop this methodology and evaluate the maturation of tissue engineered constructs using these testing configurations side-byside, and to determine whether the FE models and curve fitting procedures could provide a reconciled set of mechanical properties across testing platforms.