Explicit Finite Element Modeling of Knee Mechanics During Simulated Dynamic Activities

The natural knee is one of the most commonly injured joints in the body due to relatively high loads and motions that can lead to debilitating degenerative diseases such as osteoarthritis. Total knee arthroplasty is a clinically successful method for eliminating pain in the osteoarthritic knee, but is subject to complications that can affect patient satisfaction and long-term implant performance. The work presented in this dissertation is a demonstration of how anatomic three-dimensional (3D) computational knee models can be an effective alternative for investigating knee mechanics when compared to the cost and time prohibitive nature of in-vivo and in-vitro methods. The studies described in this work utilized the explicit finite element (FE) method to investigate varying aspects of soft tissue constraint, implant alignment, and applied dynamic loading on knee mechanics in 3D natural and implanted partial or whole joint knee models. Combined probabilistic and FE methods were used to successfully identify the most important parameters affecting joint laxity in the natural knee and patellar component alignment in the implanted knee. Two model verification studies demonstrated strong agreement between model-predicted and experimental 3D kinematics of specimen-specific isolated patellofemoral and whole joint cadaveric knee models under simulated dynamic loading (deep knee bend and gait) collected in a mechanical simulator. Using one of the single specimen whole joint models, an additional study successfully identified the most important anatomic and implant alignment parameters related to a clinically-relevant complication associated with a particular implant design. Lastly, a new method of efficiently generating 3D natural articular knee surfaces for FE analysis was developed through a combined mesh morphing and statistical shape modeling approach. These studies included several novel methods for investigating knee mechanics under dynamic loading and specimen-specific soft tissue constraint using the explicit FE method that could be used to better reproduce the complex in-vivo knee environment in forward or muscle-driven models and to assist design-phase implant performance evaluation