Optimizing Ligament Modeling Techniques in Total Knee Replacement Finite Element Models

A total knee replacement (TKR) is an orthopedic implant designed to alleviate pain and restore joint function as an end-stage treatment for osteoarthritis. As the number of TKR surgeries performed continues to increase, it is important to understand the causes of TKR failure to improve patient outcomes and prevent TKR failure. TKRs failure modes include instability and malalignment which are influenced by ligament balancing. Poor ligament balancing can lead to instability and irregular kinematics, which can result in implant failure. Computational TKR research, including finite element analysis (FEA) modeling, is an efficient and low-risk technique for investigating knee biomechanics. Ligaments should be incorporated within TKR FEA models to investigate the correlation between subject-specific ligament anatomy and mechanical properties , ligament balancing, and TKR function. However, there is currently no consensus on the appropriate computational modeling choices to best represent these structures. Therefore, this thesis seeks to 1) quantify how knee ligament modeling choices affect resulting predictions of TKR kinematics and laxity, and 2) explore how knee ligament mechanical properties influence TKR function within a TKR FEA model. A sensitivity study of ligament attachment site found 14 of the 18 parameters (superior and inferior attachment point of each ligament, along 3 translational directions) were statistically significant for at least one kinematic motion. Knee laxity testing results demonstrated that a linear ligament material model resulted in smaller laxity ranges compared to the nonlinear ligament material model but followed a similar trend. A sensitivity study of ligament material parameters found 5 of the 6 parameters (stiffness and slack length of each ligament) achieved statistical significance for at least one kinematic motion. Lastly, increasing the number of ligament fibers from 1 to 5 influenced knee laxity and ligament engagement. These studies demonstrate that varying knee ligament anatomical and mechanical properties impact TKR kinematics and laxity. Study limitations include the use of one-dimensional representations of ligaments, one implant type, and the lack of direct comparison with cadaveric testing. This work provides a crucial step towards the development of patient-specific models to better predict TKR failure and improve surgical guidance.