Computational Parametric Studies for Preclinical Evaluation of Total Knee Replacements

Abstract

Aseptic loosening remains a leading cause of long-term failure of total knee replacement (TKR) that can limit the lifetime of the implant past the second decade. To help accelerate and facilitate advances in TKR design, our goal was to develop a computational framework based on previous work, that could accurately and efficiently predict the effect of design, surgical, and patient variability on TKR wear. The framework can accommodate patient-specific, population-specific, or standardized motions and forces as inputs. The wear model that is fully integrated into the finite element model the framework is built around was calibrated from materials testing (wheel-on-flat) experiments. Validation of the model is carried out by comparison to pin-on-disk and mechanical knee simulator studies. We present two applications to test the effectiveness of the framework for performing parametric studies: one to test the sensitivity of TKR wear to the transverse-plane rotational alignment of the tibial component, and the second to test the sensitivity of TKR wear to femoral center of rotation. We demonstrate that wear is highly sensitive to femoral component alignment, consistent with previous studies, and that choice of femoral center of rotation is important during simulator testing of TKR components. The two reported applications represent initial attempts to study variability in component alignment- future work will include studying variability in kinematics and kinetics. In a design setting, the finished framework will allow new innovations to be tested as soon as they are developed, supplementing mechanical testing, and reducing the amount required.