Multi-scale modeling and analysis via surrogate modeling techniques for in vivo knee loading predictions

Abstract

Total knee replacement is a viable treatment for end-stage knee arthritis. With a greater number of younger patients opting for total knee replacement surgery, their increasingly active lifestyles will result in higher wear rates while decreasing the life expectancy of the tibial insert component of the knee replacement implant. In response to the eventuality of patients with more active lifestyles requiring knee replacement surgery, this research proposed to accurately estimate in vivo knee loading over a gait cycle through a multi-scale modeling approach. Estimates for knee loading were compared to publicly-available in vivo knee loading measurements from a telemetric implant. A whole-body musculoskeletal modeling approach was used to simulate the gait cycle of a person who had undergone total knee replacement surgery. This approach was used to calculate net knee joint contact forces. Then, an explicit dynamic finite element analysis was used to estimate the load distribution in the medial and lateral compartments of the knee using a six degree of freedom knee joint. Surrogate modeling via spline interpolations was then utilized to reduce computational time and effort for calculation of the load distributions from finite element analysis to less than five seconds. Results suggest that generic whole-body modeling and hybrid forward dynamic simulation techniques for estimating knee joint loads may become clinically feasible in the near future. Finite element modeling and analysis produced two key results. First, the best results from varying the location of the femoral component reference point did not accurately reflect an ISO wear model location for the femoral reference point. Second, the finite element model accurately estimated the medial and lateral contact forces during the stance phase. However, surrogate modeling successfully interpolated the load distributions in the medial and lateral contact surfaces using results from the finite element analysis without requiring any knowledge of the geometry of the contact surfaces. This research concludes by proposing to couple whole-body modeling and simulation techniques with a surrogate optimization scheme to provide clinicians with a patient's knee loading behavior. A path toward improving predictive wear modeling and simulation is also provided.