Evaluation of a Surrogate Contact Model in Force-Dependent Kinematic Simulations of Total Knee Replacement

Abstract

Knowing the forces in the human body is of great clinical interest and musculoskeletal (MS) models are the most commonly used tool to estimate them in vivo. Unfortunately, the process of computing muscle, joint contact, and ligament forces simultaneously is computationally highly demanding. The goal of this study was to develop a fast surrogate model of the tibiofemoral (TF) contact in a total knee replacement (TKR) model and apply it to force-dependent kinematic (FDK) simulations of activities of daily living (ADLs). Multiple domains were populated with sample points from the reference TKR contact model, based on reference simulations and design-of-experiments. Artificial neural networks (ANN) learned the relationship between TF pose and loads from the medial and lateral sides of the TKR implant. Normal and right-turn gait, rising-from-a-chair, and a squat were simulated using both surrogate and reference contact models. Compared to the reference contact model, the surrogate contact model predicted TF forces with a root-mean-square error (RMSE) lower than 10 N and TF moments lower than 0.3 N·m over all simulated activities. Secondary knee kinematics were predicted with RMSE lower than 0.2 mm and 0.2 deg. Simulations that used the surrogate contact model ran on average three times faster than those using the reference model, allowing the simulation of a full gait cycle in 4.5 min. This modeling approach proved fast and accurate enough to perform extensive parametric analyses, such as simulating subject-specific variations and surgical-related factors in TKR.

Leveraging subject-specific musculoskeletal modeling to assess effect of anterior cruciate ligament retaining total knee arthroplasty during walking gait

“…The predicted tibiofemoral rotations and translations for each subject between BCR TKA, BCR TKA without ACL, and PCR TKA during walking gait are shown in Figures 4 and 5. These were similar to in vivo kinematics for BCR TKA patients reported by Arauz et al, and MSK-based kinematics of PCR TKA reported by Marra et al 15,34,35 (Figures 4 and 5). Only slight differences in tibiofemoral internal/external rotation were observed between the BCR TKA (with and without ACL) and PCR TKA (Figure 4(b) and (e)), with no other major differences between the groups for angular kinematic parameters.…”

“…These were validated indirectly by comparison with available data from previous studies. 15,20,34 Third, the walking mechanics of the two PCR subjects from the Grand Challenge data were assumed to have the same mechanics if they had the BCR implant in this study. This limitation exists for all similar prior studies.…”

A computational framework for simultaneous estimation of muscle and joint contact forces and body motion using optimization and surrogate modeling

“…With this approach, the velocities and accelerations of the secondary coordinates were assumed to be zero and an elastic foundation was used to model contact. In one recent study a surrogate contact model was used to speed up FDK computation [12]. Guess et al (2014) avoided optimization and instead used feedback control with deformable contact models for the foot and joint of interest [13].…”

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

“…Since the mechanics of the slow and fast models interact, the two models should ideally be simulated simultaneously rather than sequentially. Surrogate models have been developed to calculate muscle-tendon lengths and moment arms produced by geometric musculoskeletal models [185,186], stresses in foot tissues produced by FE models [192], strain fields in long bones produced by FE models [286], and contact forces, stresses, and/or wear in natural and artificial knees produced by FE or elastic foundation models [220,[287][288][289][290][291][292].…”