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Research

PREDICT TKA PROSTHESIS CONSTRAINT BEHAVIOUR USING COMPUTER SIMULATION

8th Combined Meeting Of Orthopaedic Research Societies (CORS)



Abstract

Summary Statement

The constraint behavior of total knee arthroplasty (TKA) prosthesis usually has to be physically tested. This study presents a computer simulation model using finite element analysis (FEA) and demonstrates its effectiveness in predicting the femorotibial constraint behavior of TKA implants.

Introduction

TKA prostheses are semi-constrained artificial joints. A well-functioning TKA prosthesis should be designed with a good balance between stability and mobility, meaning the femorotibial constraint of the artificial joint cannot be excessive or too lax. To assess the constraint behavior of a TKA prosthesis, physical testing is usually required, and an industrial test standard has been developed for this purpose. Benefiting from technological advancement, computer simulation has become increasingly useful in many industries, including medical device research and development. FEA has been extensively used in stress analysis and structural evaluation of various orthopaedic implants. This study presented an FEA-based simulation to evaluate the femorotibial constraint behavior of TKA prosthesis, and demonstrated the effectiveness of the method by validating it through physical testing.

Methods

A Cruciate Retaining (CR) TKA prosthesis design (Optetrak Logic CR, size 3, Exactech, FL, USA) was used in this study. The prosthesis system consists of a femoral component, a tibial insert, and a tibial baseplate. CAD models of the implants assembled at 0° of flexion were used for the simulation. Finite element models were generated using 10-node tetrahedral elements, with all materials considered linear elastic. Boundary conditions were set up according to the ASTM F1223 standard. The tibial baseplate was fixed distally. A constant compressive force (710 N) was applied on the femoral component. Nonlinear Surface-Surface-Contact was defined at the femorotibial articulating surfaces as well as between the tibial insert and tibial baseplate. A coefficient of friction of 0.2 determined from the physical test was input into the simulation. The femoral component was driven under a displacement-controlled scheme to slide along the anterior-posterior (AP) direction on the tibial insert. At each time step, constraint force occurring at the articulating surface was derived from the reaction force at the distal fixation of the tibial baseplate. The force-displacement curve was plotted by combining the results of all time steps to characterize the constraint behavior of the prosthesis. A nonlinear FEA solver (NX Nastran SOL601, Siemens, TX, USA) was used to solve the simulation. In addition, five samples of the prostheses were physically tested per ASTM F1223. Simulation results were compared to the physical testing.

Results

The simulation successfully captured the movement of contact location and pressure along the movement of the femoral component. The force-displacement curve predicted by the simulation exhibited a very close hysteresis loop profile as the results of physical testing. Using the curve slope from 0 to 5 mm to characterise the constraint in the most relevant displacement range, the simulation predicted 45.7 N/mm anteriorly and 36.4 N/mm posteriorly, which are less than 10% different from the physical testing results (46.4 N/mm anteriorly and 39.6 N/mm posteriorly).

Discussion/Conclusion

This study demonstrated that the simulation was able to closely predict the femorotibial constraint behavior of the TKA prosthesis under ASTM F1223 testing. The simulation results resembled the physical test results not only in the general profile of the curve but also in the magnitude of slope values. The increased difference at the far anterior region could be related to the fact that no material nonlinearity was considered in the current simulation, a factor that could be improved in future studies. A validated simulation method could be very useful in TKA prosthesis design. Since no physical prototypes are required, design evaluation and optimization can be achieved in a much easier and faster manner.