Computational wear prediction of insert conformity and material on mobile-bearing unicompartmental knee arthroplasty

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Abstract

Objectives Unicompartmental knee arthroplasty (UKA) is an alternative to total knee arthroplasty with isolated medial or lateral compartment osteoarthritis. However, polyethylene wear can significantly reduce the lifespan of UKA. Different bearing designs and materials for UKA have been developed to change the rate of polyethylene wear. Therefore, the objective of this study is to investigate the effect of insert conformity and material on the predicted wear in mobile-bearing UKA using a previously developed computational wear method. Methods Two different designs were tested with the same femoral component under identical kinematic input: anatomy mimetic design (AMD) and conforming design inserts with different conformity levels. The insert materials were standard or crosslinked ultra-high-molecular-weight polyethylene (UHMWpe). We evaluated the contact pressure, contact area, wear rate, wear depth, and volumetric wear under gait cycle loading conditions. Results conforming design inserts had the lower contact pressure and larger contact area. However, they also had the higher wear rate and volumetric wear. The improved wear performance was found with AMD inserts. In addition, the computationally predicted volumetric wear of crosslinked UHMWpe inserts was less than half that of standard UHMWpe inserts. Conclusion our results showed that increasing conformity may not be the sole predictor of wear performance; highly crosslinked mobile-bearing polyethylene inserts can also provide improvement in wear performance. These results provide improvements in design and materials to reduce wear in mobile-bearing UKA.

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Koh, Y. G., Lee, J. A., Lee, H. Y., Kim, H. J., & Kang, K. T. (2019). Computational wear prediction of insert conformity and material on mobile-bearing unicompartmental knee arthroplasty. Bone and Joint Research, 8(11), 563–569. https://doi.org/10.1302/2046-3758.811.BJR-2019-0036.R1

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