Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois.
J Orthop Res. 2020 Jul;38(7):1538-1549. doi: 10.1002/jor.24755. Epub 2020 Jun 8.
Polyethylene wear remains a contributor to long term failure in total knee replacements (TKRs). Advances in materials have improved polyethylene wear rates, therefore further wear reductions require a better understanding of patient-specific factors that lead to wear. Variability of gait within patients is considerable and could lead to significant variability in wear rates that cannot be predicted by standard testing methods. An in-silico study was performed to investigate the influence of gait variability on TKR polyethylene wear. Nine characteristic peaks within the load and motion profiles used for TKR wear testing were varied 75% to 125% from baseline (ISO-14243-3:2014) to generate 310 unique waveforms. Wear was calculated for 1-million cycles using a finite element TKR wear model. From the results, a surrogate model was developed using multiple linear regression, and used to predict how wear changes due to dispersion of motion and force peaks within a) ±5%, the maximum allowable input tolerance of ISO, and b) ±25%, more reflective of patient gait inter-variability. The range of wear within the ±5% tolerance was 0.65 mm /million cycles and was 3.24 mm /million cycles within the ±25% variability more in line with the dispersion observed within patients. Although no one kinematic or kinetic peak dominated variability in TKR volumetric wear, variability within flexion/extension peaks were the largest contributor to wear rate variability. Interaction between the peaks of different waveforms was also important. This study, and future studies incorporating patient-specific data, could help to explain the connection between patient-specific gait factors and wear rates.
聚乙烯磨损仍然是全膝关节置换术（TKR）长期失败的原因之一。材料的进步提高了聚乙烯的磨损率，因此，要进一步降低磨损率，就需要更好地了解导致磨损的患者特定因素。患者内的步态变化很大，可能导致磨损率的显著变化，而标准测试方法无法预测这些变化。进行了一项计算机模拟研究，以研究步态变化对 TKR 聚乙烯磨损的影响。TKR 磨损测试中使用的负荷和运动曲线中的九个特征峰从基线（ISO-14243-3：2014）增加或减少 75%到 125%，以生成 310 个独特的波形。使用有限元 TKR 磨损模型计算了 100 万次循环的磨损。从结果中，使用多元线性回归开发了一个替代模型，并用于预测由于运动和力峰值的分散导致磨损如何变化：a）±5%，这是 ISO 允许的最大输入公差，b）±25%，更能反映患者步态的变异性。在±5%公差范围内的磨损范围为 0.65mm/百万次循环，在±25%变化范围内的磨损范围为 3.24mm/百万次循环，更符合患者内观察到的分散情况。虽然没有一个运动学或动力学峰值主导着 TKR 容积磨损的变化，但在弯曲/伸展峰值内的变化是导致磨损率变化的最大因素。不同波形的峰值之间的相互作用也很重要。这项研究以及未来结合患者特定数据的研究，可以帮助解释患者特定的步态因素与磨损率之间的联系。
