Computational wear prediction of a total knee replacement from in vivo kinematics
Computational wear prediction of a total knee replacement from in vivo kinematics
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DOI：
10.1016/j.jbiomech.2004.02.013
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发表时间：
2005-02-01
影响因子：
2.4
通讯作者：
Banks, SA
中科院分区：
文献类型：
--
作者：
Fregly, BJ;Sawyer, WG;Banks, SA
全膝关节置换术中超高分子量聚乙烯关节面的磨损仍然是这些临床成功器械寿命的主要限制因素。目前很少有设计工具可用于根据不同的运动学预测植入物的轻度磨损。载荷和材料特性。本文报告了一种计算机建模方法的实施，该方法使用荧光镜测量的运动作为输入，并使用计算效率高的动态接触和摩擦学分析预测患者特定的植入物损伤。根据X线透视数据生成两种载荷条件（70-30和50-50内外侧载荷分割）下两种活动（步态和楼梯）的多体动力学模拟，以预测胫骨衬垫表面上单个元件的接触压力和滑动速度时间历史。这些时间历程被用于计算磨损分析，以预测由于每个元件所经历的磨损和蠕变而导致的损坏深度。根据从提供体内活动的同一患者体内取出的胫骨垫片，评价预测的损伤面积、体积和最大深度。总体而言，预测的损坏与回收时观察到的损坏非常一致。步态和楼梯模拟分别预测外侧最大损伤的正确位置，而步态和楼梯的组合需要预测内侧的正确位置。预测的最大损伤深度也与检索结果一致。每次损伤预测的总计算时间小于30分钟。这种方法的持续改进将为准确预测全膝关节置换术中的临床相关磨损提供一个强大的工具。(C)2004 Elsevier Ltd.保留所有权利。
Wear of ultra-high molecular weight polyethylene bearings in total knee replacements remains a major limitation to the longevity of these clinically successful devices. Few design tools are currently available to predict mild wear in implants based on varying kinematics. loads, and material properties. This paper reports the implementation of a computer modeling approach that uses fluoroscopically measured motions as inputs and predicts patient-specific implant damage using computationally efficient dynamic contact and tribological analyses. Multibody dynamic simulations of two activities (gait and stair) with two loading conditions (70-30 and 50-50 medial-lateral load splits) were generated from fluoroscopic data to predict contact pressure and slip velocity time histories for individual elements on the tibial insert surface. These time histories were used in a computational wear analysis to predict the depth of damage due to wear and creep experienced by each element. Predicted damage areas, volumes, and maximum depths were evaluated against a tibial insert retrieved from the same patient who provided the in vivo motions. Overall, the predicted damage was in close agreement with damage observed on the retrieval. The gait and stair simulations separately predicted the correct location of maximum damage on the lateral side, whereas a combination of gait and stair was required to predict the correct location on the medial side. Predicted maximum damage depths were consistent with the retrieval as well. Total computation time for each damage prediction was less than 30 min. Continuing refinement of this approach will provide a robust tool for accurately predicting clinically relevant wear in total knee replacements. (C) 2004 Elsevier Ltd. All rights reserved.