Herve Ophelie M, Flanagan Will, Kanetis Jake, Mooney Bailey, Kremen Thomas J, McAllister David R, Clites Tyler R
Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA, 90095, USA.
Department of Orthopaedic Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
Ann Biomed Eng. 2025 Jan;53(1):193-206. doi: 10.1007/s10439-024-03624-8. Epub 2024 Oct 2.
Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return-to-sport rates. Unfortunately, the mechanics of ligament injury are difficult to study in vivo, and computational studies provide limited insight. The objective of this study was to implement and validate a robotic system capable of reproducing natural six degree-of-freedom clamped-kinematic trajectories on human cadaver knees (meaning that positions and orientations are rigidly controlled and resultant loads are measured). To accomplish this, we leveraged the field's recent access to high-fidelity bone kinematics from dynamic biplanar radiography (DBR), and implemented these kinematics in a coordinate frame built around the knee's natural flexion-extension axis. We assessed our system's capabilities in the context of ACL injury, by moving seven cadaveric knee specimens through kinematics derived from walking, running, drop jump, and ACL injury. We then used robotically simulated clinical stability tests to evaluate the hypothesis that knee stability would be only reduced by the motions intended to injure the knee. Our results show that the structural integrity of the knee was not compromised by non-injurious motions, while the injury motion produced a clinically relevant ACL injury with characteristic anterior and valgus instability. We also demonstrated that our robotic system can provide direct measurements of reaction loads during a variety of motions, and facilitate gross evaluation of ligament failure mechanisms. Clamped-kinematic robotic evaluation of cadaver knees has the potential to deepen understanding of the mechanics of knee ligament injury.
膝关节韧带损伤是最常见的运动损伤之一,且恢复周期长,恢复运动的比率低。遗憾的是,韧带损伤的力学机制在体内难以进行研究,而计算机模拟研究提供的见解有限。本研究的目的是构建并验证一种机器人系统,该系统能够在人体尸体膝关节上再现自然的六自由度夹紧运动轨迹(即位置和方向受到严格控制,并测量合成载荷)。为实现这一目标,我们利用了该领域近期通过动态双平面X线摄影(DBR)获取的高保真骨骼运动学数据,并在围绕膝关节自然屈伸轴构建的坐标系中实现了这些运动学数据。我们通过让七个尸体膝关节标本按照从行走、跑步、跳落和前交叉韧带(ACL)损伤中获取的运动学数据进行移动,在ACL损伤的背景下评估了我们系统的能力。然后,我们使用机器人模拟临床稳定性测试来评估膝关节稳定性仅会因旨在损伤膝关节的运动而降低这一假设。我们的结果表明,膝关节的结构完整性不会因非损伤性运动而受损,而损伤性运动会导致具有典型前向和外翻不稳定特征的临床上相关的ACL损伤。我们还证明,我们的机器人系统能够在各种运动过程中直接测量反应载荷,并有助于对韧带失效机制进行大致评估。对尸体膝关节进行夹紧运动学机器人评估有可能加深对膝关节韧带损伤力学机制的理解。