In vivo knee joint loading and kinematics – the interplay between movement and loading at the patello-femoral and tibio-femoral joints.

虽然全膝关节置换术是治疗膝关节骨性关节炎的一种非常成功的治疗方法，但约20%的患者后来证明对手术后的功能结果不满意。有相当一部分患者患有尚未完全了解的术后症状，如前膝疼痛。要解决膝关节置换的遗留问题，需要更好地了解髌股关节和胫股关节之间的力学相互作用。然而，在动态活动期间精确测量膝关节的内部载荷和运动学是非常具有挑战性的；因此，到目前为止还没有合适的数据。在过去的几年里，柏林夏里特研究所和苏黎世理工大学之间的紧密合作使我们能够捕捉到全球独一无二的活体胫股载荷和内部关节运动学数据集。同时测量这两个关键参数，以及全身运动、地面反作用力和肌肉活动，现在为本应用提供了基础，旨在了解置换关节的基本膝关节力学。同时，我们将量化患者特定的Patello-股骨负荷，它们如何与Patello-股骨和胫股关节内的动态运动相关，以及拮抗肌肉共同收缩如何影响总的关节力和关节面上的压力分布。特别是，我们将开发一种技术平台，使我们能够识别可能导致关节结构负荷过大的植入参数的不利组合。在对照活体膝关节负荷测量和肌电肌电激活进行验证后，通过先进的受试者特定模型确定的肌肉骨骼负荷将作为详细接触分析的输入，目的是揭示关节表面的负荷分布。虽然这一特定的体内作用力和运动学数据集仅限于6名患者，但它是全球最大的可用数据集，在该项目中，我们的目标是将其建立为以后分析其他植入物或患者运动学数据的基准。在这样做的同时，我们还将为评估其他植入物设计和植入方法奠定技术基础，而不仅仅是这里使用的经验证的器械植入物。

While total knee arthroplasty is a generally very successful treatment for knee osteoarthritis, about 20% of patients later turn out to be not satisfied with their functional post-operative outcome. A substantial patient population suffers from not yet fully understood post-operative symptoms, such as anterior knee pain. Progress towards solving the remaining problems of knee joint replacement requires a better understanding of the mechanical interaction between the patello-femoral and tibio-femoral joints. However, measuring the precise internal loading and kinematics of the knee during dynamic activities is extremely challenging; as a result no appropriate data is available so far. Over the last few years, a tight collaboration between the Charité-Berlin and the ETH-Zürich allowed us to capture a worldwide unique dataset of synchronized in vivo tibio-femoral loads and internal joint kinematics. The simultaneous measurement of these two key parameters, along with whole body motion, ground reaction forces and muscle activity, now provides the basis for the present application, which aims to gain an understanding of the underlying knee mechanics in a replaced joint. Concurrently, we will quantify the patient-specific patello-femoral loads, how they relate to the dynamic movements within the patello-femoral and tibio-femoral joints, and how antagonist muscle co-contraction affects the total joint forces and the pressure distributions at the articulating surfaces. In particular, we will develop a technology platform that enables us to identify adverse combinations of implantation parameters, that may lead to excessive loading of the joint structures. After validation against in vivo knee load measurements and muscle activation from EMG, the musculoskeletal loading determined through advanced subject specific models will serve as input to detailed contact analyses with the goal to unravel the loading distribution at the articulating surfaces. Although this specific dataset of in vivo forces and kinematics is limited to a patient cohort of six, it is globally the largest available dataset, and within this project we aim at establishing it as a benchmark for later analyses of other implants or patient kinematic data. In doing so, we will also lay the technological foundation to evaluate other implant designs and implantation methods, beyond the validated instrumented implants used here.