Osteoarthritis (OA) has a complex, heterogeneous and only partly understood etiology. There is a definite role of joint cartilage pathomechanics in originating and progressing of the disease. Although it is still not identified precisely enough to design or select targeted treatments, the progress of this year's research demonstrates that this goal became much closer. On multiple scales - tissue, joint and whole body - an increasing number of studies were done, with impressive results. (1) Technology based instrument innovations, especially when combined with machine learning models, have broadened the applicability of biomechanics. (2) Combinations with imaging make biomechanics much more precise & personalized. (3) The combination of Musculoskeletal & Finite Element Models yield valid personalized cartilage loads. (4) Mechanical outcomes are becoming increasingly meaningful to inform and evaluate treatments, including predictive power from biomechanical models. Since most recent advancements in the field of biomechanics in OA are at the level of a proof op principle, future research should not only continue on this successful path of innovation, but also aim to develop clinical workflows that would facilitate including precision biomechanics in large scale studies. Eventually this will yield clinical tools for decision making and a rationale for new therapies in OA.

骨关节炎 (OA) 具有复杂、异质且仅部分了解的病因。关节软骨病理机制在疾病的发生和发展中具有明确的作用。尽管仍然没有足够精确地确定来设计或选择靶向治疗，但今年的研究进展表明，这一目标变得更加接近。在多个尺度上——组织、关节和全身——进行了越来越多的研究，结果令人印象深刻。(1) 基于技术的仪器创新，尤其是与机器学习模型相结合时，拓宽了生物力学的适用性。(2) 与成像的结合使生物力学更加精确和个性化。(3) 肌肉骨骼和有限元模型的组合产生有效的个性化软骨负荷。(4) 机械结果对于告知和评估治疗变得越来越有意义，包括来自生物力学模型的预测能力。由于 OA 生物力学领域的最新进展都处于证明操作原则的水平，因此未来的研究不仅应该继续沿着这条成功的创新道路前进，而且还应该致力于开发有助于大规模纳入精密生物力学的临床工作流程学习。最终，这将产生用于决策的临床工具和 OA 新疗法的基本原理。未来的研究不仅应该在这条成功的创新道路上继续进行，而且还应该致力于开发临床工作流程，以促进将精密生物力学纳入大规模研究。最终，这将产生用于决策的临床工具和 OA 新疗法的基本原理。未来的研究不仅应该在这条成功的创新道路上继续进行，而且还应该致力于开发临床工作流程，以促进将精密生物力学纳入大规模研究。最终，这将产生用于决策的临床工具和 OA 新疗法的基本原理。