While cervical arthroplasty using Total Disc Replacement (TDR) implants is an established treatment for persistent neck and arm pain, revision rates limit it from reaching its full potential. To address the underlying complications, we developed finite element simulation-driven design optimizations for a TDR's bone-implant interface and motion-preservation features. These automated processes explored high-dimensional design spaces iteratively through analysis of design variations interplay with spinal structures. The optimizations were metamodel-based using artificial neural networks and a hybrid optimizer. They optimized the motion-preservation zone towards replicating the asymptomatic spinal segment's ligaments strain profiles and its facet joint force profiles during main motions. This design process aims to minimize the risk for postoperative pain, avoidable degeneration and to restore segmental biomechanics, to prevent adjacent segment effects. Designs with single articulation and with dual articulation (with a mobile insert) were optimized. The bone-implant interface was optimized with the aim to minimize the risk for subsidence and implant migration. The optimizations improved the multi-objective value of the bone-implant interface by 14.6% and that of the motion-preservation zone by 36.1%. Implant migration, the leading cause of revisions, was reduced by 24.8%. With this, we show the potential of simulation-driven implant design optimization for addressing complex clinical challenges.

翻译：虽然使用全椎间盘置换（TDR）植入物进行颈椎关节成形术是治疗持续性颈部和手臂疼痛的成熟方法，但翻修率限制了其充分发挥潜力。为解决潜在并发症，我们针对TDR的骨-植入物界面和运动保留功能开发了有限元仿真驱动的设计优化方法。这些自动化流程通过分析设计变体与脊柱结构的相互作用，迭代探索高维设计空间。优化采用基于人工神经网络的元模型和混合优化器。其将运动保留区域的优化目标设定为：在主运动过程中，复现无症状脊柱节段的韧带应变分布及其小关节力分布。该设计流程旨在最大限度地降低术后疼痛风险、避免可预防的退行性变、恢复节段生物力学特性，从而预防邻近节段效应。研究对单关节面和双关节面（带活动衬垫）的设计分别进行了优化。骨-植入物界面的优化目标是最小化沉降和植入物移位的风险。优化使骨-植入物界面的多目标值提升了14.6%，运动保留区域的多目标值提升了36.1%。作为翻修主要原因的植入物移位减少了24.8%。由此，我们展示了仿真驱动的植入物设计优化在应对复杂临床挑战方面的潜力。