Aims The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee's functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. Methods We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics. Results There were evident biomechanical differences between the simulated patient models, but also trends that appeared reproducible at the population level. Optimizing the implant position significantly reduced the maximum observed strain root mean square deviations within the cohort from 36.5% to below 5.3% for all but the anterolateral ligament; and concomitantly reduced the kinematic deviations from 3.8 mm (SD 1.7) and 4.7° (SD 1.9°) with MA to 2.7 mm (SD 1.4) and 3.7° (SD 1.9°) relative to the pre-diseased state. To achieve this, the femoral component consistently required translational adjustments in the anterior, lateral, and proximal directions, while the tibial component required a more posterior slope and varus rotation in most cases. Conclusion These findings confirm that MA-induced biomechanical alterations relative to the pre-diseased state can be reduced by optimizing the implant position, and may have implications to further advance pre-planning in robotic-assisted surgery in order to restore pre-diseased knee function.

中文翻译：

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2023 年 ISTA 奖：实现全膝关节置换术中病前状态的功能重建。


目的 机器人辅助全膝关节置换术中最佳植入物定位的手术目标仍然是正在进行的讨论主题。拟议的目标之一是根据膝关节的病前状态重建其功能行为。本研究的目的是优化植入物定位，从机械对位 （MA） 开始，以恢复患者群体的病前状态，包括韧带应变和运动学模式。方法 我们使用基于主动外观模型的方法对 21 例骨关节炎患者的术前 CT 进行分割，识别无骨赘表面并从分割的骨骼中估计软骨;这些几何形状用于构建患病前膝关节的患者特异性肌肉骨骼模型。随后，使用 MA 方法模拟植入，并采用先前开发的优化技术来找到最佳种植体位置，从而最大限度地减少病变前和术后韧带应变和运动学之间的均方根偏差。结果 模拟患者模型之间存在明显的生物力学差异，但在人群水平上似乎具有可重复的趋势。优化植入物位置显着降低了队列中观察到的最大应变均方根偏差，除前外侧韧带外，所有菌株均方差从 36.5% 降低到 5.3% 以下;并同时将 MA 的运动学偏差从 3.8 mm （SD 1.7） 和 4.7° （SD 1.9°） 降低到相对于病前状态的 2.7 mm （SD 1.4） 和 3.7° （SD 1.9°）。 为了实现这一目标，股骨组件始终需要在前、外侧和近端方向进行平移调整，而在大多数情况下，胫骨组件需要更多的后斜率和内翻旋转。结论这些发现证实，通过优化植入物位置可以减少 MA 诱导的相对于病前状态的生物力学改变，并可能对进一步推进机器人辅助手术的预先规划以恢复病前膝关节功能具有意义。