Key points are not available for this paper at this time.
Abstract Robotic‐assisted total knee arthroplasty (RTKA) has gained widespread acceptance due to its demonstrated ability to improve surgical accuracy compared to conventional total knee arthroplasty (CTKA). While the precise impact of RTKA on postoperative patient‐reported outcome measures (PROMs) remains inconclusive, the increased accuracy in alignment and joint kinematics suggests potential improvements in patient satisfaction and functional outcomes. Two primary RTKA systems exist: image‐based, which uses preoperative CT scans for detailed 3D modeling, and image‐less, which relies on intra‐operative digitization of anatomical landmarks. Both systems aim to achieve accurate implant placement and soft‐tissue balancing, yet they differ in methodology and reliance on preoperative data. Despite RTKA's theoretical advantages, there is ongoing debate about whether accuracy alone is sufficient to achieve optimal postoperative outcomes, particularly concerning joint kinematics and alignment strategies. Literature reveals no significant difference in coronal plane alignment between image‐based and image‐less systems, though image‐less systems may be more prone to varus errors due to the reliance on intra‐articular landmarks. Additionally, image‐free systems may face challenges in replicating native knee anatomy, especially in the sagittal plane, leading to potential limitations in achieving ideal tibial slope reconstruction. The future of RTKA may lie in refining implant positioning strategies that minimize postoperative alterations to pre‐arthritic knee kinematics, particularly with standardized off‐the‐shelf implants. As robotic technology evolves, there is potential to enhance surgical outcomes by combining accuracy with personalized alignment approaches that better address individual patient anatomy. Further research is needed to assess the long‐term clinical benefits of RTKA and its capacity to improve patient‐specific functional outcomes. Level of evidence level 5
Hirschmann et al. (Tue,) studied this question.