Improved mediolateral load distribution without adverse laxity pattern in robot-assisted knee arthroplasty compared to a standard manual measured resection technique.

Purpose: Robot-assisted total knee arthroplasty (rTKA) remains in its infancy, is expensive but offers the promise of improved kinematic performance through precise bone cuts, with minimal soft tissue disruption, based on pre-resection soft tissue behaviour. This cadaveric study examined load transfer, soft tissue performance and radiographic indices for conventional (sTKA) versus rTKA. The null hypothesis was there would be no difference between the two modes of implantation.

Methods: Whole (ten) cadaveric limbs were randomised to receive either robotic (rTKA, N = 5) or conventional measured resection (sTKA, N = 5) knee arthroplasty. Laxity patterns were established using validated fixed sensors (Verasense) with manual maximum displacement for six degrees of freedom. Tibiofemoral load and contact points were determined dynamically using remote sensor technology for medial and lateral compartments through a functional arc of motion (0-110 degrees of motion). Final component position was assessed using pre- and post-implantation CT.

Results: No significant intergroup differences for laxity were found (n.s.). The rTKA group exhibited consistently balanced mediolateral load throughout the full arc with significantly reduced overall total load across the joint (for distinct points of measurement, p < 0.05). Despite using flexion-extension and mediolateral gap balancing with measured resection, the sTKA group failed to achieve balance in at least three points of the flexion arc. Post-operative CT confirmed satisfactory component alignment with no significant differences for positioning between the two groups.

Conclusion: This work found improved load sharing for rTKA when compared to conventional surgery for same donor knees. Laxity and CT determined final component positioning was not significantly different. The work supports the contention that robot-assisted TKA delivers improved tibiofemoral load sharing in time zero studies under defined conditions but such offers the promise of improved clinical performance and reduced implant wear.