Accuracy and learning curve of imageless robotic-assisted total knee arthroplasty

Abstract

Background: Total knee arthroplasty (TKA) is widely used to manage severe knee osteoarthritis. However, conventional TKA (C-TKA) often leaves patients dissatisfied due to suboptimal alignment and soft-tissue balance. Robotic-assisted TKA (RA-TKA), particularly with imageless systems like the NAVIO Surgical System, promises enhanced accuracy and improved outcomes. This study aims to validate the accuracy of RA-TKA in achieving functional alignment (FA) and to explore the learning curve associated with this technique. Materials and methods: A retrospective analysis included 101 patients undergoing RA-TKA with the NAVIO system from July 2021 to April 2024. Data on alignment angles, gap balance, and surgical times were analyzed. Patients were categorized by preoperative coronal alignment (valgus, neutral, and varus), with subgroups within the varus category. Accuracy was defined as deviations ≤3° for alignment and ≤1 mm for gap balance. Learning curve trends were analyzed using segmented regression. Results: The study demonstrated a mean alignment error of 1.18° (±1.21) and a gap balance accuracy of 84 %, with no significant differences across knee morphologies. The RA-TKA system achieved an overall implant alignment accuracy rate of 95 %. Varus knees with greater deformities (>6°) showed comparable or superior accuracy to less severe cases. Surgical time averaged 72.3 min (±5.6), with significant reductions observed after the first 11 cases, reflecting procedural efficiency improvements without compromising accuracy. Conclusion: The RA-TKA reliably achieves precise FA across diverse knee morphologies with a rapid learning curve. Future studies should evaluate long-term outcomes and implant survivorship to confirm these promising findings. Level of evidence: IV.