Artificial Intelligence-Based Three-Dimensional Preoperative Planning for Total Knee Arthroplasty in End-Stage Knee Osteoarthritis​

Accurate preoperative templating for total knee arthroplasty (TKA) in patients with end-stage knee osteoarthritis (KOA) remains challenging, and the accuracy of conventional planning methods is variable. This preliminary, retrospective, single-center study evaluated the reliability of a robot-independent, artificial intelligence (AI)-based, three-dimensional (3D) preoperative planning system (AIKNEE) for predicting prosthesis size and component position in patients undergoing TKA for end-stage KOA. Twenty-eight knees from 24 patients with Kellgren-Lawrence grade 3-4 KOA were included. The primary outcome was the agreement between the planned and implanted prosthesis sizes. Secondary outcomes included correction of the coronal hip-knee-ankle (HKA) angle, improvement in Hospital for Special Surgery (HSS) knee scores, and early postoperative complications. The planned size matched the implanted size exactly in 53.57% of femoral components (15/28; 95% confidence interval [CI], 35.8%-70.5%) and 46.43% of tibial components (13/28; 95% CI, 29.5%-64.2%). Agreement within ±1 size was 85.71% for femoral components (24/28; 95% CI, 68.5%-94.3%) and 96.43% for tibial components (27/28; 95% CI, 82.3%-99.4%), giving an overall matching rate of 91.07% (51/56; 95% CI, 80.7%-96.1%). The postoperative HKA angle improved from 173.0° ± 3.9° to 178.2° ± 1.2° (P < 0.001), and the HSS score increased from 39.7 ± 2.2 preoperatively to 80.8 ± 1.3 at the 1-month follow-up (P < 0.001). No major early complications, including infection, dislocation, or deep venous thrombosis, were observed. Within this preliminary cohort, the AIKNEE system predicted prosthesis size with a reliability comparable to that reported for existing AI templating tools. Because the study was retrospective, single-arm, unblinded, and limited to 1 month of follow-up, these data characterize planning accuracy only and do not demonstrate clinical effectiveness; adequately powered, controlled studies with long-term follow-up are required.