Accuracy of Implant Size Prediction Using an Image-Free Robotic System in Primary Total Knee Arthroplasty: A Prospective Observational Study
摘要
Accurate implant sizing is crucial for achieving proper knee balance and favorable clinical outcomes in Total Knee Arthroplasty (TKA). While robotic-assisted technology (RA-TKA) is increasingly used, limited evidence exists regarding the accuracy of image-free systems in predicting appropriate implant sizes. This study evaluates the effectiveness of an image-free robotic system in accurately selecting femoral and tibial component sizes during primary TKA.
Methods100 patients undergoing primary image-free robotic-assisted TKA (CORI Surgical System, Smith & Nephew) for end-stage osteoarthritis by consecutive sampling were included. Patients with prior knee surgeries or undergoing revision TKA were excluded. All surgeries were performed by a single surgical team using a standard medial parapatellar approach with a handheld saw. Femoral registration points included femur center, Whiteside’s line, and mapping of the entire distal femur including anterior femur cortex. Tibial registration included tibia center and mapping of entire proximal tibia articular surface. Implant sizes predicted by the robotic system were independently verified using trial components. Accuracy was compared to historical controls of digital templating using chi-square test (significance set at p < 0.05).
ResultsThe image-free robotic system predicted the exact femoral component size with 92% accuracy (92/100 cases) and within ± 1 size with 100% accuracy (100/100 cases). Similarly for tibia, exact component size accuracy was 72%, within ± 1 size was 94% and within ± 2 size was 100%. Compared to digital templating controls, the robotic system demonstrated statistically significant improvement in both exact size prediction (p < 0.0001) and ± 1 size accuracy (p = 0.003) for the femur and exact size prediction for tibia (p < 0.0001). Accuracy within ± 1 and ± 2 sizes of tibia did not differ significantly between the groups.
ConclusionThis study demonstrates that image-free robotic-assisted technology provides high accuracy in predicting femoral implant sizes during primary total knee arthroplasty. Tibial component size prediction showed comparatively lower exact match accuracy, which may be influenced by intraoperative factors, such as bone resection adjustments and soft tissue balancing. The findings suggest that image-free robotic systems can support implant size selection and enhance intraoperative decision-making, particularly for the femoral component, while highlighting the continued importance of surgical judgment in optimizing overall component sizing.