The Role of Computed Tomography in Achieving True External Rotation in Robotic Knee Replacement: A Retrospective Analysis of 300 Knees.

• Tác giả: Syed Ali, Pramod Bhor, Sachin Kale, Dnyanada Kutumbe, Sawankumar Pawar, Arvind Vatkar
• Ngôn ngữ: eng
• Ký hiệu phân loại: 133.3237 Divinatory arts
• Thông tin xuất bản: India : Journal of orthopaedic case reports , 2025
• Bộ sưu tập: NCBI
• ID: 171013

Tóm tắt

INTRODUCTION: Midflexion gap (MFG) malalignment remains a challenge in total knee arthroplasty (TKA), often attributed to inaccurate femoral component positioning. Precise determination of true external rotation (TER) is crucial for optimal implant orientation and MFG reduction. This study aimed to evaluate the utility of computed tomography (CT)-based TER measurement in robotic knee replacements. MATERIALS AND METHODS: A retrospective analysis was conducted on data from 300 patients who underwent robotic TKA using a system that incorporates CT-derived bone models. TER was measured preoperatively on CT scans. RESULTS: The mean posterior condylar angle (PCA) (n = 300) between the transepicondylar axis (TEA) and the posterior condylar axis was 2.87 ± 0.73° (95% confidence interval [CI]) with a range of 2.14-3.6°. The external rotation between the anatomical and surgical TEA is 1.19 ± 0.94° (95% CI) with a range of 0.25-2.13°. Intraclass correlation coefficient for the angle is 1 (TEA) and 0.98 (PCA). This highlights potential discrepancies between traditional radiographic measurements and actual TER. Femoral component positioning aligned closer to the CT-based TER compared to standard methods. In addition, a significant reduction in MFG was observed in knees with TER-guided implant placement. CONCLUSION: CT-based TER measurement provides a more accurate assessment of femoral rotation compared to conventional radiographs. This improved precision translates into optimal implant positioning and significantly reduces MFG malalignment in robotic knee replacements. Our findings suggest that incorporating CT-based TER into the workflow can enhance the accuracy and outcomes of robotic TKA.