Aims. Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage artificial intelligence (AI) to determine the accuracy and effect of using different radiological anatomical landmarks to quantify mechanical alignment in relation to a traditionally defined radiological ankle centre. Methods. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A sub-cohort of 250 radiographs were annotated for landmarks relevant to knee alignment and used to train a deep learning (U-Net)
Aims. Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort. Methods. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A DL
Around the world, the emergence of robotic technology has improved surgical precision and accuracy in total knee arthroplasty (TKA). This territory-wide study compares the results of various robotic TKA (R-TKA) systems with those of conventional TKA (C-TKA) and computer-navigated TKA (N-TKA). This is a retrospective study utilizing territory-wide data from the Clinical Data Analysis and Reporting System (CDARS). All patients who underwent primary TKA in all 47 public hospitals in Hong Kong between January 2021 and December 2023 were analyzed. Primary outcomes were the percentage use of various robotic and navigation platforms. Secondary outcomes were: 1) mean length of stay (LOS); 2) 30-day emergency department (ED) attendance rate; 3) 90-day ED attendance rate; 4) 90-day reoperation rate; 5) 90-day mortality rate; and 6) surgical time.Aims
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