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. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A DL workflow was created to measure the FMAA and validated against human measurements. To reflect potential intramedullary guide placement during manual TKA, two different FMAAs were calculated either using a line approximating the entire diaphyseal shaft, and a line connecting the apex of the femoral intercondylar sulcus to the centre of the diaphysis. The proportion of FMAAs outside a range of 5.0° (SD 2.0°) was calculated for both definitions, and FMAA was compared using univariate analyses across sex, BMI, knee alignment, and femur length.Aims
Methods
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. 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) workflow for angle calculation on the entire database. The radiological ankle centre was defined as the midpoint of the superior talus edge/tibial plafond. Knee alignment (hip-knee-ankle angle) was compared against 1) midpoint of the most prominent malleoli points, 2) midpoint of the soft-tissue overlying malleoli, and 3) midpoint of the soft-tissue sulcus above the malleoli.Aims
Methods
Successful total knee arthroplasty (TKA) is predicated on accurate bony resection, mechanical alignment and component positioning. An active robotic TKA system is designed to achieve reliable and accurate bony resection based upon a preoperatively developed surgical plan. Surgical resections are executed intra-operatively according to this pre-operative plan. The goal of this study was to determine the accuracy of final implant positioning and alignment using this active robotic device, as well as its early clinical outcomes. An FDA prospective study under investigational device exemption was conducted from 2017–2018. Pre-operative CT scans were used to create a pre-operative plan using the TSolution One? Surgical System (THINK Surgical, Inc). TKA was performed using a standard approach, with planned and robotically executed femoral and tibial resections. Subjects completed 3-month follow-up with post-operative CT scans. A validated method was used to compare pre- and post-operative CT scans to determine differences between planned and achieved implant position. Femoral and tibial component sizing, and mean differences in implant position and alignment were compared. Short Form 12 Physical (PCS) and Mental Component Summary (MCS) scores as well as Knee Society (Objective and Functional) scores at 12 weeks post-operatively were compared with pre-operative scores. Paired-sample t-tests were used for comparisons.Objectives
Materials and Methods
