The impact of a diaphyseal femoral deformity on knee alignment varies according to its severity and localization. The aims of this study were to determine a method of assessing the impact of diaphyseal femoral deformities on knee alignment for the varus knee, and to evaluate the reliability and the reproducibility of this method in a large cohort of osteoarthritic patients. All patients who underwent a knee arthroplasty from 2019 to 2021 were included. Exclusion criteria were genu valgus, flexion contracture (> 5°), previous femoral osteotomy or fracture, total hip arthroplasty, and femoral rotational disorder. A total of 205 patients met the inclusion criteria. The mean age was 62.2 years (SD 8.4). The mean BMI was 33.1 kg/m2 (SD 5.5). The radiological measurements were performed twice by two independent reviewers, and included hip knee ankle (HKA) angle, mechanical medial distal femoral angle (mMDFA), anatomical medial distal femoral angle (aMDFA), femoral neck shaft angle (NSA), femoral bowing angle (FBow), the distance between the knee centre and the top of the FBow (DK), and the angle representing the FBow impact on the knee (C’KS angle).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
No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model. A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data.Aims
Methods
The Coronal Plane Alignment of the Knee (CPAK) classification is a simple and comprehensive system for predicting pre-arthritic knee alignment. However, when the CPAK classification is applied in the Asian population, which is characterized by more varus and wider distribution in lower limb alignment, modifications in the boundaries of arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) should be considered. The purposes of this study were as follows: first, to propose a modified CPAK classification based on the actual joint line obliquity (aJLO) and wider range of aHKA in the Asian population; second, to test this classification in a cohort of Asians with healthy knees; third, to propose individualized alignment targets for different CPAK types in kinematically aligned (KA) total knee arthroplasty (TKA). The CPAK classification was modified by changing the neutral boundaries of aHKA to 0° ± 3° and using aJLO as a new variable. Radiological analysis of 214 healthy knees in 214 Asian individuals was used to assess the distribution and mean value of alignment angles of each phenotype among different classifications based on the coronal plane. Individualized alignment targets were set according to the mean lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) of different knee types.Aims
Methods
It is unknown whether gap laxities measured in robotic arm-assisted total knee arthroplasty (TKA) correlate to load sensor measurements. The aim of this study was to determine whether symmetry of the maximum medial and lateral gaps in extension and flexion was predictive of knee balance in extension and flexion respectively using different maximum thresholds of intercompartmental load difference (ICLD) to define balance. A prospective cohort study of 165 patients undergoing functionally-aligned TKA was performed (176 TKAs). With trial components in situ, medial and lateral extension and flexion gaps were measured using robotic navigation while applying valgus and varus forces. The ICLD between medial and lateral compartments was measured in extension and flexion with the load sensor. The null hypothesis was that stressed gap symmetry would not correlate directly with sensor-defined soft tissue balance.Aims
Methods
Medial pivot (MP) total knee arthroplasties (TKAs) were designed to mimic native knee kinematics with their deep medial congruent fitting of the tibia to the femur almost like a ball-on-socket, and a flat lateral part. GMK Sphere is a novel MP implant. Our primary aim was to study the migration pattern of the tibial tray of this TKA. A total of 31 patients were recruited to this single-group radiostereometric analysis (RSA) study and received a medial pivot GMK Sphere TKA. The distributions of male patients versus female patients and right versus left knees were 21:10 and 17:14, respectively. Mean BMI was 29 kg/m2 (95% confidence interval (CI) 27 to 30) and mean age at surgery was 63 years (95% CI 61 to 66). Maximum total point motions (MTPMs), medial, proximal, and anterior translations and transversal, internal, and varus rotations were calculated at three, 12, and 24 months. Patient-reported outcome measure data were also retrieved.Aims
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