This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.Aims
Methods
This study aimed to investigate the relationship between changes in patellar height and clinical outcomes at a mean follow-up of 7.7 years (5 to 10) after fixed-bearing posterior-stabilized total knee arthroplasty (PS-TKA). We retrospectively evaluated knee radiographs of 165 knees, which underwent fixed-bearing PS-TKA with patella resurfacing. The incidence of patella baja and changes in patellar height over a minimum of five years of follow-up were determined using Insall-Salvati ratio (ISR) measurement. We examined whether patella baja (ISR < 0.8) at final follow-up affected clinical outcomes, knee joint range of motion (ROM), and Knee Society Score (KSS). We also assessed inter- and intrarater reliability of ISR measurements and focused on the relationship between patellar height reduction beyond measurement error and clinical outcomes.Aims
Methods
