Objectives. The purpose of this study was to compare the thickness of the hip capsule in patients with surgical
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
Acetabular edge-loading was a cause of increased wear rates in metal-on-metal hip arthroplasties, ultimately contributing to their failure. Although such wear patterns have been regularly reported in retrieval analyses, this study aimed to determine their in vivo location and investigate their relationship with acetabular component positioning. 3D CT imaging was combined with a recently validated method of mapping bearing surface wear in retrieved hip implants. The asymmetrical stabilizing fins of Birmingham hip replacements (BHRs) allowed the co-registration of their acetabular wear maps and their computational models, segmented from CT scans. The in vivo location of edge-wear was measured within a standardized coordinate system, defined using the anterior pelvic plane.Aims
Methods
