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
Cementless acetabular components rely on press-fit fixation for initial stability. In certain cases, initial stability is more difficult to obtain (such as during revision). No current study evaluates how a surgeon’s impaction technique (mallet mass, mallet velocity, and number of strikes) may affect component fixation. This study seeks to answer the following research questions: 1) how does impaction technique affect a) bone strain generation and deterioration (and hence implant stability) and b) seating in different density bones?; and 2) can an impaction technique be recommended to minimize risk of implant loosening while ensuring seating of the acetabular component? A custom drop tower was used to simulate surgical strikes seating acetabular components into synthetic bone. Strike velocity and drop mass were varied. Synthetic bone strain was measured using strain gauges and stability was assessed via push-out tests. Polar gap was measured using optical trackers.Aims
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