With fluoroscopic analysis of knee implant kinematics the implant contour must be detected in each image frame, followed by estimation of the implant pose. With a large number of possibly low... Show moreWith fluoroscopic analysis of knee implant kinematics the implant contour must be detected in each image frame, followed by estimation of the implant pose. With a large number of possibly low-quality images, the contour detection is a time-consuming bottleneck. The present paper proposes an automated contour detection method, which is integrated in the pose estimation. In a phantom experiment the automated method was compared with a standard method, which uses manual selection of correct contour parts. Both methods demonstrated comparable precision, with a minor difference in the Y-position (0.08 mm versus 0.06 mm). The precision of each method was so small (below 0.2 mm and 0.3 degrees) that both are sufficiently accurate for clinical research purposes. The efficiency of both methods was assessed on six clinical datasets. With the automated method the observer spent 1.5 min per image, significantly less than 3.9 min with the standard method. A Bland-Altman analysis between the methods demonstrated no discernible trends in the relative femoral poses. The threefold increase in efficiency demonstrates that a pose estimation approach with integrated contour detection is more intuitive than a standard method. It eliminates most of the manual work in fluoroscopic analysis, with sufficient precision for clinical research purposes. Show less
One of the most important causes of failure in unicompartmental knee replacement (UKR) is polyethylene wear. The aim of this study was to develop and assess a novel Roentgen stereophotogrammetric... Show moreOne of the most important causes of failure in unicompartmental knee replacement (UKR) is polyethylene wear. The aim of this study was to develop and assess a novel Roentgen stereophotogrammetric analysis (RSA)-based method for the measurement of linear wear suitable for UKR. Model-based RSA was used to estimate the linear wear of polyethylene bearings in UKR. A phantom was used to validate the method using in vitro measured bearing thicknesses and the linear wear of ten control bearings was estimated in vivo. Computer aided design (CAD) models for the UKRs were used in the model-based RSA system. There was no statistically significant difference between the estimated and measured bearing thicknesses using the CAD models (p=0.386). The precision of the linear wear measurement, expressed as the standard deviation of the difference between the estimated and measured bearing thickness was 0.163 mm. The bias (mean difference) was 0.030 mm. The use of RSA to measure in vivo wear in a UKR has been shown to be accurate in a phantom, and has been verified with in vivo measured controls. The technique does not require surgical implantation of marker balls and can be used retrospectively. Show less