The purpose of this study is to develop a method to analyse the pose of the knee nearthrosis mounted and to automate the registration procedure for easy use in clinical applications. The proposed registration method is essentially a model-based method, in which the CAD model is acquired by reverse engineering. The CAD model is converted into a two-dimensional (2D) image by a rendering technique, and the compatibility of the X-ray image and the image of the CAD model is investigated. To avoid the optimisation of six unknown parameters with respect to the relative pose between the condyle and tibial models, a 2D coordinate system is set on each component of the X-ray images. A 3D coordinate system is also set on each of the two nearthrosis components. With such a setup, there is only one unknown rotational angle on each component, which is determined by an optimum algorithm in accordance with the contour error between the X-ray image and the image of the CAD model. Extensive computer simulation and in vitro experiments using real X-ray images have been implemented to investigate the feasibility of the proposed registration method.

No abstract

After total knee replacement, the monitoring of the prosthetic performance is often done by roentgenographic examination. However, the two-dimensional (2D) roentgen images only provide information about the projection onto the anteroposterior (AP) and mediolateral (ML) planes. Historically, the model-based roentgen stereophotogrammetric analysis (RSA) technique has been developed to predict the spatial relationship between prostheses by iteratively comparing the projective data for the prosthetic models and the roentgen images. During examination, the prosthetic poses should be stationary. This should be ensured, either by the use of dual synchronized X-ray equipment or by the use of a specific posture. In practice, these methods are uncommon or technically inconvenient during follow-up examination. This study aims to develop a rotation platform to improve the clinical applicability of the model-based RSA technique. The rotation platform allows the patient to assume a weight-bearing posture, while being steadily rotated so that both AP and ML knee images can be obtained. This study uses X-ray equipment with a single source and flat panel detectors (FPDs). Four tests are conducted to evaluate the quality of the FPD images, steadiness of the rotation platform, and accuracy of the RSA results. The results show that the distortion-induced error of the FPD image is quite minor, and the prosthetic size can be cautiously calibrated by means of the scale ball(s). The rotation platform should be placed closer to the FPD and orthogonal to the projection axis of the X-ray source. Image overlap of the prostheses can be avoided by adjusting both X-ray source and knee posture. The device-induced problems associated with the rotation platform include the steadiness of the platform operation and the balance of the rotated subject. Sawbone tests demonstrate that the outline error, due to the platform, is of the order of the image resolution (= 0.145 mm). In conclusion, the rotation platform with steady rotation, a knee support, and a handle can serve as an alternative method to take prosthetic images, without the loss in accuracy associated with the RSA method.

Recently, the model-based roentgen stereophotogrammetric analysis (RSA) method has been developed as an in vivo tool to estimate static pose and dynamic motion of the instrumented prostheses. The two essential inputs for the RSA method are prosthetic models and roentgen images. During RSA calculation, the implants are often reversely scanned and input in the form of meshes to estimate the outline error between prosthetic projection and roentgen images. However, the execution efficiency of the RSA iterative calculation may limit its clinical practicability, and one reason for inefficiency may be very large number of meshes in the model. This study uses two methods of mesh manipulation to improve the execution efficiency of RSA calculation. The first is to simplify the model meshes and the other is to segment and delete the meshes of insignificant regions. An index (i.e. critical percentage) of an optimal element number is defined as the trade-off between execution efficiency and result accuracy. The predicted results are numerically validated by total knee prosthetic system. The outcome shows that the optimal strategy of the mesh manipulation is simplification and followed by segmentation. On average, the element number can even be reduced to 1% of the original models. After the mesh manipulation, the execution efficiency can be increased about 75% without compromising the accuracy of the predicted RSA results (the increment of rotation and translation error: 0.06° and 0.02 mm). In conclusion, prosthetic models should be manipulated by simplification and segmentation methods prior to the RSA calculation to increase the execution efficiency and then to improve clinical applicability of the RSA method.