2D/3D image registration techniques have supplanted RSA for kinematic analysis as they are faster, non-invasive and enable pre and post op studies. Improved algorithms have solved the problem of accuracy of out-of-plane translation [1,2]. The aim of this study is to apply these new algorithms to the post op case.

In this study, Computer-Aided Design (CAD) models of the femoral and tibial components were registered to fluoroscopic images. The prosthesis (RBK knee, Global Orthopaedic Technology), was implanted into a sawbones knee. A perspex cage held the knee static while simultaneous fluoroscopy and dual X-rays were taken from 0 and 90 degrees flexion. Translations orthogonal to the fluoroscope were simulated by sliding the cage at 5 mm intervals. The CAD models were then registered with the fluoroscopy frames. Registration information was used to perform kinematic analysis.

This study has demonstrated greater accuracy for the post operative than pre-operative registration applications. The standard deviation of error for flexion/extension was 0.23° with respect to RSA. The average standard deviation of error for out-of-plane rotations (i.e. abduction/adduction and internal/external rotation) was 0.46°. Translations such as anterior-posterior drawer, compression/distraction and medio-lateral shift had errors of 0.16 mm, 0.17 mm and 0.59 mm, respectively. Both the registration and kinematic analysis accuracies for prosthesis components were superior to those for registration of natural (e.g. cadaver) bones [1]. While rotation accuracies improved about 0.1°, improvement in translation was substantial. In particular, medio-lateral translation accuracy has improved from 1 mm (in our previous study) to 0.59 mm, which is promising. It is worth noting that the best reported accuracy for out-of-plane or medio-lateral translation has been 1.03 mm [2]. Hence, this technique is competitive with other 3D/2D registration methods reported in the literature.

Our experiments show that our 3D CAD to 2D fluoroscopy registration method is sufficiently accurate to produce confident and reliable analysis of prospective kinematics studies.

The standard approach for kinematic analysis of knee joints has been roentgen stereophotogrammetry (RSA). This approach requires implanting tantalum beads during surgery so pre- and post-surgery comparisons have not been conducted. CT- fluoroscopy registration is a non-invasive alternative but has had accuracy and speed limitations. Our new algorithm addresses these limitations.

Our approach to the problem of registering CT data to single-plane fluoroscopy was to generate a digitally reconstructed radiograph (DRR) from the CT data and then filter this to produce an edge-enhanced image, which was then registered with an edge-enhanced version of the fluoroscopy frame. The algorithm includes a new multi-modal similarity measure and a novel technique for the calculation of the required gradients.

Three lower limb specimens were implanted with 1 mm tantalum beads to act as fiducial markers. Fluoroscopy data was captured for a knee flexion and femur and tibia CT data was registered to the fluoroscopy images.

A previous version of our algorithm (developed in 2008) showed good accuracy for in-plane translations and rotations of the knee bones. However, this algorithm did not have the ability to accurately determine out-of-plane translations. This lack of accuracy for out-of-plane translations has also been the major limitation of other single-plane 2D-3D registration algorithms. Fregly et. al. and Dennis et. al. reported standard deviations for this measurement of 5.6 and 3.03 mm respectively. The latest version of our algorithm achieves error standard deviations for out-of-plane translations of 0.65 mm. The algorithm includes a new similarity measure, which calculates the sum of the conditional variances (SCV) of the joint probability distributions of the images to be registered. This new similarity measure determines the true 3D position of the bones for a wider range of initial disparities and is also faster than the cross-cumulative residual entropy (CCRE) measure used in the 2008 version. For a set of initial 3D positions ranging from ± 5 pixels and ± 5 degrees the proposed approach successfully determined the correct 3D position for 96% of cases–whilst the approach using CCRE was successful for only 49% of cases. The algorithm also required 60% less iterations than the previous CCRE approach.

The new registration algorithm developed for the project provides a level of accuracy that is superior to other similar techniques. This new level of accuracy opens the way for a non-invasive mechanism for sophisticated kinematic analysis of knee joints. This will enable prospective, longitudinal and controlled studies of reconstruction surgery.