Total knee replacement (TKR) design aims to restore normal kinematics with emphasis on flexion range. The survivorship of a TKR is dependent on the kinematics in six-degrees-of-freedom (6-DoF). Stepping up, such as stair ascent is a kinematically demanding activity after TKR. The debate about design choice has not yet been informed by 6-DoF in vivo kinematics. This prospective randomised controlled trial (RCT) compared kneeling kinematics in three TKR designs.

68 participants were randomised to receive either cruciate retaining (CR-FB), rotating platform (CR-RP) or posterior stabilised (PS-FB) prostheses. Image quality was sufficient for 49 of these patients to be included in the final analysis following a minimum 1-year follow-up. Patients completed a step-up task while being imaged using single-plane fluoroscopy. Femoral and tibial computer-aided design (CAD) models for each of the TKR designs were registered to the fluoroscopic images using bespoke software OrthoVis to generate six-degree-of-freedom kinematics. Differences in kinematics between designs were compared as a function of flexion.

There were no differences in terminal extension between the groups. The CR-FB was further posterior and the CR-RP was more externally rotated at terminal extension compared to the other designs. Furthermore, the CR-FB designs was more posteriorly positioned at each flexion angle compared to both other designs. Additionally, the CR-RP design had more external femoral rotation throughout flexion when compared with both fixed bearing designs. However, there were no differences in total rotation for either step-up or down. Visually, it appears there was substantial variability between participants in each group, indicating unique patient-specific movement patterns.

While use of a specific implant design does influence some kinematic parameters, the overall patterns are similar. Furthermore, there is high variability indicating patient-specific kinematic patterns. At a group level, none of these designs appear to provide markedly different step-up kinematic patterns. This is important for patient expectations following surgery. Future work should aim to better understand the unique patient variability.

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.

To better understand the functional effects of pathologies, a system to capture accurate real-time 3D imaging of functional activities, without the limitations of RSA, is desirable. To address this problem, a new registration algorithm was developed to automatically determine the 3D kinematics of the knee using commonly available imaging modalities.

To evaluate this new registration algorithm, three cadaveric knees were implanted with 1mm tantalum beads to act as gold standard fiducial markers. The knees were flexed between 0 and 90° and fluoroscopy data was captured at a rate of 25 frames/sec and a resolution of 0.5 mm/pixel (Axiom Artis MP). “Pin-cushion” distortion and beam spreading were accounted for. CT data was captured using a Toshiba Aquillon 16 using bone and soft tissue algorithms. For every frame of the fluoroscopy data, the 3D femur and tibia data was individually registered to the fluoroscopy images using the new algorithm. This position data was then used to generate a kinematic 3D model. Similar fluoroscopy-to-CT registration techniques have been proposed for stationary image-guided surgery applications. The majority of these techniques use fluoroscopy images projected onto at least two different planes (with some systems using as many as 18 planes). Other techniques have been proposed that use a single-plane but require stochastic optimization procedures that perform in the order of 500 iterations to find the optimal 3-D registration. The reported average target registration errors (TREs) of these systems range from 0.5–1.2 mm. The newly developed registration technique requires only a single-plane fluoroscopy image and uses a novel gradient-descent optimization strategy that converges to the optimal 3-D position within 20–30 iterations. Preliminary results demonstrate that the performance of the new registration algorithm is able to align the bones of the knee with an average TRE of 0.57 mm. Up to 7 degrees of concurrent axial rotation was observed during flexion of the knees to 90°. The new registration algorithm developed for the project is capable of automatically determining the 3D kinematics of a knee joint using only single-plane fluoroscopy data. The new algorithm requires approximately one-tenth the number of iterations to find the optimal registration position when compared with existing single-plane techniques. Once it is established in vivo that this image registration technique has the accuracy of RSA, this method will permit real-time kinematic studies without tantalum beads. This will enable prospective longitudinal and controlled studies of reconstruction surgery, and conservative management of joint pathologies.