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A NEW METHOD OF TWO-DIMENSIONAL–THREE-DIMENSIONAL REGISTRATION FOR POST-OPERATIVE CALCULATION OF HIP AND KNEE PROSTHESIS PLACEMENT



Abstract

Introduction and Aims: A method has been designed to accurately measure post-operative alignment of hip (acetabular) and knee (femoral and tibial) prosthetic components relative to the pre-operative plan. Conventional methods involve 2D measurements; this new method uses 2D-3D registration to align both the prosthesis and the pre-operative CT volume to the post-operative x-ray.

Method: The method uses an automatic approach to align a CAD model of the prosthesis to the post-operative x-ray. A rendering of the prosthesis is produced and overlaid onto the post-operative x-ray image. The prosthesis can be rotated and translated in 3D to match the outline of the rendering shown on the post-operative x-ray. An initial manual procedure is used to align the rendering of the bone surface from pre-operative CT to the bony anatomy on the post-operative x-ray. This manual registration position is then used as a starting position for an automated intensity-based registration algorithm.

Results: The automated intensity-based registration algorithm allowed 3D verification of the prosthesis position. A number of digitally reconstructed radiographs (DRRs) were produced by casting rays through the pre-operative CT volume. The DRRs were then compared with the post-operative X-ray image using a similarity measure. This similarity measurement was optimised using gradient decent-type search strategy to alter the rotation and translation parameters. If the Hounsfield numbers of the voxels, which the casting rays passed through, were integrated along the ray and projected onto an imaging plane, a radiograph-like image was produced. To concentrate the area of registration and thus quicken registration algorithm, the user also manually defined a region of registration interest. Hence, DRRs were only produced within the region of interest. Due to the large size of the pelvis and tube-like nature of the femur and tibia, a total of 10 starting positions were used for this algorithm. These starting positions were found by adding random Gaussian noise to the parameters found using the manual process. The registration position was defined as the final position that produced the best similarity measurement value.

Conclusion: Validation has demonstrated this method’s accuracy in calculating the post-operative position of acetabular and knee prostheses with respect to the pre-operative plan. The results are repeatable, robust and enable pre- and post-operative 3D implant position comparison. The inaccuracies observed with conventional methods due to incorrect alignment on x-ray are reduced.

These abstracts were prepared by Editorial Secretary, George Sikorski. Correspondence should be addressed to Australian Orthopaedic Association, Ground Floor, The William Bland Centre, 229 Macquarie Street, Sydney, NSW 2000, Australia.

One or more of the listed authors are receiving or have received benefits or support from a recognised academic body for the pursuance of the study.