Tumour knee replacement planning in a 3D graphics system

Limb salvage surgery has replaced amputation as the treatment of choice for sarcomas of the extremities. However, complications such as prosthesis loosening and fracture of bone or prosthesis continue to occur due to poorly aligned prosthesis or unconsidered bone deformities. These can be minimized by detailed implantation planning: intervention, resection, selection, and alignment decisions considering anatomical variations. Previous works employed interactive identification of anatomical landmarks, and prosthesis position planning by superimposing prosthesis drawing on radiographic image, which is cumbersome and error-prone. We present an automated methodology for mega endoprosthesis implantation planning in a 3D computer graphics environment. First, a virtual anatomical model is reconstructed by stacking and segmenting CT scan images. A neighborhood configuration based 3D visualization algorithm has been developed for fast rendering of the volumetric data, enabling a quick understanding of anatomical structures. Key skeletal landmarks used for implantation are automatically localized using curvature analysis of the 3D model and knowledge based rules. Anatomical details (mainly dimensions and reference axes) are extracted based on the landmarks and used in resection planning. A decision support method has been developed for segregating prosthesis components into three sets: 'most suitable', 'probably suitable', and 'not suitable' for a particular patient. The geometrical landmarks of the prosthesis components are mapped with respect to the anatomical landmarks of the patient's model to derive alignment relationships. 3D curved medial axes of both (prosthesis and anatomical models) are used for reference and alignment. A set of selection and positional accuracy measures have been developed to evaluate the anatomical conformity of the prosthesis. The computer-aided methodology is illustrated for tumour knee endoprosthetic replacement. It is shown to reduce the time required for implantation planning and improve the quality of outcome. The 3D environment is also more intuitive and easy-to-use than the traditional approach relying on 2D images