A feature-based statistical shape model for geometric analysis of the human talus and development of universal talar prostheses.

Statistical data pertaining to anatomic variations of the human talus contain valuable information for advances in biological anthropology, diagnosis of the talar pathologies, and designing talar prostheses. A statistical shape model (SSM) can be a powerful data analysis tool for the anatomic variations of the talus. The main concern in constructing an SSM for the talus is establishing the true geometric correspondence between the talar geometries. The true correspondence complies with biological and/or mathematical homologies on the talar surfaces. In this study, we proposed a semi-automatic approach to establish a dense correspondence between talar surfaces discretized by triangular meshes. Through our approach, homologous salient surface features in the form of crest lines were detected on 49 talar surfaces. Then, the point-wise correspondence information of the crest lines was recruited to create posterior Gaussian process morphable models that non-rigidly registered the talar meshes and consequently established inter-mesh dense correspondence. The resultant correspondence perceptually represented the true correspondence as per our visual assessments. Having established the correspondence, we computed the mean shape using full generalized Procrustes analysis and constructed an SSM by means of principal component analysis. Anatomical variations and the mean shape of the talus were predicted by the SSM. As a clinically related application, we considered the mean shape and investigated the feasibility of designing universal talar prostheses. Our results suggest that the mean shape of (the shapes of) tali can be used as a scalable shape template for designing universal talar prostheses.