Predicting Femoral Geometry from Anatomical Features

Knee replacement surgery is a common orthopaedic procedure that greatly benefits from a three-dimensional geometric representation of a patient’s knee bone obtained from MR or CT data. The use of these image modalities pose the following challenges: (i) high imaging cost; (ii) long wait times; (iii) limited availability and (iv) in the latter, large exposure to ionizing radiation. Traditional approaches based on planar X-ray radiography are significantly less prone to these issues; however, they only provide two-dimensional information. This work presents a proof of concept study for generating patient-specific femoral bone shapes from a statistical shape atlas using anatomical features acquired from calibrated X-ray radiographs. Our hypothesis was: three-dimensional geometry can be reconstructed, within 2 millimeters RMS, by identifying features on two calibrated radiographs. We illustrate the feasibility of our approach with regards to acquiring features and the viability of reconstructing patient-specific bony anatomy. A set of reliable and relevant features is identified for which an acquisition protocol and user-interface was devised to minimize inter-observer variability. Both the data and methods used to construct the atlas are discussed as well generating shapes from features. The reconstructions accuracy was comparable to, albeit lower than, competing approaches that rely on two-dimensional bony contours. i