Abstract
Computer assisted knee arthroplasty systems provide the surgeon with tools for planning the femoral and tibial cuts, automatic implant sizing, and precise guidance for the bone milling and sawing tools. These systems require 3D models of the patient’s proximal tibial epiphysis, and distal femoral epiphysis. Currently preoperative CT scans are used to construct these models. The high irradiation, financial and time cost of the CT motivated the research for an alternative. In this work we developed a system for reconstructing a 3D bone model from a set of points localized by the surgeon intra-operatively on the bone surface using an optical localizer.
A training set of 314 dry femurs, and 314 dry tibias (200 males, and 114 females) of Caucasian ethnicity was CT scanned, and segmented to create 3D models for these bones. These models were then used to extract the modes of variation for the femurs and tibias within each gender. Using these modes of variation along with the average model for the training set, a new femoral or tibial epiphysis model can be reconstructed. This reconstruction is performed by optimizing the average model’s morphology along the modes of variation to create a 3D model that matches the point cloud localized on the surface of the bone.
A set of 77 male and 71 female dry femur and tibia pairs was used to digitize a sparse point cloud on the knee joint using an optical localizer. These point clouds were then used to reconstruct their corresponding models using the aforementioned algorithm. An average error of 0.42 between the reconstructed and the CT models was obtained.
Correspondence should be addressed to Diane Przepiorski at ISTA, PO Box 6564, Auburn, CA 95604, USA. Phone: +1 916-454-9884; Fax: +1 916-454-9882; E-mail: ista@pacbell.net
