Three-Dimensional Printing and Navigation in Bone Tumor Resection

One of the most promising advances raised by the current computer age is performing research “in silico,” which means computer-assisted. The objective of this chapter is firstly to evaluate if a 3D in-silico model of an oncological patient could be used to make a 3D-printed prototype in real scale, discriminating precisely healthy tissues, tumoral tissues and oncological margins. Secondly, the objective is to evaluate if this prototype could be representative enough to allow testing osteotomies under navigated guidance based on images. A tumor resection for a patient with diagnosed metaphyseal osteosarcoma of the proximal tibia was transferred into a rapid prototyping model, fabricated using 3D printing and representing different structures in different colors. The planned osteotomy was executed using Stryker Navigator to guide the cutting saw and the prototype was opened to verify the precision of the performed osteotomy. Both osteotomy planes showed successful correspondence with the safe margin, with a maximum error of 1 mm. The application of these techniques in general orthopedics would help to reduce the incidence of unforeseen intraoperative failures, contributing to obtain predictable surgical procedures. This would implement a new way of performing development, research and training in orthopedics and traumatology by in-silico technology

Automatic Scan Planning for Magnetic Resonance Imaging of the Knee Joint

Automatic scan planning for magnetic resonance imaging of the knee aims at defining an oriented bounding box around the knee joint from sparse scout images in order to choose the optimal field of view for the diagnostic images and limit acquisition time. We propose a fast and fully automatic method to perform this task based on the standard clinical scout imaging protocol. The method is based on sequential Chamfer matching of 2D scout feature images with a three-dimensional mean model of femur and tibia. Subsequently, the joint plane separating femur and tibia, which contains both menisci, can be automatically detected using an information-augmented active shape model on the diagnostic images. This can assist the clinicians in quickly defining slices with standardized and reproducible orientation, thus increasing diagnostic accuracy and also comparability of serial examinations. The method has been evaluated on 42 knee MR images. It has the potential to be incorporated into existing systems because it does not change the current acquisition protocol