Design and Accuracy Assessment of an Automated Image-Guided Robotic Osteotomy System

Abstract

Image-guided robotic spine surgery systems, currently used only for pedicle screw placement, have been in clinical use since 2004. Robotic spine osteotomy (bone removal and shaping), however, is still in the research phase. This article presents the development and evaluation of a KUKA-based image-guided robotic system that automates the osteotomy process, from automatic milling path determination to milling execution, using laminectomy as the experimental paradigm. An approach to quantify milling (overall path) and margin (from thecal sac penetration) accuracy is also described. System accuracy was evaluated in two experiments. In the first, common preoperative images and image fiducial points were used to perform a bilateral laminectomy on 10 identical 3D-printed vertebrae phantoms. In the second, individual preoperative images with individually identified fiducial points were used to perform a bilateral laminectomy on 4 identical 3D-printed vertebrae phantoms. The accuracy results for the first experiment were 0.19 ± 0.16 mm (milling) and 0.69 ± 0.37 mm (margin). For the second, the accuracy results were 0.24 ± 0.15 mm and 0.42 ± 0.26 mm, respectively. The results compare favorably to current accepted clinical standards for laminectomy. The system developed here implements a valuable new role for robotics in spinal surgery.