In open spine surgery, the accuracy of image guidance is compromised by alignment change between supine preoperative CT images (pCT) and prone intraoperative positioning. We have developed a level-wise registration framework to compensate for the intervertebral motion by updating pCT to match with intraoperative stereovision (iSV) data of the exposed spine. In this study, we compared performance of the iSV image updating system in different lengths of exposure using retrospective data from one cadaver pig specimen. Specifically, L1 to L6 were exposed and 3 metallic mini-screws were implanted on each level as “ground truth” locations. The spine was positioned supine to acquire pCT, and then positioned prone to acquire iSV using a hand-held iSV device. One image pair of iSV was acquired from each exposed vertebra. Three exposure lengths were evaluated by selecting data from corresponding levels to compare performance: 6 levels, 4 levels, and 3 levels. Accuracy of iSV updating was assessed through point-to-point registration error (ppRE) using mini-screw locations, and the average accuracy was 1.26±0.77 mm, 1.54±0.62 mm, and 1.38±0.44 mm, for the three exposure lengths, respectively. The time cost was ~10-15 min and similar in all three exposure sizes. Results indicate that performance of iSV image updating was similar in different lengths of exposure, and the accuracy was within clinically acceptable range (2 mm).
The accuracy of image guidance in spinal surgery can be compromised by intervertebral motion between preoperative supine CT images and intraoperative prone positioning. Patient registration and image updating approaches have been developed to register CT images with intraoperative spine and compensate for posture and alignment changes. We have developed a hand-held stereovision (HHS) system to acquire intraoperative profiles of the exposed spine and facilitate image registration and surgical navigation during open spinal surgery. First, we calibrated the stereo parameters using a checkerboard pattern, and the mean reprojection error was 0.33 pixel using 42 image pairs. Second, we attached an active tracker to the HHS device to track its location using a commercial navigation system. We performed spatial calibration to find the transformation between camera space and tracker space, and the error was 0.73 ± 0.39 mm. Finally, we evaluated the accuracy of the HHS using an ex-vivo porcine specimen. We used a tracked stylus to acquire locations of landmarks such as spinous and transverse processes, and calculated the distances between these points and the reconstructed stereovision surface. The resulting accuracy was 0.91 ± 0.58 mm, with an overall computational efficiency of ~ 5s for each image pair. Compared to our previous microscope-based stereovision system, the accuracy and efficiency of HHS are similar while HHS is more practical and functional, and would be more broadly applicable in spine procedures.