Miniature Screws, often used for fiducials, are currently localized on DICOM images manually. This time-consuming process can add tens of minutes to the computational process for registration, or error analysis. Through a series of morphological operations, this localization task can be completed in a time much less than a second when performed on a standard laptop. Two image sets were analyzed. The first data set consisted of six intraoperative CT (iCT) scans of the lumbar spine of both cadaver and live porcine samples. This dataset includes not only implanted mini-screws, but other metal instrumentation. The second dataset consists of 6 semi-rigidly deformed CT (uCT) scans of the lumbar spine of the same animals. This dataset has been intensity down sampled from 16 bits to eight bits as a pre-processing step. Also, due to other deformation steps, other artifacts are apparent. Both datasets show at least 18 mini-screws which were rigidly implanted in the lumbar vertebrae. Each vertebra has at least three mini-screws implanted. These images were processed as follows: projection image forming via maximum row values, thresholding, opening, non-circular regions were removed, and circular regions were eroded. Leaving voxel locations of the center of each mini-screw. The aforementioned steps can be completed with a mean computational efficiency of .0365 seconds. Which is an unobtainable time for manual localization. Even by the most skilled. The true positive rates of the iCT and uCT datasets were 96.
Background: Successful navigation in spine surgeries relies on accurate representation of the spine’s interoperative pose. However, its position can move between preoperative imaging and instrumentation. A measure of this motion is a preoperative-to-intraoperative change in lordosis. Objective: To investigate the effect this change has on navigation accuracy and the degree to which an interoperative stereovision system (iSV) for intraoperative patient registration can account for this motion. Methods: For six live pig specimens, a preoperative CT (pCT) was obtained of the lumbar spine in supine position and an interoperative CT in the prone position. Five to six iSV images were intraoperatively acquired of the exposed levels. A fiducial-based registration was performed on a navigation system with the pCT. Separately, the pCT was deformed to match iSV surface data to generate an updated CT (uCT). Navigational accuracy of both the commercial navigation and iSV systems was determined by tracked fiducials and landmarks. Change in lordosis Cobb angle between supine and prone positions was calculated representing preoperative-to-interoperative change in spine pose. Results: The preoperative-to-interoperative change ranged from 12 to 41°. Registration accuracy varied by 4.8 and 1.5 mm for the commercial system (6.2+-1.9 mm) and iSV (3.0+0.6 mm) respectively. Rank correlation shows strong association between increased registration error and positional change for the commercial system (correlation of 0.94, P=0.02) while minimal association for iSV (0.09, P=0.92). Conclusion: Change in spinal pose effects navigational accuracy of commercial systems. iSV shows promise in accounting for these changes given its accuracy is uncorrelated with pose change.
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