Intra-operative navigation began with the localization of subsurface structures in cranial neurosurgery using frame-based stereotaxy. Advances in imaging and computing power have led to the development of modern frameless three-dimensional (3D) computer-assisted navigation (CAN), employed across multiple surgical disciplines. In spinal surgery, CAN may guide implant placement, bony decompression and soft-tissue resection. However, adoption of 3D CAN by spinal surgeons has been limited by cumbersome registration protocols, workflow disruption, high capital cost, and questionable quantitative and clinical utility. A novel technique for image-to-patient registration has recently been developed, based on optical topographic imaging (OTI). Whether OTI-based CAN is able to provide accurate intra-operative image-guidance for common spinal procedures, while addressing current limitations of CAN techniques, warrants study. First, we explored the current paradigms of reporting CAN accuracy in the context of spinal procedures, finding that quantitative application accuracy and radiographic screw placement do not correlate. We therefore proposed a combined quantitative and radiographic system of reporting CAN accuracy. Second, we examined the registration workflow and accuracy of OTI-CAN in open posterior thoracolumbar instrumentation, in pre-clinical swine and cadaveric models and subsequently in clinical in-vivo testing. We found that OTI-CAN is comparably accurate to but significantly faster than existing 3D CAN techniques. We subsequently found that OTI-CAN was similarly accurate, with maintained workflow improvements, in minimally-invasive (MIS) thoracolumbar and open cervical approaches. Finally, we explored mechanisms by which current CAN and specifically surface-based registration techniques, including OTI, may fail. We found that navigation error increases with greater working distance to the dynamic reference frame (DRF), and with greater geometric symmetry over the osseous posterior elements. Taken together, this body of work demonstrates that OTI is a feasible technique for spinal CAN, and may alleviate the primary issues plaguing current systems to allow increased adoption into settings where CAN may be most useful.Ph.D.2019-11-16 00:00:0
