Evaluation of conoscopic holography for estimating tumor resection cavities in model-based image-guided neurosurgery
Amber L. Simpson, Kay Sun, Thomas S. Pheiffer, D. Caleb Rucker, Allen K. Sills, Reid C. Thompson, and Michael I. Miga, Vanderbilt University and Vanderbilt University Medical Center, Volume 61, Issue 6, Page:1833-1843
Approximately 70,000 primary brain tumors will present each year in the United States with approximately one third being malignant. Neurologic malignancies are the second leading cause of cancer-related death in children under the age of 20 and in males between the ages of 20-30. The primary treatment for these tumors is complete removal of the mass. Regardless of tumor status, the need to determine tumor extent as well as the surrounding eloquent structures during resection is fundamental to reducing the burden of neurological disease. With respect to surgical therapy, the deployment of visual displays that relate the patient’s exposed brain within the operating room to the preoperatively acquired high resolution neuroanatomical images has become commonplace. Surgeons use a pen-like device to point to a specific feature on the delicate brain anatomy and to see the corresponding location on the neuroanatomical images, facilitated by an interactive display.
Accurately mapping the intraoperative state of the patient to the preoperative image is a complex task further challenged by soft tissue changes due to surgical manipulation, swelling, and the application of pharmaceuticals. Inaccuracies in this mapping have the potential to compromise the surgeon’s ability to accurately localize tumor extents. Some advocate the use of expensive intraoperative imaging units to compensate for intraoperative tissue changes. We have demonstrated that intraoperatively acquired cortical surface geometric data can be used to: improve image-to-patient alignment, measure brain deformations during surgery, and drive a computational approach to brain shift correction during image-guided neurosurgery. With respect to the digitization technology described in this paper, it is clear that the conoprobe provides important real-time data regarding resection and adds another dimension to our non-contact instrumentation framework for soft-tissue deformation compensation for surgical navigation.
Keywords: image-guided neurosurgery, brain shift, computation modeling, intraoperative evaluation