An Integrated CT-based Image-Guided Neurosurgical System

DESCRIPTION (provided by applicant): Image-guidance is revolutionizing many medical procedures by providing anatomical information and instrument position during interventions which, in turn, allows for minimally invasive techniques and access to ordinarily inaccessible parts of body. In many difficult procedures that involve vital structures, like the resection of tumors at the skull base, image-guidance can be a necessity. In such cases, the accuracy of the image guidance is often limited by the accuracy of imaging (especially registration). A fully integrated intraoperative image-guidance system combines both the imaging and guidance hardware into a single functioning system that can acquire highly accurate imagery repeatedly within the operating room (OR) environment. Such imagery is well-registered with the true patient coordinates since registration steps are not specifically needed. Moreover, having an intraoperative imager allows one to monitor changes in anatomy throughout a procedure and to assess progress. Such integrated systems have a great advantage over nonintegrated systems where the imagery is collected prior to a procedure followed by registration (i.e.: no updates, more chances for misregistration). Integrated systems based on magnetic resonance imaging are highly attractive due to image quality and lack of ionizing radiation; however, such units place heavy constraints on the OR and are very costly. Units based on ultrasound are inexpensive, but produce relatively poor imagery and are not suitable for regions near bony structures. To date a highly compact, interactive, inexpensive, integrated imaging and guidance system based on x-ray computed tomography (CT) has not been developed. Such a unit would fill a "modality vacancy" in intraoperative imaging and guidance, would provide updatable images familiar to surgeons, and would be particularly suited to difficult procedures like skull base surgery. We propose not only to build such a system (leveraging off previous developments at Xoran Technologies, Inc. for reducing the size of the imager and the effective dosage) but to evaluate the device through clinical trials for the specific task of resection of brain tumors.