Grant: Collaborative Health Research Projects (NSERC partnered)

Each year, thousands of Canadians undergo neurosurgery for resection of brain lesions such as tumours, epileptic foci and vascular malformations that are in close proximity to areas of the brain that are critical to movement, vision, sensation, or language. Accurate guidance information is required to balance two constraints: achieving maximal resection of pathological tissue while minimizing potential neurological deficits. Image-guided neurosurgery systems (i.e., a GPS for surgery) provide tools to visualize and interpret patient-specific volumes of anatomical, vascular and functional data to enable precise surgical interventions. Unfortunately, brain tissue can deform up to 30mm or more during surgery (known as brain shift). Over the past 15 years, Collins' NeuroImaging and Surgical Technologies (NIST) lab at the MNI has developed an open-source research image-guided surgery platform known as IBIS. Our novel contribution uses ultrasound, acquired intra-operatively, to achieve accurate patient-image registration, even in the presence of brain shift. However, our methods can sometimes be limitated in terms of accuracy, robustness, and anatomical coverage. We propose to integrate data from multiple sensors and multiple algorithms to accurately and robustly account for brain shift and allow for accurate guidance throughout surgery. To do this we will apply Kalman filters in a multi-channel registration framework. To reduce development costs and facilitate inter-lab collaborations, we will integrate our IBIS software into 3DSlicer to take advantage of a huge user base (280,000 downloads, 250+/week). Our industrial partner Synaptive Medical, a dynamic Toronto-based startup, will provide input, ensure commercial relevance and help trainees learn about development and commercialization of medical devices. Synaptive's help will facilitate translation of our image-guided technology to the operating room so that all patients can benefit from these tools.