Grant: Doctoral: Vanier Canada Graduate Scholarships

Supervisor: Drs. Parvin Mousavi and John Rudan, Queen's University Glioblastoma is one of the deadliest brain tumours in humans, with less than 5% of patients surviving 5 years after diagnosis. The current treatment involves brain tumour surgery to remove as much of the brain tumour as possible followed by radiation and chemotherapy. While radiation therapy successfully reduces tumor size, it sometimes creates areas of dead brain and/or tumor tissue at the site of treatment known as radionecrosis. Unlike tumor tissue which is generally removed as extensively as possible, radiation necrosis is managed much less aggressively. Unfortunately, radiation necrosis and tumor recurrence are almost indistinguishable on imaging, which makes it challenging for surgeons to plan a surgical strategy. Here we intend to adapt a tool (called the iKnife) that analyzes smoke from tissues cauterized (burned) during surgery to differentiate tumor tissues from radiation necrosis tissue. To do this we are building a library of tumor and radiation necrosis tissues and training our systems on the smoke produced from these. Once we have finished training and validating this technology, we hope to implement this in live operations to help surgeons make surgical decisions in real-time. We believe that this research will allow for the implementation of this tool in a surgical setting resulting in better patient outcomes and quality of life.