Grant: Collaborative Health Research Projects (NSERC partnered)

"Prostate cancer is the leading incident cancer in Canadian men. A standard treatment of organ confined prostate cancer is radical surgical extirpation of the prostate via open, laparoscopic, or robot assisted radical prostatectomy. While the long term prognosis of prostate cancer patients has improved significantly over the past two decades, there are still significant rates of positive surgical margins, leading to possible cancer recurrence, and complications, such as impotence and incontinence. Robot-assistance provides improved visualization and dexterity to the surgeon for improved outcomes. However, there remains a lack of guidance tools available to the surgeon for real time, in-field determination of prostate region anatomy, and for the determination of tumor location, extension and proximity to critical structures such as cavernosal nerves. It is the goal of our research to provide such guidance tools in the form of an augmented reality system for robot-assisted radical prostatectomy. We plan to use intra-operative endorectal ultrasound imaging to improve guidance for robot-assisted surgery. Several types of image acquisition modes - B-mode, Doppler, elastography - will be used to improve the delineation of the prostate boundary. This will help determine appropriate surgical planes at the bladder neck, at the striated urethral sphincter, and adjacent to the nerves and the rectum. Periprostatic nerve location will be inferred from the location of the associated blood vessels in Doppler images. Cancer location and the likelihood of extension of cancer outside the prostate will also be imaged using ultrasound elastography. To judge the quality of our ultrasound imaging quality, we will use magnetic resonance imaging (MRI) of the same patients, as magnetic resonance imaging provides the best rendering of anatomical detail. To determine whether ultrasound combined with MRI can determine cancer location, we will use histopathology of the extirpated tissue after surgery. The magnetic resonance images, corresponding segmented anatomy and likely cancer location derived from them, will be registered to the intra-operative ultrasound images and displayed in the correct location during surgery. Our image guidance system will be integrated with the visualization and localization tools available for the da Vinci surgical robot. "