Grant: Collaborative Health Research Projects (NSERC partnered)

Confirming the location, extent, and grade of prostate cancer for diagnostic and therapeutic purposes remains challenging due to the architectural and phenotypic heterogeneity. In the case of blind systematic ultrasound-guided biopsies, this leads to more than 30% of false negative rates, while for tumor-targeted (focal) therapies such as brachytherapy, their success hinge on precise mapping of MRI cancer targets to provide the gross tumor location, but lack molecular information at the treatment location, without accurate grading of the tumor and can lead to a poor balance of toxicities. Therefore, there is no existing medical technologies addressing the timely confirmation of tumor location/grade during therapy. Our objective is to develop an image-guidance system integrating real-time molecular tissue characterization with an optical Raman spectroscopy (RS) instrument for tumor-targeted prostate cancer interventions, improving tumor localization and characterization. Specifically, we will develop and conduct first in-human studies using a real-time navigation platform technology allowing for high-precision and tumor-specific harvesting of samples during biopsy procedures. Four research aims will be completed to insure in-human translation of the technology into to our partners Elekta and Philips Canada within 3 years: (1) Develop a fiber optics RS needle device for tissue characterization to guide prostate interventions; (2) Train supervised machine-learning algorithms from spectral RS signatures to infer biological properties; (3) Implement an integrated image-guidance platform with real-time RS tissue classification and needle tracking to identified MRI targets with prostate motion compensation; (4) Conduct a pilot clinical study patients with localized PCa visible on MRI and who will undergo HDR brachytherapy. Ultimately, we will have a high-end technique clinically tested in prostate interventions for practical molecular identification and cancer detection.