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MRI-Derived Risk Maps to Predict Prostate Cancer Progression

Institution: University of California, San Francisco
Investigator(s): Susan Noworolski, Ph.D.
Award Cycle: 2019 (Cycle 28) Grant #: 28IR-0060 Award: $924,132
Subject Area: Cancer
Award Type: High Impact Research Project Award

Initial Award Abstract

Prostate cancer is extremely prevalent, striking >15,000 Californian men per year. With the risk of treatment side effects being high (77%) and the risk of short-term progression of prostate cancer being low (20%), men deemed at low-risk of progression to spread of the cancer outside the prostate are recommended to follow active surveillance. Unfortunately, about 80% of these men instead undergo treatment, in large part due to the poor predictive accuracy of current, clinical indicators of risk of progression.

The amount of aggressive disease is currently accepted to be the best predictor for prostate cancer progression. However current methods to assess this are based on evaluating biopsy samples of the prostate, which only test small portions of the prostate and can thus mischaracterize the cancer. Multiparametric MRI (mpMRI) may be able to overcome this limitation by imaging the entire prostate. However, current mpMRI methods rely on qualitative assessments of limited parameters which are not sensitive enough for accurate prediction of progression.

In the proposed study, we will leverage our state-of-the-art mpMRI, translated to the clinic in 2015 and performed more than 30 times a week, and our novel, mpMRI analyses to detect cancer and aggressive cancer in the prostate. We will create maps of the prostate showing brighter areas where there is higher risk of cancer and maps with brighter areas for higher risk of aggressive cancer. We will test if the bright cancer volumes from these maps can be used to identify and to predict prostate cancer progression. We will also test if combinations of these measures with clinical measures perform better than current methods. Lastly, we will automate creating these risk maps and test providing them to radiologists, similar to how they review standard images, to facilitate translation to the clinic.

This project addresses the TRDRP’s cancer prevention, treatment and biology research priority. It is in the area of translational cancer research, centered on early detection and prediction of progression of cancer to plan treatment strategies. The proposed methods to predict risk of progression based on the MRI risk-maps are expected to help guide doctors and their prostate cancer patients in choosing therapy or in following active surveillance, to ultimately reduce morbidity and mortality from prostate cancer.