Federal Grant Award Summary

Yale University received a $519,592 Project Grant from the National Cancer Institute under the Cancer Detection and Diagnosis Research program (CFDA 93.394) awarded on June 15, 2026, with a completion date of May 31, 2031. The grant supports research to develop and validate deep learning-derived magnetic resonance imaging (MRI) biomarkers for improved risk stratification and treatment selection in localized prostate cancer. Traditional risk assessment methods utilizing Gleason grade and prostate-specific antigen (PSA) levels have demonstrated limited effectiveness, and tissue-based genomic biomarkers, while promising, require specialized equipment and only evaluate a small percentage of the prostate gland. The research team will leverage multiparametric prostate MRI and artificial intelligence algorithms to create quantitative imaging biomarkers capable of identifying patients at highest risk for disease recurrence.

The primary deliverable under Aim 1 involves validation of the prognostic capability of MRI biomarkers across a multi-institutional cohort of 2,250 prostate cancer patients representing diverse demographics and genomic/clinical characteristics. This research directly addresses the Cancer Detection and Diagnosis Research program's objectives of developing accurate diagnostic techniques and methods for predicting disease course. The project is designed to overcome prior implementation challenges through robust external validation and resolution of informatics integration barriers, ultimately providing a low-cost, scalable biomarker solution applicable across varied clinical settings for enhanced patient stratification and personalized treatment decision-making.