The goal of this study is to apply cutting-edge imaging approaches, incorporating
machine-learning for pattern recognition and multispectral analysis, to the development and
validation of intermediate endpoint biomarkers in benign tissue that characterize the
response to 5α-reductase inhibitor chemoprevention as well as the risk of prostate cancer
among men with negative biopsies.