Discovery of Prostate-Specific Antigen in 1980s has led to widespread screening for prostate cancer, leading to earlier stage detection. This resulted in an unexpected problem: many cancers diagnosed using the PSA test have proven to be non-aggressive and slow growing and, hence, do not require urgent intervention (which can be associated with poorer quality of life and high costs). Conversely some slow growing cancers ultimately will behave aggressively and ultimately cause cancer death. Consequently, many men with slow growing cancers today will be treated for a disease that is unlikely to be fatal. There remains a clear need for a clinical tool to delineate aggressive and non-aggressive prostate cancers in a screening setting, allowing the tailoring of treatment to the individual needs of each prostate cancer patient and limiting the likelihood of over- or under-treatment. Ideally such a tool would be easily implemented and cost-effective. Differences in DNA ploidy, which is the amount of genetic material within the nuclei of cancer cells, can be associated outcomes for a variety of cancer types. Pilot data published by our group shows that DNA ploidy can predict the progression of prostate cancers; however this method is costly and laborious. We have pilot data that suggests the same or even better objective prognostic information can be obtained from the combination of measurements of cell nuclear features (describing DNA distribution patterns in the nucleus) and cell sociology features (describing cell organization within the tissue). We denote this as a "QDP" quantitative digital pathology approach, which can be performed in a much less labor intensive fashion on prostate biopsy core tissue than the DNA ploidy method. The goals of this proposal are to compare the DNA ploidy approach against a larger test of the QDP approach. Success in this work will yield a powerful new tool for managing prostate cancer patients and improving disease outcomes.