What is the maximal possibility that a physician can detect a prostate cancer, given it is there? This research explores this issue from a statistical point of view and evaluates the theoretical results experimentally. We have collected 300 prostate specimens each with clinically localized cancers. We have reconstructed 300 computerized 3D prostate models from these collected prostate specimens. What we will present here is an innovative study we have done recently using the above 300 3D prostate models: First, a 3D prostate cancer distribution atlas has been built by mapping the 300 individual prostate models. Optimal biopsy protocols have then been developed based on the 3D cancer distribution atlas using nonlinear optimization techniques. By then, we have known, in theory, the maximal possible detection rate of prostate cancer with optimized biopsy. Finally, to experimentally evaluate the developed optimal biopsy protocols, a new generation of image-guided prostate biopsy system is being developed by dynamically fusing the optimal biopsy protocols as well as the 3D cancer atlas with the ultrasound images during in vivo biopsies. A physician performing the needle biopsy on a live patient using the developed image-guided prostate biopsy system will have a significantly improved understanding on where the biopsies should be placed, leading to an improved performance in terms of cancer detection.