Identifying ambiguous prostate gland contours from histology using capsule shape information and least squares curve fitting

Abstract

Objective To obtain an accurate assessment of the percentage and depth of extra-capsular soft tissue removed with the prostate by the various surgical techniques in order to help surgeons in determining the appropriateness of different surgical approaches. This can be enhanced by an accurate and automated means of identifying the prostate gland contour. Materials and MethodsTo facilitate 3D reconstruction and, ultimately, more accurate analyses, it is essential for us to identify the capsule boundary that separates the prostate gland tissue from its extra-capsular tissue. However, the capsule is sometimes unrecognizable due to the naturally occurring intrusion of muscle and connective tissue into the prostate gland. At these regions where the capsule disappears, its contour can be arbitrarily created with a continuing contour line based on the natural shape of the prostate. We utilize an algorithm based on a least squares curve fitting technique that uses a prostate shape equation to merge previously detected capsule parts with the shape equation to produce an approximated curve that represents the prostate capsule. Results We have tested our algorithm using three different shapes on 13 histologic prostate slices that are cut at different locations from the apex. The best result shows a 90% average contour match when compared to pathologist-drawn contours. ConclusionWe believe that automatically identifying histologic prostate contours will lead to increased objective analyses of surgical margins and extracapsular spread of cancer. Our results show that this is achievable.