Tissue architecture analysis in prostate cancer and its precursors: An innovative approach to computerized histometry.

Abstract

It is the aim of these studies to derive a numerically defined progression index for prostatic intraepithelial neoplasia (PIN) lesions. Histometric and karyometric features were automatically extracted from images of histopathologic sections by a machine vision system. Both histometric and karyometric measures lend themselves to the defining of a progression index. Karyometric features were found to be more sensitive. They allow the detection of very early change. It is possible to measure progression of PIN lesions with precision. The methodology would lend itself for measurement of regression due to chemopreventive intervention.