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

Abstract

Aims: It is the aim of these studies to derive a numerically defined progression index for prostatic intraepithelial neoplasia (PIN) lesions. Methods: Histometric and karyometric features were automatically extracted from images of histopathologic sections by a machine vision system. Results: 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. Conclusions: It is possible to measure progression of PIN lesions with precision. The methodology would lend itself for measurement of regression due to chemopreventive intervention.