Histological Image Processing Features Induce a Quantitative Characterization of Chronic Tumor Hypoxia.

ABSTRACT: Hypoxia in tumors signifies resistance to therapy. Despite a wealth of tumor histology data, including anti-pimonidazole staining, no current methods use these data to induce a quantitative characterization of chronic tumor hypoxia in time and space. We use image-processing algorithms to develop a set of candidate image features that can formulate just such a quantitative description of xenographed colorectal chronic tumor hypoxia. Two features in particular give low-variance measures of chronic hypoxia near a vessel: intensity sampling that extends radially away from approximated blood vessel centroids, and multithresholding to segment tumor tissue into normal, hypoxic, and necrotic regions. From these features we derive a spatiotemporal logical expression whose truth value depends on its

SUBMITTER: Sundstrom A 

PROVIDER: S-EPMC4836667 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature