Histological Image Processing Features Induce a Quantitative Characterization of Chronic Tumor Hypoxia.
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 predicate clauses that are grounded in this histological evidence. As an alternative to the spatiotemporal logical formulation, we also propose a way to formulate a linear regression function that uses all of the image features to learn what chronic hypoxia looks like, and then gives a quantitative similarity score once it is trained on a set of histology images.
Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America.|Department of Computer Science, Courant Institute of Mathematical Sciences, New York, NY, United States of America.
Andrew
http://orcid.org/0000-0002-3378-4513
A
Sundstrom
Department of Biochemistry and Molecular Pharmacology, NYU School of Medicine, New York, NY, United States of America.
Elda
E
Grabocka
Department of Biochemistry and Molecular Pharmacology, NYU School of Medicine, New York, NY, United States of America.
Dafna
D
Bar-Sagi
Department of Computer Science, Courant Institute of Mathematical Sciences, New York, NY, United States of America.
Bud
B
Mishra
D000465:Algorithms; D000818:Animals; D045744:Cell Line, Tumor; D003110:Colonic Neoplasms / Q000473:pathology*; D006801:Humans; D000860:Hypoxia / Q000473:pathology*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D051379:Mice; D008819:Mice, Nude; D009593:Nitroimidazoles / Q000008:administration & dosage
D009593:Nitroimidazoles; C033815:pimonidazole