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Comparative scoring by visual and image analysis of cells in human solid tumors labeled for proliferation markers
Author(s) -
Weaver Jean R.,
Au Jessie L.S.
Publication year - 1997
Publication title -
cytometry
Language(s) - English
Resource type - Journals
eISSN - 1097-0320
pISSN - 0196-4763
DOI - 10.1002/(sici)1097-0320(19970201)27:2<189::aid-cyto11>3.0.co;2-q
Subject(s) - computational biology , biology , artificial intelligence , microbiology and biotechnology , pattern recognition (psychology) , computer science
This study determined the validity of an image analysis program developed to score individual cells in human solid tumors labeled by proliferating cell nuclear antigen (PCNA) or bromodeoxy‐uridine (BrdUrd). The program used nuclear size, grey level, and perimeter convexity to identify cells, and evaluated labeling by the fraction of nuclear area displaying positive immunostaining (MPB). Total cell number (TC) and BrdUrd or PCNA labeling index (LI) were evaluated in 142 images using visual (TC visual ,LI visual ) and image analysis (TC IA , LI IA ). Without the perimeter convexity criterion, image analysis resulted in a) TC IA equal to TC visual in spite of the presence of various non‐cellular objects and b) significant correlations between LI IA and LI visual for PCNA and BrdUrd, although for these markers the LI IA were 4 and 6% lower than their respective LI visual . Both visual and image analyses yielded significant inter‐investigator variation among three investigators (coefficient of variation between 8.2 and 47.5%) and significant intra‐investigator, inter‐day variation (coefficients of variation between 3.8 and 51.8%). We conclude that image analysis using size, grey level and MPB is a valid alternative to visual scoring of PCNA and BrdUrd LI in individual cells. Cytometry 27:189–199, 1997. © 1997 Wiley‐Liss, Inc.

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