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Photoshop-based image analysis for the semiautomated assessment of Ki-67-defined proliferative activity in the routine diagnosis of breast cancer
A simple Macintosh-based image analysis system using consumer-level software was applied to quantitative immunocytochemistry. In three representative x20 fields of 26 infiltrating breast cancers, the number of nuclei were counted that were immunostained with the antibody MIB-1, directed to the cell cycle-specific nuclear antigen Ki-67. The computer-generated proliferative rate exhibited a high linear correlation with visually estimated (r(2) = 0.852, (p < 0.0001) and manually counted proliferative rates (r(2) = 0.643,p < 0.0001). The computer-generated proliferative rate correlated significantly with flow cytometric S-phase fractions (r(2) = 0.345 and r(2) = 0.402, without and with cytokeratin gating, respectively; p < 0.0001) and with histologic and nuclear tumor grades (p < 0.005 and p < 0.039, respectively). No statistically significant interrelationship was found with other prognostic parameters (tumor type, tumor size, hormone receptor expression, overexpression of c-erb B-2 oncogene or of the tumor suppressor gene product p53). This study confirms the interrelationships observed in previous studies between proliferative rate of breast cancers and other prognostic parameters. It presents a Macintosh-based image analysis system as an inexpensive simple tool for the accurate, transparent, and reliable quantification of immunostained nuclei in routine diagnostic immunocytochemistry.
breast cancer, image analysis, proliferative rate, quantification, MONOCLONAL-ANTIBODY KI-67, S-PHASE FRACTION, CELL-PROLIFERATION, FLOW-CYTOMETRY, PROGNOSTIC FACTORS, NUCLEAR ANTIGEN, DNA CONTENT, CARCINOMA, IMMUNOHISTOCHEMISTRY, MACINTOSH
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