Open Access Research

Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer

László Krecsák1, Tamás Micsik2*, Gábor Kiszler3, Tibor Krenács2, Dániel Szabó3, Viktor Jónás3, Gergely Császár4, László Czuni4, Péter Gurzó3, Levente Ficsor3 and Béla Molnár35

Author Affiliations

1 H-1063 Budapest, Podmaniczky u. 63, Hungary

2 Ist Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary

3 3DHISTECH Ltd., Konkoly-Thege Miklós út 29-33, Building 18, Budapest H-1121, Hungary

4 University of Pannonia, Faculty of Information Technology, I-012, Egyetem u. 10., 8200 Veszprém, Hungary

5 Hungarian Academy of Sciences, Clinical Gastroenterology Research Unit, Budapest, Hungary

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Diagnostic Pathology 2011, 6:6  doi:10.1186/1746-1596-6-6

Published: 18 January 2011

Abstract

Background

The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.

Methods

The effectiveness of two connected semi-automated image analysis software (NuclearQuant v. 1.13 application for PannoramicViewer v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.

Results

The detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.

Conclusions

NuclearQuant v. 1.13 application for PannoramicViewer v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.