technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancertechnical note验证的半自动图像分析软件应用雌激素和孕激素受体检测在乳腺癌.pdf

Krecsák et al. Diagnostic Pathology 2011, 6:6 /content/6/1/6 RESEARCH Open Access Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer 1 2* 3 2 3 3 4 László Krecsák , Tamás Micsik , Gábor Kiszler , Tibor Krenács , Dániel Szabó , Viktor Jónás , Gergely Császár , 4 3 3 3,5 László Czuni , Péter Gurzó , Levente Ficsor , Béla Molnár 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 Pannoramic™ Viewer 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