ArticleDiagnostic pathology2011
Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer.
Article in Diagnostic pathology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 37 citations in OpenAlex.
- Article
- Immunohistochemical Study of Ezrin Expression in Colorectal Carcinoma: A Comparative Study between Objective Method and Digital Quantitative Assessment.Asian Pacific journal of cancer prevention : APJCP · 2020Article
- Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.Diagnostic pathology · 2016Article
- Computer-based image analysis in breast pathology.Journal of pathology informatics · 2016Review
- Computer Aided Semi-Automated Evaluation of HER2 Immunodetection--A Robust Solution for Supporting the Accuracy of Anti HER2 Therapy.Pathology oncology research : POR · 2015Article
- Oestrogen receptors β1 and βcx have divergent roles in breast cancer survival and lymph node metastasis.British journal of cancer · 2014Article
- Exploring the spatial dimension of estrogen and progesterone signaling: detection of nuclear labeling in lobular epithelial cells in normal mammary glands adjacent to breast cancer.Diagnostic pathology · 2014Article
- Immunohistochemical analysis of medullary breast carcinoma autoantigens in different histological types of breast carcinomas.Diagnostic pathology · 2012Article
- Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring.Diagnostic pathology · 2012Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsThe 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-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.
resultsThe 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.
conclusionsNuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.
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