Literature DB >> 21512768

Digital image analysis of membrane connectivity is a robust measure of HER2 immunostains.

Anja Brügmann1, Mikkel Eld, Giedrius Lelkaitis, Søren Nielsen, Michael Grunkin, Johan D Hansen, Niels T Foged, Mogens Vyberg.   

Abstract

The purpose of this study was to develop and validate a new software, HER2-CONNECT(TM), for digital image analysis of the human epidermal growth factor receptor 2 (HER2) in breast cancer specimens. The software assesses immunohistochemical (IHC) staining reactions of HER2 based on an algorithm evaluating the cell membrane connectivity. The HER2-CONNECT algorithm was aligned to match digital image scorings of HER2 performed by 5 experienced assessors in a training set and confirmed in a separate validation set. The training set consisted of 167 breast carcinoma tissue core images in which the assessors individually and blinded outlined regions of interest and gave their HER2 score 0/1+/2+/3+ to the specific tumor region. The validation set consisted of 86 core images where the result of the automated image analysis software was correlated to the scores provided by the 5 assessors. HER2 fluorescence in situ hybridization (FISH) was performed on all cores and used as a reference standard. The overall agreement between the image analysis software and the digital scorings of the 5 assessors was 92.1% (Cohen's Kappa: 0.859) in the training set and 92.3% (Cohen's Kappa: 0.864) in the validation set. The image analysis sensitivity was 99.2% and specificity 100% when correlated to FISH. In conclusion, the Visiopharm HER2 IHC algorithm HER2-CONNECT(TM) can discriminate between amplified and non-amplified cases with high accuracy and diminish the equivocal category and thereby provides a promising supplementary diagnostic tool to increase consistency in HER2 assessment.

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Year:  2011        PMID: 21512768     DOI: 10.1007/s10549-011-1514-2

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  21 in total

1.  Impact of JPEG 2000 compression on deep convolutional neural networks for metastatic cancer detection in histopathological images.

Authors:  Farhad Ghazvinian Zanjani; Svitlana Zinger; Bastian Piepers; Saeed Mahmoudpour; Peter Schelkens; Peter H N de With
Journal:  J Med Imaging (Bellingham)       Date:  2019-04-24

2.  Quantitative digital imaging analysis of HER2 immunohistochemistry predicts the response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma.

Authors:  Aidan C Li; Jing Zhao; Chao Zhao; Zhongliang Ma; Ramon Hartage; Yunxiang Zhang; Xiaoxian Li; Anil V Parwani
Journal:  Breast Cancer Res Treat       Date:  2020-01-30       Impact factor: 4.872

3.  Digital separation of diaminobenzidine-stained tissues via an automatic color-filtering for immunohistochemical quantification.

Authors:  Rong Fu; Xiaomian Ma; Zhaoying Bian; Jianhua Ma
Journal:  Biomed Opt Express       Date:  2015-01-15       Impact factor: 3.732

Review 4.  Progress on deep learning in digital pathology of breast cancer: a narrative review.

Authors:  Jingjin Zhu; Mei Liu; Xiru Li
Journal:  Gland Surg       Date:  2022-04

5.  Free digital image analysis software helps to resolve equivocal scores in HER2 immunohistochemistry.

Authors:  Henrik O Helin; Vilppu J Tuominen; Onni Ylinen; Heikki J Helin; Jorma Isola
Journal:  Virchows Arch       Date:  2015-10-22       Impact factor: 4.064

6.  Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays.

Authors:  Aida Laurinaviciene; Darius Dasevicius; Valerijus Ostapenko; Sonata Jarmalaite; Juozas Lazutka; Arvydas Laurinavicius
Journal:  Diagn Pathol       Date:  2011-09-23       Impact factor: 2.644

7.  Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring.

Authors:  Anthony E Rizzardi; Arthur T Johnson; Rachel Isaksson Vogel; Stefan E Pambuccian; Jonathan Henriksen; Amy Pn Skubitz; Gregory J Metzger; Stephen C Schmechel
Journal:  Diagn Pathol       Date:  2012-06-20       Impact factor: 2.644

8.  HER2 Molecular Marker Scoring Using Transfer Learning and Decision Level Fusion.

Authors:  Suman Tewary; Sudipta Mukhopadhyay
Journal:  J Digit Imaging       Date:  2021-03-19       Impact factor: 4.903

9.  Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association.

Authors:  Haydee Lara; Zaibo Li; Esther Abels; Famke Aeffner; Marilyn M Bui; Ehab A ElGabry; Cleopatra Kozlowski; Michael C Montalto; Anil V Parwani; Mark D Zarella; Douglas Bowman; David Rimm; Liron Pantanowitz
Journal:  Appl Immunohistochem Mol Morphol       Date:  2021-08-01

10.  Astronomical algorithms for automated analysis of tissue protein expression in breast cancer.

Authors:  H R Ali; M Irwin; L Morris; S-J Dawson; F M Blows; E Provenzano; B Mahler-Araujo; P D Pharoah; N A Walton; J D Brenton; C Caldas
Journal:  Br J Cancer       Date:  2013-01-17       Impact factor: 7.640

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