Literature DB >> 28248729

Virtual Double Staining: A Digital Approach to Immunohistochemical Quantification of Estrogen Receptor Protein in Breast Carcinoma Specimens.

Nina Lykkegaard Andersen1, Anja Brügmann, Giedrius Lelkaitis, Søren Nielsen, Michael Friis Lippert, Mogens Vyberg.   

Abstract

Visual assessment of immunohistochemically detected estrogen receptor protein is prone to interobserver and intraobserver variation due to its subjective evaluation. The aim of this study was to validate a new image analysis system based on virtual double staining (VDS) by comparing visual and automated scorings of ER in tissue microarrays of breast carcinomas. Tissue microarrays were constructed of 112 consecutive resection specimens of breast carcinomas. Immunohistochemistry assays for ER and pancytokeratin was applied on separate serial sections. ER scoring was visually performed by 5 observers using the histoscore (H-score) method. The Visiopharm ER image analysis protocol (APP) software application using VDS technique was applied separating stromal cells from carcinoma and other epithelial cells based on the pancytokeratin reaction. Using color deconvolution, polynomial filters, and nuclear segmentation the APP determined the percentage of positive cells and their intensity, and calculated the resulting H-score. On the basis of 1% cutoff VDS was perfectly correlated with visual assessment (κ=1). Using H-score, a very high agreement between VDS and visual ER assessment was seen (R=0.950). Image analysis has the attributes to eliminate the shortcomings of visual ER evaluation by generating automated, reproducible, and objective results of ER assessment.

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Year:  2018        PMID: 28248729     DOI: 10.1097/PAI.0000000000000502

Source DB:  PubMed          Journal:  Appl Immunohistochem Mol Morphol        ISSN: 1533-4058


  7 in total

1.  Magee Equations™ and response to neoadjuvant chemotherapy in ER+/HER2-negative breast cancer: a multi-institutional study.

Authors:  Rohit Bhargava; Nicole N Esposito; Siobhan M OʹConnor; Zaibo Li; Bradley M Turner; Ioana Moisini; Aditi Ranade; Ronald P Harris; Dylan V Miller; Xiaoxian Li; Harrison Moosavi; Beth Z Clark; Adam M Brufsky; David J Dabbs
Journal:  Mod Pathol       Date:  2020-07-13       Impact factor: 7.842

2.  Serine/threonine kinase 32C is overexpressed in bladder cancer and contributes to tumor progression.

Authors:  Erlin Sun; Kangkang Liu; Kun Zhao; Lining Wang
Journal:  Cancer Biol Ther       Date:  2018-10-25       Impact factor: 4.742

Review 3.  Assessment of estrogen receptor low positive status in breast cancer: Implications for pathologists and oncologists.

Authors:  Nicola Fusco; Moira Ragazzi; Elham Sajjadi; Konstantinos Venetis; Roberto Piciotti; Stefania Morganti; Giacomo Santandrea; Giuseppe Nicolò Fanelli; Luca Despini; Marco Invernizzi; Bruna Cerbelli; Cristian Scatena; Carmen Criscitiello
Journal:  Histol Histopathol       Date:  2021-09-29       Impact factor: 2.303

4.  CD164 promotes tumor progression and predicts the poor prognosis of bladder cancer.

Authors:  Xiao-Guang Zhang; Tong Zhang; Chang-Ying Li; Ming-Hao Zhang; Fang-Min Chen
Journal:  Cancer Med       Date:  2018-07-18       Impact factor: 4.452

Review 5.  Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association.

Authors:  Famke Aeffner; Mark D Zarella; Nathan Buchbinder; Marilyn M Bui; Matthew R Goodman; Douglas J Hartman; Giovanni M Lujan; Mariam A Molani; Anil V Parwani; Kate Lillard; Oliver C Turner; Venkata N P Vemuri; Ana G Yuil-Valdes; Douglas Bowman
Journal:  J Pathol Inform       Date:  2019-03-08

6.  Deep Learning to Estimate Human Epidermal Growth Factor Receptor 2 Status from Hematoxylin and Eosin-Stained Breast Tissue Images.

Authors:  Deepak Anand; Nikhil Cherian Kurian; Shubham Dhage; Neeraj Kumar; Swapnil Rane; Peter H Gann; Amit Sethi
Journal:  J Pathol Inform       Date:  2020-07-24

Review 7.  The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy.

Authors:  Olga Kuczkiewicz-Siemion; Kamil Sokół; Beata Puton; Aneta Borkowska; Anna Szumera-Ciećkiewicz
Journal:  Cancers (Basel)       Date:  2022-08-08       Impact factor: 6.575

  7 in total

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