Literature DB >> 18091390

Assessment of two automated imaging systems in evaluating estrogen receptor status in breast carcinoma.

Sumita Gokhale1, Daniel Rosen, Nour Sneige, Leslie K Diaz, Erika Resetkova, Aysegul Sahin, Jinsong Liu, Constance T Albarracin.   

Abstract

Immunohistochemical staining for estrogen receptor (ER) status is widely used in the management of breast cancer. These stains have traditionally been scored manually, which results in generally good agreement among observers when the cases are strongly positive. However, significant interobserver and intraobserver differences in scoring can occur in borderline or weakly staining cases. Recently, automated systems have been proposed to provide a more sensitive and objective method of ER quantification. The ChromaVision Automated Cellular Imaging System and the Applied Imaging Ariol SL-50 quantify the color intensity of the immunoreactive product. To assess the accuracy of these 2 automated systems and to compare them to one another and to manual scoring, we performed immunostaining for ER on 64 cases of breast cancer. The percentages of positive cells were scored manually by 4 pathologists and by the 2 imaging systems. A discrepancy in scoring was defined as that which resulted in the reclassification of a case from negative to positive or vice versa. Our results showed significant agreement between the 2 automated systems. When automated scores were compared with the manual scores, only 5 of the 64 cases (7%) were discrepant. In 4 of these, the percentage of cells staining for ER was low (0% to 20%). Overall, the 2 systems were comparable, and discrepant results were most frequently seen when analyzing tumors with low levels of ER positive cells.

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Year:  2007        PMID: 18091390     DOI: 10.1097/PAI.0b013e31802ee998

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


  25 in total

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2.  Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry.

Authors:  Christopher Fiore; Dyane Bailey; Niamh Conlon; Xiaoqiu Wu; Neil Martin; Michelangelo Fiorentino; Stephen Finn; Katja Fall; Swen-Olof Andersson; Ove Andren; Massimo Loda; Richard Flavin
Journal:  J Clin Pathol       Date:  2012-03-23       Impact factor: 3.411

3.  Comparison of evaluations of hormone receptors in breast carcinoma by image-analysis using three automated immunohistochemical stainings.

Authors:  Koji Arihiro; Miyo Oda; Katsunari Ogawa; Kenshi Tominaga; Yoshie Kaneko; Tomomi Shimizu; Shiho Ohnishi; Megumi Oda; Yuki Kurita; Yuko Taira; Masayoshi Fujii; Maiko Tanaka
Journal:  Exp Ther Med       Date:  2010-08-26       Impact factor: 2.447

4.  An improved image analysis method for cell counting lends credibility to the prognostic significance of T cells in colorectal cancer.

Authors:  Juha P Väyrynen; Juha O Vornanen; Sara Sajanti; Jan P Böhm; Anne Tuomisto; Markus J Mäkinen
Journal:  Virchows Arch       Date:  2012-04-24       Impact factor: 4.064

5.  Software-automated counting of Ki-67 proliferation index correlates with pathologic grade and disease progression of follicular lymphomas.

Authors:  Mark A Samols; Nathan E Smith; Jonathan M Gerber; Milena Vuica-Ross; Christopher D Gocke; Kathleen H Burns; Michael J Borowitz; Toby C Cornish; Amy S Duffield
Journal:  Am J Clin Pathol       Date:  2013-10       Impact factor: 2.493

6.  Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretation.

Authors:  Lynne Dobson; Catherine Conway; Alan Hanley; Alex Johnson; Sean Costello; Anthony O'Grady; Yvonne Connolly; Hilary Magee; Daniel O'Shea; Michael Jeffers; Elaine Kay
Journal:  Histopathology       Date:  2010-06-24       Impact factor: 5.087

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

Authors:  László Krecsák; Tamás Micsik; Gábor Kiszler; Tibor Krenács; Dániel Szabó; Viktor Jónás; Gergely Császár; László Czuni; Péter Gurzó; Levente Ficsor; Béla Molnár
Journal:  Diagn Pathol       Date:  2011-01-18       Impact factor: 2.644

8.  Patterns of FGF-23, DMP1, and MEPE expression in patients with chronic kidney disease.

Authors:  Renata C Pereira; Harald Juppner; Carlos E Azucena-Serrano; Ora Yadin; Isidro B Salusky; Katherine Wesseling-Perry
Journal:  Bone       Date:  2009-08-11       Impact factor: 4.398

9.  Apoptosis index correlates with chemotherapy efficacy and predicts the survival of patients with gastric cancer.

Authors:  Yongning Jia; Bin Dong; Lei Tang; Yiqiang Liu; Hong Du; Peng Yuan; Aiwen Wu; Jiafu Ji
Journal:  Tumour Biol       Date:  2012-03-01

10.  Assessment of automated image analysis of breast cancer tissue microarrays for epidemiologic studies.

Authors:  Kelly L Bolton; Montserrat Garcia-Closas; Ruth M Pfeiffer; Máire A Duggan; William J Howat; Stephen M Hewitt; Xiaohong R Yang; Robert Cornelison; Sarah L Anzick; Paul Meltzer; Sean Davis; Petra Lenz; Jonine D Figueroa; Paul D P Pharoah; Mark E Sherman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-03-23       Impact factor: 4.254

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