Literature DB >> 19575836

Reproducibility of immunostaining quantification and description of a new digital image processing procedure for quantitative evaluation of immunohistochemistry in pathology.

Vagner Bernardo1, Simone Q C Lourenço, Renato Cruz, Luiz H Monteiro-Leal, Licínio E Silva, Danielle R Camisasca, Marcos Farina, Ulysses Lins.   

Abstract

Quantification of immunostaining is a widely used technique in pathology. Nonetheless, techniques that rely on human vision are prone to inter- and intraobserver variability, and they are tedious and time consuming. Digital image analysis (DIA), now available in a variety of platforms, improves quantification performance: however, the stability of these different DIA systems is largely unknown. Here, we describe a method to measure the reproducibility of DIA systems. In addition, we describe a new image-processing strategy for quantitative evaluation of immunostained tissue sections using DAB/hematoxylin-stained slides. This approach is based on image subtraction, using a blue low pass filter in the optical train, followed by digital contrast and brightness enhancement. Results showed that our DIA system yields stable counts, and that this method can be used to evaluate the performance of DIA systems. The new image-processing approach creates an image that aids both human visual observation and DIA systems in assessing immunostained slides, delivers a quantitative performance similar to that of bright field imaging, gives thresholds with smaller ranges, and allows the segmentation of strongly immunostained areas, all resulting in a higher probability of representing specific staining. We believe that our approach offers important advantages to immunostaining quantification in pathology.

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Year:  2009        PMID: 19575836     DOI: 10.1017/S1431927609090710

Source DB:  PubMed          Journal:  Microsc Microanal        ISSN: 1431-9276            Impact factor:   4.127


  11 in total

1.  Comparative analysis of colorimetric staining in skin using open-source software.

Authors:  Paul C Billings; Jenine K Sanzari; Ann R Kennedy; Keith A Cengel; John T Seykora
Journal:  Exp Dermatol       Date:  2015-02       Impact factor: 3.960

2.  Digital images are data: and should be treated as such.

Authors:  Douglas W Cromey
Journal:  Methods Mol Biol       Date:  2013

3.  Avoiding twisted pixels: ethical guidelines for the appropriate use and manipulation of scientific digital images.

Authors:  Douglas W Cromey
Journal:  Sci Eng Ethics       Date:  2010-06-22       Impact factor: 3.525

4.  Improving evaluation of the distribution and density of immunostained cells in breast cancer using computerized video image analysis.

Authors:  Brendon J Coventry; Michael J Weightman; John M Skinner; John Bradley
Journal:  Cancer Manag Res       Date:  2011-04-18       Impact factor: 3.989

Review 5.  Intercellular Communication in the Central Nervous System as Deduced by Chemical Neuroanatomy and Quantitative Analysis of Images: Impact on Neuropharmacology.

Authors:  Diego Guidolin; Cinzia Tortorella; Manuela Marcoli; Guido Maura; Luigi F Agnati
Journal:  Int J Mol Sci       Date:  2022-05-22       Impact factor: 6.208

6.  Immune profiling in human breast cancer using high-sensitivity detection and analysis techniques.

Authors:  Brendon J Coventry; Michael J Weightman; John Bradley; John M Skinner
Journal:  JRSM Open       Date:  2015-09-22

7.  Microvascular density of regenerative nodule to small hepatocellular carcinoma by automated analysis using CD105 and CD34 immunoexpression.

Authors:  Juliana Passos Paschoal; Vagner Bernardo; Nathalie Henriques Silva Canedo; Osmar Damasceno Ribeiro; Adriana Caroli-Bottino; Vera Lucia Pannain
Journal:  BMC Cancer       Date:  2014-02-07       Impact factor: 4.430

8.  Digital immunohistochemistry platform for the staining variation monitoring based on integration of image and statistical analyses with laboratory information system.

Authors:  Aida Laurinaviciene; Benoit Plancoulaine; Indra Baltrusaityte; Raimundas Meskauskas; Justinas Besusparis; Daiva Lesciute-Krilaviciene; Darius Raudeliunas; Yasir Iqbal; Paulette Herlin; Arvydas Laurinavicius
Journal:  Diagn Pathol       Date:  2014-12-19       Impact factor: 2.644

9.  Precise Identification of Cell and Tissue Features Important for Histopathologic Diagnosis by a Whole Slide Imaging System.

Authors:  Thomas W Bauer; Cynthia Behling; Dylan V Miller; Bernard S Chang; Elena Viktorova; Robert Magari; Perry E Jensen; Keith A Wharton; Jinsong Qiu
Journal:  J Pathol Inform       Date:  2020-02-06

10.  A Model based Survey of Colour Deconvolution in Diagnostic Brightfield Microscopy: Error Estimation and Spectral Consideration.

Authors:  Peter Haub; Tobias Meckel
Journal:  Sci Rep       Date:  2015-07-30       Impact factor: 4.379

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