Automated selection of DAB-labeled tissue for immunohistochemical quantification

Eric M. Brey, Zahid Lalani, Carol Johnston, Mark Wong, Larry V. McIntire, Pauline J. Duke, Charles W. Patrick

Research output: Contribution to journalArticlepeer-review

159 Scopus citations

Abstract

The increased use of immunohistochemistry (IHC) in both clinical and basic research settings has led to the development of techniques for acquiring quantitative information from immunostains. Staining correlates with absolute protein levels and has been investigated as a clinical tool for patient diagnosis and prognosis. For these reasons, automated imaging methods have been developed in an attempt to standardize IHC analysis. We propose a novel imaging technique in which brightfield images of diaminobenzidene (DAB)-labeled antigens are converted to normalized blue images, allowing automated identification of positively stained tissue. A statistical analysis compared our method with seven previously published imaging techniques by measuring each one's agreement with manual analysis by two observers. Eighteen DAB-stained images showing a range of protein levels were used. Accuracy was assessed by calculating the percentage of pixels misclassified using each technique compared with a manual standard. Bland-Altman analysis was then used to show the extent to which misclassification affected staining quantification. Many of the techniques were inconsistent in classifying DAB staining due to background interference, but our method was statistically the most accurate and consistent across all staining levels.

Original languageEnglish (US)
Pages (from-to)575-584
Number of pages10
JournalJournal of Histochemistry and Cytochemistry
Volume51
Issue number5
DOIs
StatePublished - May 1 2003

Keywords

  • Diaminobenzidene
  • Growth factors
  • Image analysis
  • Immunohistochemistry
  • Normalized blue

ASJC Scopus subject areas

  • Anatomy
  • Cell Biology

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