Modified true-color computer-assisted image analysis versus subjective scoring of estrogen receptor expression in breast cancer: a comparison

Anticancer Res. May-Jun 1999;19(3B):2189-93.

Abstract

Background: Hormone receptor expression can be quantified by computerized image analysis in immunohistochemically stained specimens. When comparing semiquantitative scoring with computerized image analysis a review of the literature shows contradictory findings concerning the correlation of these two methods. Recent technical approaches have been developed with true-color computer-assisted image analysis facilitating new measurement designs. We performed a study with a new approach using the principle of semiquantitative assessment of hormone receptor content and measuring two different binary images (immunohistochemically stained nuclear area and total nuclear area).

Material and methods: Eighty formalin-fixed, paraffin-embedded and immunohistochemically stained breast cancer specimens were assessed for estrogen receptor expression by true color computer-assisted image analysis and by conventional light microscopy scoring according to Remmele (immunoreactive score (IRS) = staining intensity (SI) x percentage of positive cells (PP)). The results of both methods were correlated.

Results: Mean optical density (MOD) and subjective scoring of SI as well as stained nuclear area vs. total nuclear area and subjective scoring of stained cells (PP) showed a high correlation (Spearman correlation coefficient: 0.95, p-value: 0.0001 and 0.64, p-value: 0.0001, respectively).

Conclusion: On the basis of this new technical approach our results confirm the correlation of semiquantitative hormone receptor scoring and quantitative computer-assisted image analysis. We believe that by automating electronic analysis in the near future we will be able to establish reliable observer-independent evaluation of immunohistochemical variables ensuing comparability in multi-center trials and cost efficiency.

Publication types

  • Comparative Study

MeSH terms

  • Breast Neoplasms / pathology*
  • Cell Nucleus / pathology
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted*
  • Image Processing, Computer-Assisted*
  • Immunohistochemistry*
  • Observer Variation
  • Receptors, Estrogen / analysis*

Substances

  • Receptors, Estrogen