Related Experiment Video
Updated: Jun 29, 2026
Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
Published on: April 8, 2016
Modified true-color computer-assisted image analysis versus subjective scoring of estrogen receptor expression in
P D Kohlberger1, F Breitenecker, A Kaider
1Department of Obstetrics and Gynecology 1, Freiburg University Medical Center, Germany. pkohlb@frk1.ukl.uni-freiburg.de
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.
