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.
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.
Authors: Leandro Luongo de Matos; Damila Cristina Trufelli; Maria Graciela Luongo de Matos; Maria Aparecida da Silva Pinhal Journal: Biomark Insights Date: 2010-02-09
Authors: Jin-Jia Hu; Andy Ambrus; Theresa W Fossum; Matthew W Miller; Jay D Humphrey; Emily Wilson Journal: J Histochem Cytochem Date: 2007-12-10 Impact factor: 2.479
Authors: Anna Babayan; Juliane Hannemann; Julia Spötter; Volkmar Müller; Klaus Pantel; Simon A Joosse Journal: PLoS One Date: 2013-09-18 Impact factor: 3.240