Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma

Objectives Biomarker expression evaluation for estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) is an essential prognostic and predictive parameter for breast cancer and critical for guiding hormonal and neoadjuvant therapy. This study compared quantitative image analysis (QIA) with pathologists' scoring for ER, PgR, and HER2. Methods A retrospective analysis was undertaken of 1,367 invasive breast carcinomas, including all histopathology subtypes, for which ER, PgR, and HER2 were analyzed by manual scoring and QIA. The resulting scores were compared, and in a subset of HER2 cases (n = 373, 26%), scores were correlated with available fluorescence in situ hybridization (FISH) results. Results Concordance between QIA and manual scores for ER, PgR, and HER2 was 93%, 96%, and 90%, respectively. Discordant cases had low positive scores (1%-10%) for ER (n = 33), were due to nonrepresentative region selection (eg, ductal carcinoma in situ) or tumor heterogeneity for PgR (n = 43), and were of one-step difference (negative to equivocal, equivocal to positive, or vice versa) for HER2 (n = 90). Among HER2 cases where FISH results were available, only four (1.0%) showed discordant QIA and FISH results. Conclusions QIA is a computer-aided diagnostic support tool for pathologists. It significantly improves ER, PgR, and HER2 scoring standardization. QIA demonstrated excellent concordance with pathologists' scores. To avoid pitfalls, pathologist oversight of representative region selection is recommended.

Automated summary

This study compared the concordance between quantitative image analysis (QIA) and pathologists' scoring in evaluating the expression of estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) in breast cancer. The results showed that QIA had excellent concordance with pathologists' scores for ER, PgR, and HER2. Pathologist oversight of representative region selection is recommended to avoid errors.