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Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p= 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 ‘training’ and ‘test’ web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference <0.6 and Maximum Absolute Deviation from reference <1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly >0.70 but aiming for observed intraclass correlation ≥0.90. Laboratory performance showed non-significant but promising trends of improvement through the calibration exercise (mean Root Mean Square Error decreased from 0.6 to 0.4, Maximum Absolute Deviation from 1.6 to 0.9; paired t-test: P=0.07 for Root Mean Square Error, 0.06 for Maximum Absolute Deviation). For tissue microarray scoring, the intraclass correlation estimate was 0.94 (95% credible interval: 0.90–0.97), markedly and significantly >0.70, the prespecified minimum target for success. Some discrepancies persisted, including around clinically relevant cutoffs. After calibrating to a common scoring method via a web-based tool, laboratories can achieve high inter-laboratory reproducibility in Ki67 scoring on centrally stained tissue microarray slides. Although these data are potentially encouraging, suggesting that it may be possible to standardize scoring of Ki67 among pathology laboratories, clinically important discrepancies persist. Before this biomarker could be recommended for clinical use, future research will need to extend this approach to biopsies and whole sections, account for staining variability, and link to outcomes.

Although an important biomarker in breast cancer, Ki67 lacks scoring standardization, which has limited its clinical use. Our previous study found variability when laboratories used their own scoring methods on centrally stained tissue microarray slides. In this current study, 16 laboratories from eight countries calibrated to a specific Ki67 scoring method and then scored 50 centrally MIB-1 stained tissue microarray cases. Simple instructions prescribed scoring pattern and staining thresholds for determination of the percentage of stained tumor cells. To calibrate, laboratories scored 18 ‘training’ and ‘test’ web-based images. Software tracked object selection and scoring. Success for the calibration was prespecified as Root Mean Square Error of scores compared with reference <0.6 and Maximum Absolute Deviation from reference <1.0 (log2-transformed data). Prespecified success criteria for tissue microarray scoring required intraclass correlation significantly >0.70 but aiming for observed intraclass correlation ≥0.90. Laboratory performance showed non-significant but promising trends of improvement through the calibration exercise (mean Root Mean Square Error decreased from 0.6 to 0.4, Maximum Absolute Deviation from 1.6 to 0.9; paired t-test: P=0.07 for Root Mean Square Error, 0.06 for Maximum Absolute Deviation). For tissue microarray scoring, the intraclass correlation estimate was 0.94 (95% credible interval: 0.90–0.97), markedly and significantly >0.70, the prespecified minimum target for success. Some discrepancies persisted, including around clinically relevant cutoffs. After calibrating to a common scoring method via a web-based tool, laboratories can achieve high inter-laboratory reproducibility in Ki67 scoring on centrally stained tissue microarray slides. Although these data are potentially encouraging, suggesting that it may be possible to standardize scoring of Ki67 among pathology laboratories, clinically important discrepancies persist. Before this biomarker could be recommended for clinical use, future research will need to extend this approach to biopsies and whole sections, account for staining variability, and link to outcomes.