Abstract 65P
Background
HER2 is a major predictive biomarker routinely assessed for all invasive breast carcinoma (BC). We aimed to assess if an artificial intelligence (AI) solution improves pathologists’ concordance and accuracy of HER2 scoring in BC.
Methods
The cohort included 577 biopsies and excisions with different BC subtypes (IDC, ILC, ± DCIS) from 4 different European sites. HER2 slides were stained with anti-HER2 antibody (4B5, VENTANA) and scanned with different scanners (Leica GT450DX, Philips UFS). This two-arm multi-reader study compared the performance of 10 pathologists (“readers”) on HER2 scoring (each reviewed 50-200 slides) unassisted vs. supported by an AI HER2 solution (Galen Breast HER2®), which detects the invasive tumor area, classifies tumor cells based on their staining pattern and derives a slide-level HER2 score by applying 2018 ASCO/CAP guidelines. Both study arms were compared to ground truth established by three breast pathologists (“experts”).
Results
Experts’ overall inter-observer agreement was 77.5% and for 0/1+/2+/3+ scores it was 84.4%/76%/61.7%/93.3%, respectively. Readers’ agreement was significantly higher when assisted by AI (90.1% vs. 77.2% without AI). For the HER2 Low relevant cut-off (0 vs. 1+/2+/3+), readers with AI showed significantly higher sensitivity (98.4% vs. 93.7% without AI), and higher inter-reader agreement (96.9% vs. 89.9%)(p < 0.05). For the 0/1+ vs. 2+/3+ classic regulatory cut-off, a trend towards higher accuracy was observed, with significant improvement in specificity (98.1% vs. 92.1%) and in inter-observer agreement (94.3% vs. 88.2%) (p < 0.05). The AI solution demonstrated high accuracy for HER2 scoring (93.4%) for 0 vs. 1+/2+/3+ and overall (82.7%). A comparison of the AI accuracy on slide subset stained with 4B5 vs A0485 antibodies will be also presented.
Conclusions
This study reports an independent multi-site validation of a fully automated AI solution for HER2 scoring in BC. Pathologists supported by AI showed improvements in HER2 scoring consistency, and a trend for better accuracy overall and for the analyzed clinical cut-offs. These results suggest AI may improve reproducibility and standardization of HER2 scoring and will be validated in additional ongoing studies.
Legal entity responsible for the study
Ibex Medical Analytics.
Funding
Ibex Medical Analytics.
Disclosure
J. Cyrta: Financial Interests, Institutional, Funding: Ibex. S. Schnitt: Financial Interests, Personal, Advisory Board: Ibex Medical Analytics, PathAI, PreciseDX. G. Macgrogan: Financial Interests, Personal, Other, participation in validation study of AI application: IBEX; Financial Interests, Personal, Invited Speaker: AstraZeneca, Daiichi Sankyo, MSD, Gilead, Menarini, Roche; Financial Interests, Personal, Advisory Board: AstraZeneca, Daiichi Sankyo, MSD. R.F. Salgado: Financial Interests, Institutional, Funding: Ibex Medical Analytics. S. Declercq: Financial Interests, Institutional, Funding: Ibex Medical Analytics. G. Broeckx: Financial Interests, Personal, Advisory Board: Roche, Novartis, MSD, AstraZeneca; Financial Interests, Personal, Invited Speaker: MSD, Novartis; Financial Interests, Personal and Institutional, Research Grant: Gilead. F. Deman: Financial Interests, Personal, Invited Speaker: AstraZeneca; Financial Interests, Personal, Advisory Board: Roche; Financial Interests, Institutional, Funding: AstraZeneca, J&J; Financial Interests, Institutional, Other, Data sharing agreement: IBEX; Financial Interests, Institutional, Invited Speaker: Owkin, Roche. M. Brevet: Financial Interests, Personal, Invited Speaker, Conference on digital pathology and HER2 low in breast Cancer: AstraZeneca; Financial Interests, Personal, Expert Testimony, Consultancy about digital pathology: Tribun Health; Financial Interests, Personal, Invited Speaker, conference about digital pathology in a pathology lab: Tribun Health; Financial Interests, Institutional, Invited Speaker, Funding for a study about HER2 AI algorithm in breast cancer: AstraZeneca & Daiichi Sankyo; Other, Member of the administration council and member of the national congress organization comittee: French society for Pathology. Y. Globerson: Financial Interests, Personal, Full or part-time Employment: Ibex Medical Analytics; Financial Interests, Personal, Stocks/Shares: Ibex Medical Analytics. R. Ziv, M. Grinwald, D. Mevorach: Financial Interests, Personal, Full or part-time Employment: Ibex Medical Analytics; Financial Interests, Personal, Stocks/Shares: Ibex Medical Analytics. J. Sandbank: Financial Interests, Personal, Full or part-time Employment: Ibex Medical Analytics, Maccabi Healthcare Services; Financial Interests, Personal, Stocks/Shares: Ibex Medical Analytics. M. Vecsler: Financial Interests, Personal, Full or part-time Employment: Ibex Medical Analytics; Financial Interests, Personal, Stocks/Shares: Ibex Medical Analytics; Non-Financial Interests, Member: USCAP, ESP. A. Vincent-Salomon: Financial Interests, Personal, Advisory Board: Ibex Medical Analytics, Amgen; Financial Interests, Personal, Invited Speaker: AstraZeneca, Daiichi Sankyo, Roche, MSD, Owkin, Primaa, Exact Sciences. All other authors have declared no conflicts of interest.