Radiologist and AI Concordance in Screening Mammography and Association with Future Breast Cancer Risk

Purpose To evaluate the association between radiologist and stand-alone AI concordance in screening mammography interpretations and future breast cancer risk and to assess how breast density influences this relationship. Materials and Methods This retrospective study included Korean women who underwent digital screening mammography between January 2009 and December 2018. Incidental breast cancers, defined as those diagnosed within 1 year of screening, were excluded using the National Cancer Registry data. A commercial AI system retrospectively analyzed mammograms, with a 10% malignancy probability threshold. Patients were categorized into four groups based on AI-radiologist concordance: Concordant-Negative, Radiologist-Positive/AI-Negative, Radiologist-Negative/AI-Positive, and Concordant-Positive. Breast density was categorized using Breast Imaging Reporting and Data System classification. Cox proportional hazards models estimated adjusted hazard ratios (HRs) and 95% CIs. Results Over a median 7.3-year follow-up, 1011 breast cancers occurred among 82 899 women (mean age, 43.4 years ± 8.6 [SD]). Breast cancer incidence was the highest in the Concordant-Positive group (5-year cumulative incidence, 37.4 per 1000 person-years) and the lowest in the Concordant-Negative group (5.9 per 1000 person-years). Compared with the Concordant-Negative group, adjusted HRs for incidental breast cancer were 2.30 (<i>P</i> < .001) for the Radiologist-Negative/AI-Positive, 1.15 (<i>P</i> = .17) for the Radiologist-Positive/AI-Negative, and 4.51 (<i>P</i> < .001) for the Concordant-Positive groups. Risk increase in the Concordant-Positive group was consistent across breast densities; in dense breasts, elevated risk occurred only with positive AI. Conclusion Positive screening mammography findings identified by both radiologists and stand-alone AI (Concordant-Positive group) were associated with he highest 5-year breast cancer incidence of 3.74%, exceeding the 3% threshold for considering chemoprevention or supplemental imaging. <b>Keywords:</b> Mammography, Breast Neoplasms, Artificial Intelligence, Screening, Concordance <i>Supplemental material is available for this article.</i> © RSNA, 2025.