ArticleJournal of breast cancer2024
Variability in Breast Density Estimation and Its Impact on Breast Cancer Risk Assessment.
Article in Journal of breast cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Mammographic density assessment by an artificial intelligence model for breast cancer detection in BreastScreen Norway.European radiology · 2026Article
- ABUS-based glandular tissue component classification for breast cancer risk prediction in Chinese women with dense breasts: a retrospective study.BMC medical imaging · 2026Article
- The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions.Journal of breast cancer · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Breast density is an independent risk factor for breast cancer, although variability exists in measurements. This study sought to evaluate the agreement between radiologists and automated breast density assessment software and assess the impact of breast density measures on breast cancer risk estimates using the Breast Cancer Surveillance Consortium (BCSC) model (v.2). A retrospective database search identified women who had undergone mammography between December 2021 and June 2022. The Breast Imaging Reporting and Data System (BI-RADS) breast composition index assigned by a radiologist (R) was recorded and analyzed using three commercially available software programs (S1, S2, and S3). The agreement rate and Cohen's kappa (κ) were used to evaluate inter-rater agreements concerning breast density measures. The 5-year risk of invasive breast cancer in women was calculated using the BCSC model (v.2) with breast density inputs from various density estimation methods. Absolute differences in risk between various density measurements were evaluated. Overall, 1,949 women (mean age, 53.2 years) were included. The inter-rater agreement between R, S1, and S2 was 75.0-75.6%, while that between S3 and the others was 60.2%-63.3%. Kappa was substantial between R, S1, and S2 (0.66-0.68), and moderate (0.49-0.50) between S3 and the others. S3 placed fewer women in mammographic density d (14.9%) than R, S1, and S2 (40.5%-44.0%). In BCSC risk assessment (v.2), S3 assessed fewer women with a high 5-year risk of invasive breast cancer than the other methods, resulting in an absolute difference of 0% between R, S1, and S2 in 75.0%-75.6% of cases, whereas the difference between S3 and the other methods occurs in 60.2%-63.3% of cases. Breast density assessment using various methods showed moderate-to-substantial agreement, potentially affecting risk assessments. Precise and consistent breast density measurements may lead to personalized and effective strategies for breast cancer prevention.
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Registered trials
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