Concordance between automated/semi-automated measurement and manual assessment of mammographic breast density in individuals undergoing breast cancer screening: A systematic review
A partir d'une revue systématique de la littérature (26 études), cette étude évalue la concordance entre des mesures automatisées ou semi-automatisées (Volpara, Quantra) de la densité mammaire et la classification BI-RADS en mammographie numérique bidimensionnelle
Introduction : Breast density is a risk factor for breast cancer and reduces the sensitivity of mammography. Manual breast imaging reporting and data system (BI-RADS) classification remains the clinical standard, but automated methods have been developed to improve reproducibility and efficiency. This review evaluated the concordance between automated/semi-automated measurements and manual assessments of mammographic breast density.
Methods : We systematically searched MEDLINE, Embase, Cochrane Database of Systematic Reviews, CENTRAL, Scopus, and Web of Science (2014 onwards) for studies comparing automated or semi-automated measurement with manual BI-RADS classification on 2D digital mammography. Eligible studies included
≥
60% of participants from routine screening populations. Data extraction and risk of bias assessment followed a registered protocol (PROSPERO: CRD42024550250).
Results : There is good concordance between automated/semi-automated measurement and manual assessment of breast density in the 26 included studies. Meta-analysis of 13 Volpara studies showed a tendency to classify mammograms as dense compared with manual assessment, but the difference was not statistically significant and statistical heterogeneity was very high (pooled difference 0.03, 95% CI
−
0.03 to 0.10; I2 = 98%). Studies of Quantra and other software showed broadly similar findings, but variability in software versions and BI-RADS editions limited comparability. Reporting of participant demographics was poor, thus generalisability is unclear.
Conclusions : Automated breast density software, such as Volpara and Quantra, shows promising concordance with manual BI-RADS assessment and may enhance consistency in screening programmes. Heterogeneity across studies and limited information on representativeness preclude firm conclusions. Large-scale, standardised, and inclusive evaluations are needed to establish clinical utility.
Funding : National Institute for Health and Care Research
Journal of Medical Screening , article en libre accès, 2026