Concordance between automated/semi-automated measurement and manual assessment of mammographic breast density in individuals undergoing breast cancer screening: a systematic review

Introduction:
Breast density is a risk factor for breast cancer and reduces the sensitivity of mammography. Manualbreast imaging reporting and data system (BI-RADS) classification remains the clinical standard, but automated methodshave been developed to improve reproducibility and efficiency. This review evaluated the concordance between auto-mated/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 screeningpopulations. 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 ofbreast density in the 26 included studies. Meta-analysis of 13 Volpara studies showed a tendency to classify mammogramsas dense compared with manual assessment, but the difference was not statistically significant and statistical heterogen-eity was very high (pooled difference 0.03, 95% CI −0.03 to 0.10; I2 = 98%). Studies of Quantra and other softwareshowed 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 withmanual BI-RADS assessment and may enhance consistency in screening programmes. Heterogeneity across studiesand limited information on representativeness preclude firm conclusions. Large-scale, standardised, and inclusive evalua-tions are needed to establish clinical utility.