Mammographic density estimation: Comparison among BI-RADS categories, a semi-automated software and a fully automated one

Although breast density is considered a strong predictor of breast cancer risk, its quantitative assessment is difficult. The aim of this study is to demonstrate that breast density assessment with a fully automated software is feasible and correlates with the semi-automated evaluation and the quantitative BI-RADS standards. A data set of 160 mammograms was evaluated by three blinded radiologists. Intra-observer (reader 1: k = 0.71; reader 2: k = 0.76; reader 3: k = 0.62) and inter-observer (reader 1 vs reader 2: k = 0.72; reader 2 vs reader 3: k = 0.80; reader 3 vs reader 1: k = 0.72) variability for the semi-automated software were good on a four-grade scale (D1/D2/D3/D4) and correlated with BI-RADS evaluation made by other two blinded radiologists (r = 0.65, p < 0.01). Inter-observer (reader 1 vs reader 2: k = 0.85; reader 2 vs reader 3: k = 0.91; reader 3 vs reader 1: k = 0.85) variability for the semi-automated software was very good on a two-grade scale (D1–D2/D3–D4). The use of the fully automated software eliminated intra- and inter-observer differences, correlated with BI-RADS categories (r = 0.62, p < 0.01) and can replace the semi-automated one (Bland–Altman statistics). Our study demonstrates that automated estimation of breast density is feasible and eliminates subjectivity. Furthermore both the semi-automated and the fully automated density estimation are more accurate than BI-RADS quantitative evaluation and could also be used in the daily clinical practice.