TY - JOUR
T1 - Mammographic density estimation
T2 - Comparison among BI-RADS categories, a semi-automated software and a fully automated one
AU - Tagliafico, Alberto
AU - Tagliafico, Giulio
AU - Tosto, Simona
AU - Chiesa, Fabio
AU - Martinoli, Carlo
AU - Derchi, Lorenzo E.
AU - Calabrese, Massimo
PY - 2009/2
Y1 - 2009/2
N2 - 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.
AB - 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.
KW - Automated evaluation
KW - Breast
KW - Breast density
KW - Inter-observer variability
KW - Mammography
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U2 - 10.1016/j.breast.2008.09.005
DO - 10.1016/j.breast.2008.09.005
M3 - Article
C2 - 19010678
AN - SCOPUS:59849128380
VL - 18
SP - 35
EP - 40
JO - Breast
JF - Breast
SN - 0960-9776
IS - 1
ER -