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Mammographic density: Comparison of visual assessment with fully automatic calculation on a multivendor dataset

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To compare breast density (BD) assessment provided by an automated BD evaluator (ABDE) with that provided by a panel of experienced breast radiologists, on a multivendor dataset.


Twenty-one radiologists assessed 613 screening/diagnostic digital mammograms from nine centers and six different vendors, using the BI-RADS a, b, c, and d density classification. The same mammograms were also evaluated by an ABDE providing the ratio between fibroglandular and total breast area on a continuous scale and, automatically, the BI-RADS score. A panel majority report (PMR) was used as reference standard. Agreement (κ) and accuracy (proportion of cases correctly classified) were calculated for binary (BI-RADS a-b versus c-d) and 4-class classification.


While the agreement of individual radiologists with the PMR ranged from κ = 0.483 to κ = 0.885, the ABDE correctly classified 563/613 mammograms (92 %). A substantial agreement for binary classification was found for individual reader pairs (κ = 0.620, standard deviation [SD] = 0.140), individual versus PMR (κ = 0.736, SD = 0.117), and individual versus ABDE (κ = 0.674, SD = 0.095). Agreement between ABDE and PMR was almost perfect (κ = 0.831).


The ABDE showed an almost perfect agreement with a 21-radiologist panel in binary BD classification on a multivendor dataset, earning a chance as a reproducible alternative to visual evaluation.

Key Points

Individual BD assessment differs from PMR with κ as low as 0.483.

An ABDE correctly classified 92 % of mammograms with almost perfect agreement (κ = 0.831).

An ABDE can be a valid alternative to subjective BD assessment.

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Automated breast density evaluator


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The authors would like to thank all the centres and the professionals who provided mammography exams for this study: in alphabetical order, APSS (Trento), A.O.U. Città della Salute e della Scienza (Turin), IRCCS Policlinico San Donato (Milan), ISPO (Florence), Ospedale Maggiore della Carità (Novara), Ospedale Regionale (Bolzano), Ospedale S.Andrea (Vercelli), and San Giovanni Bosco ASLTO2Nord (Turin).

The authors would like to acknowledge Dr. Stefano Ciatto for the helpful discussions and suggestions he provided for this study and, in general, to the im3D research team: even after his passing, his teachings continue to drive breast imaging scientific research.

The scientific guarantor of this publication is Francesco Sardanelli (IRCCS Policlinico San Donato, Milan, Italy and Università degli Studi di Milano, Department of Biomedical Sciences for Health, Milan, Italy). Some authors of this manuscript (L. Morra, D. Sacchetto, S. Agliozzo, L. Correale, A. Bert and L.A. Carbonaro) declare relationships with the company im3D. The authors state that this work has not received any funding. Two of the authors (L. Correale and F. Sardanelli) have significant statistical expertise. Institutional review board approval and written informed consent were not required because the study retrospectively evaluated a dataset of fully anonymized images acquired within routine diagnostic procedures. Methodology: retrospective, multicenter study.

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Correspondence to Daniela Sacchetto.

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Sacchetto, D., Morra, L., Agliozzo, S. et al. Mammographic density: Comparison of visual assessment with fully automatic calculation on a multivendor dataset. Eur Radiol 26, 175–183 (2016).

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