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

Daniela Sacchetto, Lia Morra, S. Agliozzo, D. Bernardi, Tomas Björklund, Beniamino Brancato, Patrizia Bravetti, Luca A. Carbonaro, L. Correale, Carmen Fantò, Elisabetta Favettini, Laura Martincich, Luisella Milanesio, Sara Mombelloni, Francesco Monetti, D. Morrone, Marco Pellegrini, Barbara Pesce, Antonella Petrillo, G. SaguattiCarmen Stevanin, Rubina M. Trimboli, Paola Tuttobene, Marvi Valentini, Vincenzo Marra, A. Frigerio, Alberto Bert, Francesco Sardanelli

Research output: Contribution to journalArticle

Abstract

Objectives 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.
Methods 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.
Results 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).
Conclusions 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.
Original languageEnglish
JournalEuropean Radiology
Publication statusPublished - 2016

Fingerprint Dive into the research topics of 'Mammographic density: Comparison of visual assessment with fully automatic calculation on a multivendor dataset'. Together they form a unique fingerprint.

  • Cite this

    Sacchetto, D., Morra, L., Agliozzo, S., Bernardi, D., Björklund, T., Brancato, B., Bravetti, P., Carbonaro, L. A., Correale, L., Fantò, C., Favettini, E., Martincich, L., Milanesio, L., Mombelloni, S., Monetti, F., Morrone, D., Pellegrini, M., Pesce, B., Petrillo, A., ... Sardanelli, F. (2016). Mammographic density: Comparison of visual assessment with fully automatic calculation on a multivendor dataset. European Radiology.