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.
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 language | English |
|---|---|
| Journal | European Radiology |
| Publication status | Published - 2016 |
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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.