Abstract
Digital breast tomosynthesis (DBT) is one of the new techniques being developed to overcome the inherent limitations of mammography caused by superimposed structures in a 2D projection. To compare the diagnostic performances of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) for lesion characterization and size measurement using breast specimens. Out of 156 women scheduled for surgery, we included in our study 114 women, each of whom had a single, breast lesion. Three breast radiologists independently evaluated the DBT and FFDM performance regarding the breast specimens obtained during surgery. Each reader measured the lesion size, and then categorized the probability of malignancy using the American College of Radiology Breast Imaging Reporting and Data system (BI-RADS). After both reading sessions, the readers selected the preferred modality of either FFDM or DBT in lesion characterization. We also analyzed the radiologists' evaluation performance in patients with dense versus fatty breasts when using DBT and FFDM. The imaging findings of 84 cancers and 30 benign lesions, all of which had been pathologically proven, were reviewed. The size evaluation determined by DBT was more accurately correlated with that found by pathology (P = 0.001 for fatty breasts and <0.001 for dense breasts) than that determined by FFDM. The correlation coefficients of DBT and FFDM to the pathologically determined lesion size were 0.90 and 0.89, respectively (P < 0.001). Compared with the pathologically determined lesion size, the size determined by both imaging modalities was overestimated. Overall, assessment of the probability of malignancy by DBT and FFDM did not differ significantly (P = 0.07); however, in dense breast, DBT was more strongly correlated with the pathology determination than FFDM (P = 0.03). DBT may be superior to FFDM for determining the preoperative size measurement of breast lesions irregardless of their parenchymal density. Particularly in dense breasts, DBT was more useful for differentiating the lesion malignancy rate.
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