Digital breast tomosynthesis compared to digital mammography in a series of Egyptian women with pathologically proven breast cancer

Background: Breast cancer has a high prevalence in Egyptian women representing a major health problem for the patients and the community. Mammography is the primary modality in breast imaging inspite of its well-known limitations. Currently, digital breast tomosynthesis is state-of-the-art modality in breast imaging which provides images reconstructed from multiple projections acquired at different angles. Objective: To compare digital breast tomosynthesis (DBT) to digital mammography (DM) in a series of Egyptian women with pathologically proven breast cancer. Materials and methods: Twenty five women who were imaged by DBT and DM, and were proved to have breast cancer, were enrolled in this study. The acquired images of DBT and DM were reviewed for the malignant features and for Breast Imaging-Reporting and Data System (BI-RADS) category assessment. The equivalence (i. e., better, equivalent or worse) of the malignant features in DBT compared to DM was also rated. Lesion detection by craniocaudal (CC) and mediolateral oblique (MLO) views was also compared. Results: The equivalence rate of DBT compared to DM was superior in 60% of lesions (95% confidence interval [CI]; 44.1-75.9%); 11 of 20 (55%) mass lesions, 3 of 4 (75%) focal density lesions, 2 of 5 (40%) architectural distortion lesions and 8 of 11 (72.7%) inmicrocalcification lesions. Moreover, lesion detection by DBT was statistically significant (p= 0.008) in 7 lesions; 4 mass lesions, 1 architectural distortion lesion and 2 microcalcification lesions. Regarding BI-RADS category assessment, category increased rating by DBT compared to DM showed high statistical significance (p= 0.001). In addition, the superior equivalence rating of lesion detection by CC view compared toMLO view was statistically significant (p= 0.040). Conclusion: Digital breast tomosynthesis provides more lesion detection and hence, it is better in assigning BI-RADS category by solving the difficulties of diagnosis caused by parenchyma overlap. (C) 2015 The Authors. The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V.