Document Type : Original Article
Authors
1
MBBCH, Faculty of Medicine, Zagazig University
2
Professor of Radio-diagnosis department, Faculty of Medicine, Zagazig University
3
Assistant Professor of Radio-diagnosis department, Faculty of Medicine, Zagazig University
Abstract
Background: Breast cancer remains the most common cancer among women globally and is a leading cause of cancer-related deaths. The present work aimed to evaluate the additive role of digital breast tomosynthesis to mammography in changing the BIRADS classification of breast lesions.
Methods: A total of 30 women who were eligible to undergo full-field digital mammography, 3D DBT and ultrasound. Lesions were categorized independently by each modality using BI-RADS 2013 criteria. Histopathology or follow-up imaging was used as reference standards.
Results: DBT detected more lesions than DM. DM identified 42 lesions, with 29 (69%) as BI-RADS 3, 4 (9.5%) as BI-RADS 5, 3 (7.1%) as BI-RADS 0, 3 (7.1%) as BI-RADS 4A, 2 (4.8%) as BI-RADS 4C, and 1 (2.4%) as BI-RADS 2. DBT detected 54 lesions, including 23 (42.6%) as BI-RADS 3, 12 (22.2%) as BI-RADS 5, 8 (14.8%) as BI-RADS 2, 5 (9.3%) as BI-RADS 4A, 5 (9.3%) as BI-RADS 4C, and 1 (1.9%) as BI-RADS 4B. The diagnostic accuracy of BI-RADS with DBT for predicting breast cancer, with BI-RADS 5 indicating malignancy, showed a sensitivity of 90.9%, specificity of 91.1%, accuracy of 92.4%. In comparison, BI-RADS with DM had a sensitivity of 89%, specificity of 88.3%, accuracy of 81%. The combined use of DM DBT yielded excellent results, with a sensitivity of 91%, specificity of 100%,overall diagnostic accuracy of 93.5%.
Conclusion: DBT significantly enhances lesion detection characterization compared to DM, particularly in dense breasts. It improves diagnostic confidence, refines BI-RADS categorization, may reduce unnecessary biopsies.
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