Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions
Amer, N., Tantawy, E., Besar, A., Ibrahim, A. (2025). Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions. EKB Journal Management System, (), -. doi: 10.21608/zumj.2025.406397.4069
Norhan Magdy Salah Moustafa Amer; Engy Fathy Tantawy; Awad Abdel-Elaziz Besar; Ahmed Gamil Ibrahim. "Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions". EKB Journal Management System, , , 2025, -. doi: 10.21608/zumj.2025.406397.4069
Amer, N., Tantawy, E., Besar, A., Ibrahim, A. (2025). 'Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions', EKB Journal Management System, (), pp. -. doi: 10.21608/zumj.2025.406397.4069
Amer, N., Tantawy, E., Besar, A., Ibrahim, A. Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions. EKB Journal Management System, 2025; (): -. doi: 10.21608/zumj.2025.406397.4069

Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions

Zagazig University Medical Journal
Articles in Press, Accepted Manuscript, Available Online from 06 September 2025  XML
Document Type: Original Article
DOI: 10.21608/zumj.2025.406397.4069
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Authors
Norhan Magdy Salah Moustafa Amer email 1; Engy Fathy Tantawy2; Awad Abdel-Elaziz Besar2; Ahmed Gamil Ibrahim3
1MBBCH, Faculty of Medicine, Zagazig University
2Professor of Radio-diagnosis department, Faculty of Medicine, Zagazig University
3Assistant 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.
Keywords
Digital Tomosynthesis; BIRADS Categorization; Mammography; Breast Lesions
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