Role of Digital Tomosynthesis in Changing the BIRADS Categorization of Mammographically Detected Breast Lesions | ||
| Zagazig University Medical Journal | ||
| Volume 31, Issue 10, October 2025, Pages 5090-5103 PDF (1.1 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/zumj.2025.406397.4069 | ||
| Authors | ||
| Norhan Magdy Salah Moustafa Amer* 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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