Breast Imaging Reporting and Data System
- PMID: 29083600
- Bookshelf ID: NBK459169
Breast Imaging Reporting and Data System
Excerpt
Breast imaging-reporting and data system (BI-RADS) is a classification system proposed by the American College of Radiology (ACR) in 1986 with the original report released in 1993. The 1980s saw an exponential increase in mammography with the implementation of yearly screening mammograms and overwhelming variation amongst radiology reports. BI-RADS was implemented to standardize risk assessment and quality control for mammography and provide uniformity in the reports for non-radiologist. The first version proposed included the suggested structure for a mammographic report, the lexicon for mammographic imaging findings, and final assessment category with recommendations for management. The ACR used scientific analysis and literature review to create a lexicon of descriptors that had shown to correlate with high predictive values associated with either benign or malignant disease. The second important aspect of the BI-RADS system was the category classification for the overall assessment of the imaging findings. The categorization provides an approximate risk of malignancy to a lesion from essentially zero to greater than 95%. The categorization and final assessment decreased ambiguity in recommendations. BI-RADS was built to be fluid and change with the adaptation of new techniques and research. Such changes that have occurred are the inclusion of lexicons for ultrasound in 2003 and MRI in 2006. The latest edition is BI-RADS 5 (2013) and included six classifications for lesions.
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References
-
- Malmartel A, Tron A, Caulliez S. Accuracy of clinical breast examination's abnormalities for breast cancer screening: cross-sectional study. Eur J Obstet Gynecol Reprod Biol. 2019 Jun;237:1-6. - PubMed
-
- Barazi H, Gunduru M. StatPearls [Internet] StatPearls Publishing; Treasure Island (FL): 2023. Jul 31, Mammography BI RADS Grading. - PubMed
-
- Ciritsis A, Rossi C, Eberhard M, Marcon M, Becker AS, Boss A. Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making. Eur Radiol. 2019 Oct;29(10):5458-5468. - PubMed
-
- Gooch JC, Yoon E, Chun J, Kaplowitz E, Jubas T, Guth A, Axelrod D, Shapiro R, Darvishian F, Schnabel F. The Relationship of Breast Density and Positive Lumpectomy Margins. Ann Surg Oncol. 2019 Jun;26(6):1729-1736. - PubMed
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