Standardized terminology developed by the American College of Radiography (ACR) through the Breast-Imaging Reporting and Data System (BI-RADS) lexicon is used worldwide to describe the findings of the various breast-imaging techniques (mammography, ultrasound, and magnetic resonance imaging (MRI)). A 7-level positive predictive value (PPV) of malignancy classification system (from BI-RADS category 0 to category 6) has been based on this terminology, giving imaging a central role in the diagnostic strategy. This document presents the standardized, compulsory BI-RADS terminology used in breast-imaging reports in 2013 in view of the new edition that will be published at the end of the year.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.diii.2014.06.006 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Application of an artificial intelligence-assisted diagnostic system for breast ultrasound: a prospective study.
Gland Surg
December 2024
Department of Ultrasound, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Background: Accurate diagnosis of breast cancer is of great importance to improve the prognosis of patients. Artificial intelligence (AI)-assisted diagnostic system for breast ultrasound is gradually being applied in the identification of benign and malignant breast lesions. This study aimed to evaluate the diagnostic performance and optimal application of AIassisted ultrasonography for breast lesions in clinical setting.
View Article and Find Full Text PDFComparing the Diagnostic Performance of Ultrasound Elastography and Magnetic Resonance Imaging to Differentiate Benign and Malignant Breast Lesions: A Systematic Review and Meta-analysis.
Acad Radiol
January 2025
Faculdade de Medicina e Ciências Biomédicas (FMCB), Universidade do Algarve. Campus de Gambelas, Edifício 2, 8005-139 Faro, Portugal (A.F.G., D.J., C.T., D.J., A.M., H.L.); Algarve Biomedical Center Research Institute (ABC-RI), Universidade do Algarve. Campus de Gambelas, Edifício 2, 8005-139 Faro, Portugal (A.M., E.P., H.L.).
Objective: The purpose of this systematic review and meta-analysis was comparing diagnostic performance of ultrasound elastography (UE), strain UE and shear wave elastography (SWE), with magnetic resonance imaging (MRI) in differentiating benign and malignant breast lesions.
Methods: Literature search of MEDLINE, Web of Science, SCOPUS and Google Scholar was performed in June 2023. Included studies used Breast Imaging Reporting and Data System (BI-RADS) and histopathology as reference standard.
A Radiomic-Clinical Model of Contrast-Enhanced Mammography for Breast Cancer Biopsy Outcome Prediction.
Acad Radiol
January 2025
Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 (C.L., S.W.); Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 (D.A., M.Z., J.S., S.W.); Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.); Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.). Electronic address:
Rationale And Objectives: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B.
View Article and Find Full Text PDFTrajectories of breast density change over time and subsequent breast cancer risk: longitudinal study.
BMJ
December 2024
Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea.
Objective: To identify clusters of women with similar trajectories of breast density change over four longitudinal assessments and to examine the association between these trajectories and the subsequent risk of breast cancer.
Design: Retrospective cohort study.
Setting: Data from the national breast cancer screening programme, which is embedded in the National Health Insurance Service database in Korea.
Accelerated High-resolution T1- and T2-weighted Breast MRI with Deep Learning Super-resolution Reconstruction.
Acad Radiol
January 2025
Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany (N.M., C.L., A.S., A.I., T.D., L.B., D.K., C.C.P., A.L., J.A.L.).
Rationale And Objectives: To assess the performance of an industry-developed deep learning (DL) algorithm to reconstruct low-resolution Cartesian T1-weighted dynamic contrast-enhanced (T1w) and T2-weighted turbo-spin-echo (T2w) sequences and compare them to standard sequences.
Materials And Methods: Female patients with indications for breast MRI were included in this prospective study. The study protocol at 1.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!