Breast imaging and reporting data system (BIRADS): Magnetic resonance imaging

Institut Curie, Lutetia Parisorum, Île-de-France, France
European Journal of Radiology (Impact Factor: 2.16). 03/2007; 61(2):212-5. DOI: 10.1016/j.ejrad.2006.08.036
Source: PubMed

ABSTRACT This article reviews the technical aspects and interpretation criteria in breast MR imaging based on the first edition of breast imaging and reporting data system (BIRADS) published by the American College of Radiology (ACR) in 2003. In a second article, practical cases will be proposed for training the readers. The major aims of using this lexicon are: first to use a logical and standardized description of MR lesions, secondly to obtain a structured MR report with a clear final impression (BIRADS assessment categories), and thirdly to help comparison between different clinical studies based on similar breast MRI terminology.

  • [Show abstract] [Hide abstract]
    ABSTRACT: The purpose of this study was to compare the diagnostic accuracy of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) as a single parameter to multiparametric (MP) MRI with 2 (DCE MRI and diffusion-weighted imaging [DWI]) and 3 (DCE MRI, DWI, and 3-dimensional proton magnetic resonance spectroscopic imaging [3D H-MRSI]) parameters in breast cancer diagnosis. This prospective study was approved by the institutional review board. Written informed consent was obtained in all patients. One hundred thirteen female patients (mean age, 52 years; range, 22-86 years) with an imaging abnormality (Breast Imaging Reporting and Data System 0, 4-5) were included in this study. Multiparametric MRI of the breast at 3 T with DCE MRI, DWI, and 3D H-MRSI was performed. The likelihood of malignancy was assessed for DCE MRI and MP MRI with 2 (DCE MRI and DWI) and 3 (DCE MRI, DWI, and 3D H-MRSI) parameters separately. Histopathology was used as the standard of reference. Appropriate statistical tests were used to assess sensitivity, specificity, and diagnostic accuracy for each assessment combination. There were 74 malignant and 39 benign breast lesions. Multiparametric MRI with 3 MRI parameters yielded significantly higher areas under the curve (0.936) in comparison with DCE MRI alone (0.814) (P < 0.001). Multiparametric MRI with just 2 parameters at 3 T did not yield higher areas under the curve (0.808) than did DCE MRI alone (0.814). Multiparametric MRI with 3 parameters resulted in elimination of false-negative lesions and significantly reduced the false-positives ones (P = 0.002). Multiparametric MRI with 3 parameters increases the diagnostic accuracy of breast cancer in comparison with DCE-MRI alone and MP MRI with 2 parameters.
    Investigative radiology 02/2014; DOI:10.1097/RLI.0000000000000029 · 4.85 Impact Factor
  • Imagerie de la Femme 06/2010; 20(2):81-88. DOI:10.1016/j.femme.2010.04.002
  • [Show abstract] [Hide abstract]
    ABSTRACT: Rapid volume density analysis (RVDA) for automated breast ultrasound (ABUS) has been proposed as a more efficient method for estimating breast density. In the current experiment, ABUS images were obtained for 67 breasts from 40 patients. For each case, three rectangular volumes of interest (VOIs) were extracted, including the VOIs located at the 6 and 12 o'clock positions relative to the nipple in the anterior to posterior pass and the lateral position relative to the nipple in the lateral pass. The centers of these VOIs were defined to align with the center of nipple, and the depths reached the retromammary fat boundary. The fuzzy c-means classifier was applied to differentiate the fibroglandular and fat tissues to estimate the density. The classification results of the three VOIs were averaged to obtain the breast density. The density correlations between the RVDA and the ABUS methods were 0.98 and 0.96 using Pearson's correlation and linear regression coefficients, respectively. The average computation times for RVDA and ABUS were 4.2 and 17.8 seconds, respectively, using an Intel® Core™2 2.66 GHz computer with 3.25 GB memory. In conclusion, the RVDA method offers a quantitative and efficient breast density estimation for ABUS.
    Ultrasonic Imaging 10/2013; 35(4):333-343. DOI:10.1177/0161734613505998 · 1.58 Impact Factor