Can Breast Magnetic Resonance Imaging Prevent Biopsy or Change the Management of BI-RADS® Category 4 Breast Lesions?
Hale TurnaoğluEmine ÖztürkCüneyt YücesoyMehmet Akif TeberAynur TuranAysu Başak ÖzbalcıGaye ŞekerBinnur ÖnalBaki Hekįmoğlu
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BI-RADS
Breast MRI
Breast imaging
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The breast imaging reporting and data system (BI-RADS) lexicon provides a standardized terminology for describing leision characteristics but does not provide defined rules for converting specific imaging features into diagnostic categories. The inter-reader agreement of the BI-RADS is moderate. In this study, we explored the use of a simplified protocol and scoring system for BI-RADS categorization which integrates the morphologic features (MF), kinetic time-intensity curve (TIC), and apparent diffusion coefficient (ADC) values with equal weights, with a view to providing a convenient and practical method for breast magnetic resonance imaging (MRI) and improving the inter-reader agreement and diagnostic performance of BI-RADS.This cross-sectional, retrospective, single-center study included 879 patients with 898 histopathologically verified lesions who underwent an MRI scan on a 3.0 Tesla GE Discovery 750 MRI scanner between January 1, 2017, and June 30, 2020. The BI-RADS categorization of the studied lesions was assessed according to the sum of the assigned scores (the presence of malignant MF, lower ADC, and suspicious TIC each warranted a score of +1). Total scores of +2 and +3 were classified as category 5, scores of +1 were classified as category 4, and scores of +0 but with other lesions of interest were classified as category 3. The receiver operating characteristic (ROC) curves were plotted, and the sensitivity, specificity, and accuracy of this categorization were investigated to assess its efficacy and its consistency with pathology.There were 472 malignant, 104 risk, and 322 benign lesions. Our simplified scoring protocol had high diagnostic accuracy, with an area under curve (AUC) value of 0.896. In terms of the borderline effect of pathological risk and category 4 lesions, our results showed that when risk lesions were classified together with malignant ones, the AUC value improved (0.876 vs. 0.844 and 0.909 vs. 0.900). When category 4 and 5 lesions were classified as malignant, the specificity, accuracy, and AUC value decreased (82.3% vs. 93.2%, 89.3% vs. 90.2%, and 0.876 vs. 0.909, respectively). Therefore, to improve the diagnostic accuracy of the protocol for BI-RADS categorization, only category 5 lesions should be considered to be malignant.Our simplified scoring protocol that integrates MF, TIC, and ADC values with equal weights for BI-RADS categorization could improve both the diagnostic performance of the protocol for BI-RADS categorization in clinical practice and the understanding of the benign-risk-malignant breast diseases.
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To assess the adherence of academic radiologists in a university center to BI-RADS lexicon (BLA) and to evaluate the structural completeness of breast MRI reports.Breast MRI reports made during 2012 in a single academic center by six readers were scored for formal completeness (FS) including recording the MRI protocol, making relevant clinical correlation, and describing background enhancement; BLA including mass rather than lesion, describing lesion outline, enhancement characteristics, and dynamic curve; and also expressing the final conclusion using BLA, resulting in a maximal total score of 8. FS and BLA were correlated with reader characteristics including breast imaging background, years of academic experience, and number of breast MRIs reported yearly. Tests used for statistical analysis were the Mann-Whitney U test and analysis of variance (ANOVA).Overall BLA was 38.9%. This percentage was 60.1% and 3.7% in radiologists with and without breast imaging background, respectively (P = 0.000). Mean FS among all readers was 3.81 ± 1.75. This score was 2.54 ± 1.1 for readers without breast imaging background and 4.6 ± 1.6 for the readers regularly involved in breast imaging (P = 0.000).Higher degree of BLA and higher mean FS were associated with radiologists regularly involved in breast imaging. No association was found with years of academic experience or number of breast MRIs interpreted yearly.
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Breast MRI
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Breast imaging
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Background: The Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions is categorized into 4A, 4B, and 4C, which reflect an increasing malignancy potential from low (2–10%) moderate (10–50%) and high (50–95%). Determining the benign and malignant of BI-RADS category 4 breast lesions is very important for accurate diagnosis and follow-up treatment. This study aimed to explore the value of breast magnetic resonance imaging (MRI) omics features and clinical characteristics in the assessment of BI-RADS category 4 breast lesions. Methods: This retrospective study analyzed 96 lesions (39 benign and 57 malignant) from 92 patients diagnosed with MRI BI-RADS category 4 lesions in the Second Affiliated Hospital of Dalian Medical University between May 2017 and December 2019. The lesions were sub-categorized as BI-RADS 4A, 4B, or 4C based on the MRI findings. An imaging omics analysis model was applied to extract the MRI features. The positive predictive value (PPV) of each subcategory was calculated, and the area under the curve (AUC) was used to describe the efficiency for different diagnoses. Moreover, we analyzed 17 clinical indicators to assess their diagnostic value for BI-RADS category 4 breast lesions. Results: The PPVs of BI-RADS 4A, 4B, and 4C were 7.1% (2/28), 41.2% (7/17), and 94.1% (48/51), respectively. The AUC, sensitivity, and specificity were 0.919, 84.2%, and 92.3%, respectively. The combination of T1-weighted images (T1WI) with dynamic contrast-enhanced (DCE) MRI yielded the best diagnostic results among all dual sequences. Two clinical indicators [progesterone receptor (PR) and Ki-67 expression] achieved an AUC almost equal to 1.0. The radiomics and redundancy reduction methods reduced the clinical data features from 1,233 to 14. Conclusions: High diagnostic performance can be achieved in distinguishing malignant breast BI-RADS category 4 lesions using the combination of T1WI and DCE in MRI. Combining the PR and Ki-67 expression variables can further improve MRI accuracy for breast BI-RADS category 4 lesions.
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Abstract The purpose of this study was to develop, standardize, and test reproducibility of a lexicon for reporting contrast‐enhanced breast magnetic resonance imaging (MRI) examinations. To standardize breast MRI lesion description and reporting, seven radiologists with extensive breast MRI experience developed consensus on technical detail, clinical history, and terminology reporting to describe kinetic and architectural features of lesions detected on contrast‐enhanced breast MR images. This lexicon adapted American College of Radiology Breast Imaging and Data Reporting System terminology for breast MRI reporting, including recommendations for reporting clinical history, technical parameters for breast MRI, descriptions for general breast composition, morphologic and kinetic characteristics of mass lesions or regions of abnormal enhancement, and overall impression and management recommendations. To test morphology reproducibility, seven radiologists assessed morphology characteristics of 85 contrast‐enhanced breast MRI studies. Data from each independent reader were used to compute weighted and unweighted kappa (κ) statistics for interobserver agreement among readers. The MR lexicon differentiates two lesion types, mass and non‐mass‐like enhancement based on morphology and geographical distribution, with descriptors of shape, margin, and internal enhancement. Lexicon testing showed substantial agreement for breast density (κ = 0.63) and moderate agreement for lesion type (κ = 0.57), mass margins (κ = 0.55), and mass shape (κ = 0.42). Agreement was fair for internal enhancement characteristics. Unweighted kappa statistics showed highest agreement for the terms dense in the breast composition category, mass in lesion type, spiculated and smooth in mass margins, irregular in mass shape, and both dark septations and rim enhancement for internal enhancement characteristics within a mass. The newly developed breast MR lexicon demonstrated moderate interobserver agreement. While breast density and lesion type appear reproducible, other terms require further refinement and testing to lead to a uniform standard language and reporting system for breast MRI. J. Magn. Reson. Imaging 2001;13:889–895. © 2001 Wiley‐Liss, Inc.
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