Breast Imaging Reporting and Data System and Contrast Enhancement Mammography: Lesion Conspicuity Likelihood of Malignancy and Relationship With Breast Tumor Receptor Status
- PMID: 36898907
- DOI: 10.1016/j.acra.2023.02.008
Breast Imaging Reporting and Data System and Contrast Enhancement Mammography: Lesion Conspicuity Likelihood of Malignancy and Relationship With Breast Tumor Receptor Status
Abstract
Rationale and objectives: The new version of the Contrast Enhanced Mammography (CEM) Breast imaging Reporting and Data System (BIRADs) encourages investigations of a new enhancement descriptor: "Lesion Conspicuity" (LC). The study aims to assess the diagnostic performance and the relationship with the receptor profile of this new enhancement descriptor.
Materials and methods: Three hundred twenty-five patients with 381 breast lesions who underwent CEM before histological assessmentwere selected. Four radiologists, blinded to each other, categorized LC into the following levels: absent, low, moderate, and high. Considering moderate and high evaluations as predictive of malignancy, the diagnostic performance of CEM was calculated using histological results of the biopsy as the gold standard. The association between LC values and the receptor profile of the neoplasms was also evaluated.
Results: The median age at the CEM examination was 50 years (IQR: 45-59). Considering the value of LC of the most experienced radiologist with the interpretation of Low Energy images (LE), we obtained a sensitivity (SE) of 91.9% (95% CI: 88.6%-95.2%) and a specificity (SP) of 67.2% (95% CI: 58.9%-75.5%). An association between "high" lesion conspicuity with ER/PgR not expressed (p = 0.025), with Ki-67>20% (p = 0.033), and with Grading G3 (p = 0.020) was observed.
Conclusion: The new feature of enhancement, "Lesion Conspicuity", demonstrated satisfactory performance in predicting the malignancy of lesions and significant correlation with the receptor profile of malignant breast neoplasms.
Keywords: Breast neoplasms; Contrast Enhanced Mammography; Mammography; Multimodal imaging.
Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of Competing Interest This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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