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|Type:||Artigo de periódico|
|Title:||Complex Breast Masses: Assessment Of Malignant Potential Based On Cyst Diameter|
|Abstract:||Objectives - The purpose of this study was to assess whether cyst diameter might contribute to the prediction of malignancy in complex breast masses. Methods - In this cross-sectional study, we identified 48 breast masses that had sonographic features suggestive of benign breast lesions (oval shape, circumscribed margins, parallel axis, and abrupt limits). However, these masses were classified as Breast Imaging Reporting and Data System (BI-RADS) category 4 because of the presence of at least 1 cyst (complex echogenicity). All breast masses were biopsied (25 core needle and 23 core needle and excision). Subsequent histologic analysis was performed, and 12 malignancies (25%) were identified. Mammographic features were reviewed. Different sonographic measurements (largest diameters of the mass and cyst and vascular pattern) were assessed for the detection of malignancy. Results - Among the sonographic features, the vascular pattern, ie, the detection of blood flow (present in the lesion [P >.99] or present immediately adjacent to the lesion [P = .46]), was not associated with malignancy, whereas the largest mass and cyst dimensions had significantly positive correlations (P = .02; P < .001, respectively) with tumor malignancy. In receiver operating characteristic curve analysis, the point with the highest sum of sensitivity and specificity corresponded to a maximum cyst diameter of 8 mm (sensitivity, 67%; specificity, 86%). The positive and negative predictive values at that cutoff point were 61% and 86%, respectively. The area under the curve was 0.772. In this study, all masses with cysts smaller than 3 mm in diameter (7 cases) were benign, and all masses with cysts larger than 13 mm in diameter (4 cases) were malignant. Conclusions - Cyst diameter is a good predictor of malignancy in complex breast masses, which, except for the presence of internal cysts, would be otherwise classified as BI-RADS category 3. © 2012 by the American Institute of Ultrasound in Medicine.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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