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Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value

PURPOSE: To investigate the positive predictive value of ultrasound classification of non-mass breast lesions (NMLs) following breast imaging reporting and data system (BI-RADS), and enhance understanding of NMLs. MATERIALS AND METHODS: Fifty-nine women with 59 ultrasound-detected breast NMLs were f...

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Autores principales: Lin, Mingnan, Wu, Size
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710769/
https://www.ncbi.nlm.nih.gov/pubmed/36449518
http://dx.doi.org/10.1371/journal.pone.0278299
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author Lin, Mingnan
Wu, Size
author_facet Lin, Mingnan
Wu, Size
author_sort Lin, Mingnan
collection PubMed
description PURPOSE: To investigate the positive predictive value of ultrasound classification of non-mass breast lesions (NMLs) following breast imaging reporting and data system (BI-RADS), and enhance understanding of NMLs. MATERIALS AND METHODS: Fifty-nine women with 59 ultrasound-detected breast NMLs were finally enrolled. The ultrasound (US) features of breast NMLs were analyzed; the incidence of malignant NMLs was calculated; the malignancy risk stratification of US for breast NMLs was established using BI-RADS. RESULTS: The incidence of malignant NMLs was 4.59% of all breast carcinoma. Non-ductal hypoechoic area, microcalcifications and posterior shadowing are the main US features of malignant NMLs, and there were significant differences between malignant and benign NMLs for microcalcifications and posterior shadowing. Taking BI-RADS 4B as a cutoff value, the sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive and negative predictive values, and odds ratio of the BI-RADS category were 82.98%,41.67%,0.62,84.78%,38.46% and 3.48, respectively. CONCLUSIONS: Stratifying the malignancy risk of breast NMLs using the BI-RADS the sensitivity and positive and predictive value are promising, but the likelihood of malignancy of malignant NMLs is underestimated, and that of benign NMLs is overestimated. The solution may be that to separate NMLs from breast masses and use different malignancy risk stratification protocols.
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spelling pubmed-97107692022-12-01 Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value Lin, Mingnan Wu, Size PLoS One Research Article PURPOSE: To investigate the positive predictive value of ultrasound classification of non-mass breast lesions (NMLs) following breast imaging reporting and data system (BI-RADS), and enhance understanding of NMLs. MATERIALS AND METHODS: Fifty-nine women with 59 ultrasound-detected breast NMLs were finally enrolled. The ultrasound (US) features of breast NMLs were analyzed; the incidence of malignant NMLs was calculated; the malignancy risk stratification of US for breast NMLs was established using BI-RADS. RESULTS: The incidence of malignant NMLs was 4.59% of all breast carcinoma. Non-ductal hypoechoic area, microcalcifications and posterior shadowing are the main US features of malignant NMLs, and there were significant differences between malignant and benign NMLs for microcalcifications and posterior shadowing. Taking BI-RADS 4B as a cutoff value, the sensitivity, specificity, area under the receiver operating characteristic curve (AUC), positive and negative predictive values, and odds ratio of the BI-RADS category were 82.98%,41.67%,0.62,84.78%,38.46% and 3.48, respectively. CONCLUSIONS: Stratifying the malignancy risk of breast NMLs using the BI-RADS the sensitivity and positive and predictive value are promising, but the likelihood of malignancy of malignant NMLs is underestimated, and that of benign NMLs is overestimated. The solution may be that to separate NMLs from breast masses and use different malignancy risk stratification protocols. Public Library of Science 2022-11-30 /pmc/articles/PMC9710769/ /pubmed/36449518 http://dx.doi.org/10.1371/journal.pone.0278299 Text en © 2022 Lin, Wu https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lin, Mingnan
Wu, Size
Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title_full Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title_fullStr Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title_full_unstemmed Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title_short Ultrasound classification of non-mass breast lesions following BI-RADS presents high positive predictive value
title_sort ultrasound classification of non-mass breast lesions following bi-rads presents high positive predictive value
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710769/
https://www.ncbi.nlm.nih.gov/pubmed/36449518
http://dx.doi.org/10.1371/journal.pone.0278299
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