Literature DB >> 30195413

BI-RADS Category 5 Assessments at Diagnostic Breast Imaging:Outcomes Analysis Based on Lesion Descriptors.

Melissa Min-Szu Yao1, Bonnie N Joe2, Edward A Sickles2, Cindy S Lee3.   

Abstract

RATIONALE AND
OBJECTIVES: The Breast Imaging-Reporting and Data System (BI-RADS) atlas defines category 5 assessments as appropriate only for lesions that are almost certainly cancer, with a positive predictive value (PPV) of ≥95%. This study aims to demonstrate the feasibility of classifying lesions at diagnostic breast imaging with sufficiently high PPV to merit category 5 assessments, and to identify those lesion descriptors that yield such a high PPV.
MATERIALS AND METHODS: For this Health Insurance Portability and Accountability Act compliant and IRB exempt study, we reviewed diagnostic breast imaging examinations (mammography and/or ultrasound) assessed as highly suggestive of malignancy (BI-RADS category 5). Pathology diagnosis was considered the gold standard. PPV3 (biopsy performed) was calculated, and the BI-RADS descriptors for each lesion were analyzed.
RESULTS: Among 22,564 consecutive diagnostic breast imaging examinations between January 2010 and September 2015, we identified 239 exams (1.1%) assessed as BI-RADS category 5 (mean age 62.5 years). Malignancy (invasive breast carcinoma and/or ductal carcinoma in situ) was diagnosed in 233 examinations (PPV3 97.5% and 95% confidence interval: 96.2%-98.8%). The most common lesion types were mass (170) and calcifications (116). Of the 220 examinations involving both mammography and ultrasound, no category 5 lesions had <3 suspicious BI-RADS descriptors, only three lesions had three suspicious descriptors, but the remaining 217 lesions (98.6%) had ≥4 suspicious descriptors.
CONCLUSION: In clinical practice, it is feasible to make BI-RADS category 5 assessments with the intended ≥95% PPV. To justify a category 5 assessment, at least four suspicious BI-RADS descriptors should be identified at the combination of diagnostic mammography and ultrasound examinations.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BI-RADS; Category 5 assessment; Diagnostic mammography; Outcome; Ultrasound

Year:  2018        PMID: 30195413     DOI: 10.1016/j.acra.2018.07.018

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  2 in total

1.  A National Chinese Survey on Ultrasound Feature Interpretation and Risk Assessment of Breast Masses Under ACR BI-RADS.

Authors:  Wen Wen; Jingyan Liu; Junren Wang; Heng Jiang; Yulan Peng
Journal:  Cancer Manag Res       Date:  2021-12-11       Impact factor: 3.989

2.  Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.

Authors:  Wen Hao; Jing Gong; Shengping Wang; Hui Zhu; Bin Zhao; Weijun Peng
Journal:  Front Oncol       Date:  2020-10-29       Impact factor: 6.244

  2 in total

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