Literature DB >> 30268720

Variability in Individual Radiologist BI-RADS 3 Usage at a Large Academic Center: What's the Cause and What Should We Do About It?

Emily B Ambinder1, Lisa A Mullen2, Eniola Falomo3, Kelly Myers4, Jessica Hung5, Bonmyong Lee6, Susan C Harvey7.   

Abstract

RATIONALE AND
OBJECTIVES: Although the breast imaging reporting and data system (BI-RADS) lists specific criteria for designating a lesion as BI-RADS category 3 (probably benign), there are no target benchmarks for BI-RADS 3 usage rates. This study investigates the variability of BI-RADS 3 rates among a group of academic breast imagers, with the goal of defining more precise utilization.
MATERIALS AND METHODS: We retrospectively reviewed all diagnostic mammograms performed between July 1, 2013 and August 8, 2017 at our academic institution. The percentage of diagnostic mammograms given a BI-RADS 3 assessment was compared between radiologists using the Chi-square test. We then evaluated for correlation between BI-RADS 3 rate and individual clinical metrics (eg, radiologist experience, cancer detection rate [CDR] and recall rate) using univariate linear regression.
RESULTS: The study included 13 breast imagers and 24,051 diagnostic breast examinations. There was significant variability in BI-RADS 3 rates between radiologists, ranging from 8.0% to 19.3% (p < 0.001). Increased BI-RADS 3 rates negatively correlated with BI-RADS 1 or 2 rate (p < 0.001) and positively correlated with recall rate (p = 0.03). There was no association between BI-RADS 3 rate and the radiologist's level of experience, BI-RADS 4 or 5 rate, or CDR.
CONCLUSION: We found significant variability in BI-RADS 3 usage, which seems to be used in place of BI-RADS 1 or 2 findings rather than to avoid biopsy recommendation. BI-RADS 3 rates also directly correlated with recall rate, suggesting a greater degree of uncertainty among specific radiologists. Importantly, increased usage of BI-RADS 3 did not correlate with provider experience or improved CDR.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BI-RADS 3; Breast imaging; breast cancer; short interval follow up

Mesh:

Year:  2018        PMID: 30268720     DOI: 10.1016/j.acra.2018.09.002

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


  2 in total

1.  Value of BI-RADS 3 Audits.

Authors:  Prithwijit Roychowdhury; Gopal R Vijayaraghavan; John Roubil; Imani M Williams; Efaza Siddiqui; Srinivasan Vedantham
Journal:  Biomed J Sci Tech Res       Date:  2022-02-14

2.  Impact of artificial intelligence in breast cancer screening with mammography.

Authors:  Lan-Anh Dang; Emmanuel Chazard; Edouard Poncelet; Teodora Serb; Aniela Rusu; Xavier Pauwels; Clémence Parsy; Thibault Poclet; Hugo Cauliez; Constance Engelaere; Guillaume Ramette; Charlotte Brienne; Sofiane Dujardin; Nicolas Laurent
Journal:  Breast Cancer       Date:  2022-06-28       Impact factor: 3.307

  2 in total

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