Literature DB >> 16935726

Accuracy of assigned BI-RADS breast density category definitions.

Brandi T Nicholson1, Alexander P LoRusso, Mark Smolkin, Viktor E Bovbjerg, Gina R Petroni, Jennifer A Harvey.   

Abstract

RATIONALE AND
OBJECTIVES: Quantitative criteria for the Breast Imaging Reporting and Data System (BI-RADS) mammographic density categories have recently been defined as <25% dense for almost entirely fatty, 25%-50% dense for scattered fibroglandular densities, 51%-75% for heterogeneously dense, and >75% dense for the extremely dense category. The purpose of this study is to compare the range of percent mammographic densities with radiologist-assigned BI-RADS mammographic density categories and compare with the recently issued definitions.
MATERIALS AND METHODS: In this study, 200 consecutive negative analog screening mammograms were assigned BI-RADS mammographic density categories independently by three radiologists blinded to the other readers' density assignment. Quantitative assessment of percent mammographic density was performed using previously validated software.
RESULTS: All three readers agreed on BI-RADS mammographic density categories in 98 cases (49%), and two of three readers agreed in all 200 cases. Using two reader's consensus, median mammographic density (range) was 6.0% (0.5%-19.2%) for fatty, 14.8% (1.2%-52.7%) for scattered densities, 51.2% (15.9%-82.2%) for heterogeneously dense, and 78.4% (60.1%-87.9%) for extremely dense breasts. The percent mammographic density ranges for fatty and extremely dense breasts correlated well with BI-RADS definitions, whereas the ranges of densities in the scattered and heterogeneously dense categories were considerably broader.
CONCLUSION: Fatty and extremely dense BI-RADS categories compare relatively well to defined criteria, and therefore may be helpful in breast cancer risk models. Scattered fibroglandular densities and heterogeneously dense categories have broad percent mammographic density ranges and may not function well in breast cancer risk models.

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Year:  2006        PMID: 16935726     DOI: 10.1016/j.acra.2006.06.005

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


  35 in total

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5.  Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment.

Authors:  Despina Kontos; Lynda C Ikejimba; Predrag R Bakic; Andrea B Troxel; Emily F Conant; Andrew D A Maidment
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Authors:  Jennifer A Harvey; Charlotte C Gard; Diana L Miglioretti; Bonnie C Yankaskas; Karla Kerlikowske; Diana S M Buist; Berta A Geller; Tracy L Onega
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10.  An Investigation into the Consistency in Mammographic Density Identification by Radiologists: Effect of Radiologist Expertise and Mammographic Appearance.

Authors:  Yanpeng Li; Patrick C Brennan; Warwick Lee; Carolyn Nickson; Mariusz W Pietrzyk; Elaine A Ryan
Journal:  J Digit Imaging       Date:  2015-10       Impact factor: 4.056

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