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Updated: Jan 6, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Racial differences in quantitative background parenchymal enhancement on breast magnetic resonance imaging
Mattia A Mahmoud1, Christine E Edmonds2,3, Bruno Barufaldi3
1Department of Biostatistics, Epidemiology, & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Importance:
Although Black women have higher absolute quantitative breast density, they are often assigned lower subjectively determined Breast Imaging and Reporting Data System (BI-RADS) density scores than White women. Background parenchymal enhancement (BPE) on breast magnetic resonance imaging is independently linked to breast cancer risk and may improve risk stratification for Black and White women.
Objective:
To evaluate differences in quantitative BPE between Black and White women and determine whether breast cancer risk factors mediate these differences.
Design, Setting, And Participants:
A cross-sectional study of 1202 women (200 Black, 1002 White; aged 40-74 years) with negative mammograms and no breast cancer history who underwent breast magnetic resonance imaging between 2016 and 2023 at an academic medical center.
Exposures:
Self-reported race (Black vs. White).
Main Outcomes And Measures:
The primary outcome was automated, quantitative BPE (median BPE and BPE ratio). Covariates included BI-RADS density, fibroglandular tissue volume, qualitative BPE, age, body mass index, and menopausal status.
Results:
Fewer Black women were classified as having extremely dense breasts (10% vs. 21%; p < .01), yet similar proportions had high qualitative BPE (35% vs. 29%; p = .29). Quantitative BPE was significantly higher in Black women (median difference, 1.51; standard deviation, 9; 95% CI, 0.13-2.90), independent of covariates. No risk factors mediated this difference.
Conclusions And Relevance:
Despite lower BI-RADS density in Black women, as suggested by prior literature, higher quantitative BPE was found, suggesting that BPE captures aspects of breast tissue composition not reflected by density. Future studies can incorporate BPE into risk models, which can improve performance and reduce disparities in risk prediction.
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