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Clinical Implications of Background Parenchymal Enhancement on Breast MRI.

November 5, 2026pubmed logopapers

Authors

Zamora KW,Coffey K,Colvin S,Dashevsky B,Dodelzon K,Maimone S,Porembka JH,Zhou W,Chikarmane SA

Affiliations (7)

  • University of Alabama at Birmingham, Department of Radiology, Birmingham, AL, USA.
  • Weill Cornell Medicine, Department of Radiology, New York, NY, USA.
  • Stanford University, Department of Radiology, Palo Alto, CA, USA.
  • Mayo Clinic, Department of Radiology, Jacksonville, FL, USA.
  • University of Texas Southwestern Medical Center, Department of Radiology, Dallas, TX, USA.
  • University of Wisconsin, Department of Radiology, Madison, WI, USA.
  • Boston Medical Center, Department of Radiology, Boston, MA, USA.

Abstract

Breast MRI is an essential tool for breast cancer detection, evaluation, and characterization, offering greater sensitivity than mammography and ultrasound. Normal breast tissue demonstrates variable enhancement on MRI, known as background parenchymal enhancement (BPE), which reflects the physiologic enhancement of fibroglandular tissue after gadolinium administration. Initially considered an incidental finding, BPE is now recognized as a dynamic imaging feature influenced by several factors, including age, menopausal status, exogenous hormone use, and prior breast cancer treatments. Increasing evidence supports its clinical relevance since variations in BPE have been associated with differences in breast cancer risk, lesion detection, and imaging interpretation. Background parenchymal enhancement (BPE) is emerging as an important imaging biomarker with potential applications in risk stratification, evaluation of disease extent, and monitoring response to neoadjuvant therapy. Differences in BPE patterns may also correlate with tumor biology and molecular subtypes, further supporting its role in personalized breast imaging assessment. This article provides a comprehensive review of BPE, highlighting its biologic basis, imaging characteristics, and clinical implications in breast cancer care. It also examines the evolving role of artificial intelligence tools in the assessment and quantification of BPE, which may improve standardization and integration into clinical decision-making and research.

Topics

Journal Article

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