Volume 51, Issue 1 pp. 43-61
Review Article

Background parenchymal enhancement on breast MRI: A comprehensive review

Geraldine J. Liao MD

Geraldine J. Liao MD

Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA

Department of Radiology, Virginia Mason Medical Center, Seattle, Washington, USA

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Leah C. Henze Bancroft PhD

Leah C. Henze Bancroft PhD

Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA

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Roberta M. Strigel MD, MS

Roberta M. Strigel MD, MS

Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA

Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA

Carbone Cancer Center, University of Wisconsin, Madison, Wisconsin, USA

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Rhea D. Chitalia BSE

Rhea D. Chitalia BSE

Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

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Despina Kontos PhD

Despina Kontos PhD

Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

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Linda Moy MD

Linda Moy MD

Department of Radiology, New York University School of Medicine, New York, New York, USA

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Savannah C. Partridge PhD

Savannah C. Partridge PhD

Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA

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Habib Rahbar MD

Corresponding Author

Habib Rahbar MD

Department of Radiology, University of Washington School of Medicine, Seattle, Washington, USA

Address reprint requests to: H.R., Seattle Cancer Care Alliance, 1144 Eastlake Ave. East, Room LG-200, Seattle, WA 98109. E-mail: [email protected]Search for more papers by this author
First published: 19 April 2019
Citations: 94
[Correction added on April 30, 2019, after first online publication: The second author's name was updated to Leah C. Henze Bancroft.]
Contract grant sponsor: National Cancer Institute (National Institutes of Health); Contract grant numbers: R01 CA203883 (to Rahbar), R01 CA207290 (to Partridge), R01 CA160620 (to Moy), P41EB017183 (to Moy), P30 CA1520 (to Strigel).

Abstract

The degree of normal fibroglandular tissue that enhances on breast MRI, known as background parenchymal enhancement (BPE), was initially described as an incidental finding that could affect interpretation performance. While BPE is now established to be a physiologic phenomenon that is affected by both endogenous and exogenous hormone levels, evidence supporting the notion that BPE frequently masks breast cancers is limited. However, compelling data have emerged to suggest BPE is an independent marker of breast cancer risk and breast cancer treatment outcomes. Specifically, multiple studies have shown that elevated BPE levels, measured qualitatively or quantitatively, are associated with a greater risk of developing breast cancer. Evidence also suggests that BPE could be a predictor of neoadjuvant breast cancer treatment response and overall breast cancer treatment outcomes. These discoveries come at a time when breast cancer screening and treatment have moved toward an increased emphasis on targeted and individualized approaches, of which the identification of imaging features that can predict cancer diagnosis and treatment response is an increasingly recognized component. Historically, researchers have primarily studied quantitative tumor imaging features in pursuit of clinically useful biomarkers. However, the need to segment less well-defined areas of normal tissue for quantitative BPE measurements presents its own unique challenges. Furthermore, there is no consensus on the optimal timing on dynamic contrast-enhanced MRI for BPE quantitation. This article comprehensively reviews BPE with a particular focus on its potential to increase precision approaches to breast cancer risk assessment, diagnosis, and treatment. It also describes areas of needed future research, such as the applicability of BPE to women at average risk, the biological underpinnings of BPE, and the standardization of BPE characterization.

Level of Evidence: 3

Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2020;51:43–61.

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