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Comparative Study
. 2017 May 18;7(1):2115.
doi: 10.1038/s41598-017-02341-8.

DCE-MRI Background Parenchymal Enhancement Quantified from an Early versus Delayed Post-contrast Sequence: Association with Breast Cancer Presence

Shandong Wu  1 , Margarita L Zuley  2   3 , Wendie A Berg  2   3 , Brenda F Kurland  4 , Rachel C Jankowitz  3   5 , Jules H Sumkin  2   3 , David Gur  2
Affiliations
Comparative Study

DCE-MRI Background Parenchymal Enhancement Quantified from an Early versus Delayed Post-contrast Sequence: Association with Breast Cancer Presence

Shandong Wu et al. Sci Rep. .

Abstract

We investigated automated quantitative measures of background parenchymal enhancement (BPE) derived from an early versus delayed post-contrast sequence in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for association with breast cancer presence in a case-control study. DCE-MRIs were retrospectively analyzed for 51 cancer cases and 51 controls with biopsy-proven benign lesions, matched by age and year-of-MRI. BPE was quantified using fully-automated validated computer algorithms, separately from three sequential DCE-MRI post-contrast-subtracted sequences (SUB1, SUB2, and SUB3). The association of BPE computed from the three SUBs and other known factors with breast cancer were assessed in terms of odds ratio (OR) and area under the receiver operating characteristic curve (AUC). The OR of breast cancer for the percentage BPE measure (BPE%) quantified from SUB1 was 3.5 (95% Confidence Interval: 1.3, 9.8; p = 0.015) for 20% increments. Slightly lower and statistically significant ORs were also obtained for BPE quantified from SUB2 and SUB3. There was no significant difference (p > 0.2) in AUC for BPE quantified from the three post-contrast sequences and their combination. Our study showed that quantitative measures of BPE are associated with breast cancer presence and the association was similar across three breast DCE-MRI post-contrast sequences.

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Conflict of interest statement

Wendie A. Berg is a consultant for data analysis and manuscript preparation for SuperSonic, Imagine. Dr. Berg is voluntary Chief Scientific Advisor to DenseBreast-info.org which receives unrestricted educational support from General Electric Healthcare and Volpara, Inc. Jules H. Sumkin is an unpaid member of Scientific Advisory Board for Hologic, Inc. and a Principle Investigator with institutional research agreements between University of Pittsburgh and Hologic, Inc. and General Electric Healthcare, Inc. For the remaining authors none were declared.

Figures

Figure 1
Figure 1
Automated segmentation of background parenchymal enhancement (BPE) and fibroglandular tissue (FGT) from breast DCE-MRI scans. (a) Whole-breast segmentation (red contour) from a pre-contrast image. (b) FGT (outlined by green contour) estimated from the segmented whole-breast. (c) The corresponding first post-contrast-subtracted (SUB1) image with superimposed breast contour (red). (d) BPE estimated from the SUB1 image (plot c). (e) The corresponding third post-contrast-subtracted (SUB3) image with superimposed breast contour (red). (f) BPE estimated from the SUB3 image (plot e).
Figure 2
Figure 2
AUCs of the combination of |BPE| and BPE% computed from different SUBs (SUB1, SUB2, and SUB3) in Comparison A (top) and Comparison B (bottom).
Figure 3
Figure 3
AUCs of distinguishing cancer cases from controls when using only four basic factors (i.e., age, menopausal status, family history, and ordinal mammographic density) and when the combination of |BPE| and BPE% computed from SUB2 were added to the four basic factors.
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