Abstract P1-01-07: Quantitative assessment of early- and delayed DCE-MRI background parenchymal enhancement in breast cancer risk prediction
Authors: Shandong Wu, Wendie A Berg, Margarita L Zuley, Brenda F Kurland, Rachel C Jankowitz, Jules Sumkin, Robert M Nishikawa, David Gur
Journal: Cancer Research (2015)

Abstract Purpose Background parenchymal enhancement (BPE) estimated from breast dynamic contrast enhanced MRI (DCE-MRI) has been correlated with breast cancer risk. Multiple time-point post-contrast-subtracted sequences are acquired in typical clinical breast DCE-MRI protocols. We quantitatively assessed BPE using fully automated computer algorithms and investigated the relationship between BPE quantified from three time-point post-contrast sequences and breast cancer risk prediction. Materials and Methods A retrospective case-control study was performed using breast DCE-MRI scans from 102 patients (mean 47.2±7.3 YO) who underwent either open surgical biopsy or core biopsy from 2009-2011: 51 women had unilateral breast cancer and 51 were age- and date-of-MRI matched controls with a unilateral biopsy-proven benign. For each MRI scan, three post-contrast-subtracted sequences (i.e., SUB 1, SUB 2 and SUB 3) acquired over a total of 7 minutes were analyzed. BPE was quantified from each of the sequences using fully automated computer algorithms on the breasts contralateral to the cancers and the contralateral (negative) breasts of the controls. For each sequence, two quantitative BPE measures were generated: the absolute BPE volume (|BPE|) and its relative amount over the whole breast volume (BPE%). Volumetric absolute and relative amounts of fibroglandular tissue (|FGT| and FGT%) were also automatically quantified, from the pre-contrast sequence. BI-RADS breast density assessment was retrieved from the mammography report (&amp;lt; 6 months) prior to cancer diagnosis (for cases) or MRI (for controls). Multivariable conditional logistic regression was performed to assess BPE measures, quantified respectively from SUB 1, SUB 2, and SUB 3, as predictors of breast cancer risk. Results Breast cancer risk odds ratios (ORs) were reported by |BPE| and BPE% (Table 1), after adjustment for breast density, |FGT|, and FGT%. Breast density did not correlate with risk for breast cancer in this study cohort: OR for BI-RADS density alone was 0.75 (95% CI: 0.35, 1.59; p=0.5). OR was 1.14 (95% CI: 0. 72, 1.81; p=0.6) for |FGT| alone and 0.70 (95% CI: 0.19, 2.52; p=0.6) for FGT% alone. Table 1: Breast cancer risk odds ratios (ORs) with 95% confidence intervals [CIs] for BPE quantified from SUB 1, SUB 2, and SUB 3, respectively. BPE from SUB1BPE from SUB2BPE from SUB3|BPE|2.0 (95% CI: 1.1-3.7; p=0.02)2.0 (95% CI: 1.2-3.3; p=0.01)1.7 (95% CI: 1.1-2.7; p=0.02)BPE%3.6 (95% CI: 1.3-10.1; p=0.01)2.8 (95% CI: 1.3-6.2; p=0.01)2.4 (95% CI: 1.2-5.0; p=0.02) Conclusions Increased BPE quantified from DCE-MRI are predictive of breast cancer risk, independent of measures of breast density and FGT. BPE estimated from three time-point SUB sequences has a similar predictive effect of breast cancer risk, while an early sequence (e.g., SUB 1) appears to have a larger magnitude of effect than that of a delayed sequence (e.g., SUB 3). Clinical Relevance Quantified BPE in breast DCE-MRI has potential for use as a biomarker of breast cancer risk and may be included to improve breast cancer risk prediction. A single post-contrast sequence (i.e., SUB 1) may be adequate for use to estimate breast cancer risk using breast MRI in the context of breast cancer screening for high-risk women. Citation Format: Shandong Wu, Wendie A Berg, Margarita L Zuley, Brenda F Kurland, Rachel C Jankowitz, Jules Sumkin, Robert M Nishikawa, David Gur. Quantitative assessment of early- and delayed DCE-MRI background parenchymal enhancement in breast cancer risk prediction [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-07.