Association of breast cancer with MRI background parenchymal enhancement: the IMAGINE case-control study

Abstract

Background Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) may be associated with breast cancer risk, but previous studies of the association are equivocal and limited by incomplete blinding of BPE assessment. In this study, we evaluated the association between BPE and breast cancer based on fully blinded assessments of BPE in the unaffected breast. Methods The Imaging and Epidemiology (IMAGINE) study is a multicenter breast cancer case-control study of women receiving diagnostic, screening, or follow-up breast MRI, recruited from three comprehensive cancer centers in the USA. Cases had a first diagnosis of unilateral breast cancer and controls had no history of or current breast cancer. A single board-certified breast radiologist with 12 years’ experience, blinded to case-control status and clinical information, assessed the unaffected breast for BPE without view of the affected breast of cases (or the corresponding breast laterality of controls). The association between BPE and breast cancer was estimated by multivariable logistic regression separately for premenopausal and postmenopausal women. Results The analytic dataset included 835 cases and 963 controls. Adjusting for fibroglandular tissue (breast density), age, race/ethnicity, BMI, parity, family history of breast cancer, BRCA1/BRCA2 mutations, and other confounders, moderate/marked BPE (vs minimal/mild BPE) was associated with breast cancer among premenopausal women [odds ratio (OR) 1.49, 95% CI 1.05–2.11; p = 0.02]. Among postmenopausal women, mild/moderate/marked vs minimal BPE had a similar, but statistically non-significant, association with breast cancer (OR 1.45, 95% CI 0.92–2.27; p = 0.1). Conclusions BPE is associated with breast cancer in premenopausal women, and possibly postmenopausal women, after adjustment for breast density and confounders. Our results suggest that BPE should be evaluated alongside breast density for inclusion in models predicting breast cancer risk.

High–Temporal/High–Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement

“…BPE decreases cancer visibility by reducing the contrast-to-noise ratio between enhancing cancers and surrounding fibroglandular tissue, making high BPE a potential pitfall of breast MRI interpretation. 8,9,[22][23][24][25] Previous work has established that high BPE is associated with higher abnormal MRI interpretation rates, higher biopsy rates, and lower specificity, 8,9,23,26 and we have also found that high BPE is associated with lower CDR and lower PPV3. 37 These results are particularly troubling given that BPE is a breast cancer risk factor [27][28][29] ; there are more cancers to be found in patients with high BPE, and so CDRs in high-BPE patients should be higher, not lower, than those in low-BPE patients.…”

Overcoming Barriers in Ductal Carcinoma In Situ Management: From Overtreatment to Optimal Treatment

“…Mammographic density is associated with breast cancer risk, 13 and greater normal tissue background parenchymal enhancement levels on magnetic resonance imaging (MRI) may improve individual risk assessments over density alone. [14][15][16] Risk assessment tools on the basis of deep learning mammography 17 and MRI 18 models may outperform established models like Tyrer-Cuzick. MRI has greater sensitivity for high-versus low-grade DCIS, is nearly 100% sensitive for invasive carcinoma, and is not affected by density.…”

MRI background parenchymal enhancement, breast density and breast cancer risk factors: A cross-sectional study in pre- and post-menopausal women.

“…BPE and MRI-FGT are characteristics of breast tissue that are routinely assessed by radiologists from standard contrastenhanced MRI. Prior studies have shown these markers to be independently associated with breast cancer risk, contributing distinct information about a woman's risk 6,16 . To better understand these relationships and how they could be used to inform recommendations for screening and prevention, it is necessary to understand the factors that impact these imaging markers.…”