Does the degree of background enhancement in breast MRI affect the detection and staging of breast cancer?

Abstract

The degree of background enhancement affected the detection and staging of breast cancer using MRI.

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

“…Qualitative background parenchymal enhancement assessment Among the 39 (28111) studies that assessed BPE qualitatively, 7,8,[10][11][12][13]15,17, 38% (15/39) studies were published in 2015 (January-October 2015) and 62% (24/39) studies were published during 2010-2014. Most of the studies were performed in the USA (17/39 studies), the Korea (10/39 studies) and Japan (6/39 studies).…”

“…8,10,[12][13][14][15]21,23,26,28,[32][33][34][35][36]38,[40][41][42][43][48][49][50][51][52][53][54]57,59,61 In five studies, 11,17,19,29,44 the authors acknowledged that owing to the retrospective nature of the study, it was not possible to analyze the point of menstrual cycle, although, following institutional protocol, screening breast MRI of patients who were pre-menopausal was performed during the second week of the menstrual cycle. In a total of 14 studies, the authors stated the menstrual period.…”

“…7 The "degree" of BPE is linked to the risk of developing breast cancer, may affect the reading of breast MRI, the staging and the risk of cancer and even the long-term outcome, particularly in patients with certain subtypes at immunohistochemistry. [8][9][10][11][12][13][14][15] BPE can be visually assessed qualitatively using the Breast Imaging-Reporting and Data System (BI-RADS) scores or quantitatively using software. 7,16 However, radiologist agreement for BPE qualitative evaluation is fair 17 and, to the best of our knowledge, there is a lack of uniformity on quantitative measurements of BPE on breast MRI.…”

Computer-Aided Diagnosis of Breast DCE-MRI Images Using Bilateral Asymmetry of Contrast Enhancement Between Two Breasts

“…Although previous studies have shown that BPE computed from DCE-MRI examinations was a useful cancer risk prediction and/or a cancer diagnostic factor [22,23], this study is different. We investigated and tested a new feature index that is generated based on the bilateral asymmetry of BPE feature values computed from the left and right breasts of one woman.…”

“…The CAD schemes first extract and compute dynamic contrast enhancement features from the characteristic kinetic curves generated from a set of the selected pixels located inside the identified and segmented breast lesions, and then apply different machine learning classifiers to distinguish between the malignant and benign lesions [16][17][18][19][20]; for example, one study reported that using a leave-one-case-out testing method, a CAD scheme using a set of selected DCE-MRI features and a Bayesian artificial neural network yielded an area under a receiver operating characteristic (ROC) curve (AUC=0.78±0.04) when applying to a dataset involving 168 malignant and 45 benign breast lesions [21]. Although the previous studies focused on detection and analysis of characteristic kinetic curves computed from the pixels inside the segmented lesions, a recent study also showed that similar to a widely used image-based risk factor, namely, the mammographic density, the background parenchymal enhancement (BPE) evaluated or computed from the entire breast areas depicting on DCE-MRI images also carried useful or higher discriminatory information associated with cancer risk assessment [22] as well as the performance of cancer detection and staging [23].…”