Background parenchymal enhancement on breast MRI: impact on diagnostic performance

Impact of Background Parenchymal Enhancement (BPE) on diagnostic performance of Contrast-Enhanced Mammography (CEM) for breast cancer diagnosis

OBJECTIVES

This study investigates how background parenchymal enhancement (BPE) impacts diagnostic performance in interpretation of contrast-enhanced mammography (CEM) for breast cancer diagnosis.

MATERIALS & METHODS

Retrospective IRB-approved single-center observational study on CEM-patients between 07/2020-09/2022. Indications for CEM were inconclusive or suspicious breast lesions identified by screening or diagnostic mammography and/or ultrasound. CEM was evaluated using the BI-RADS lexicon CEM supplement. BPE was assessed by one supervised reader and dichotomized as minimal/mild and moderate/marked. Exclusion criteria included patients without a 24-month follow-up, histology or CEM images were not available for technical reasons. Image interpretation was conducted by board-certified radiologists. All readers were blinded to patient clinical data and histopathology results. Statistical analysis included Kappa statistics and ROC analysis. Diagnostic metrics were calculated at a BI-RADS > 3 cut-off. P-values < 0.05 indicated statistical significance.

RESULTS

229 female patients (mean age 53.8 ± 10.7 years) were included. BPE was minimal in 49.3 %, mild in 36.8 %, moderate in 12.5 %, and marked in 1.4 % of patients. Overall AUC was higher in minimal/mild BPE (0.94 ± 0.01) compared to moderate/marked BPE (0.82 ± 0.04), which proved statistically significant (difference 0.12, p = 0.004). Sensitivity was higher in the minimal/mild BPE group at 90.9 % compared to 66.7 % in the moderate/marked BPE group (p = 0.05). Specificity was significantly higher in the minimal/mild vs. moderate/marked BPE group, p = 0.0006).

CONCLUSION

BPE significantly affects the diagnostic performance of CEM, particularly sensitivity. This highlights the importance of assessing and reporting BPE in CEM to provide a simple metric indicating the reliability of test results.

Impact of Background Parenchymal Enhancement on Diagnostic Performance of Breast MRI: A Systematic Review and Meta-Analysis

Background Breast MRI is the most sensitive modality for detecting breast cancer, but its diagnostic performance can be reduced by background parenchymal enhancement (BPE). However, the implications of the degree of BPE in diagnostic evaluation remain controversial due to conflicting evidence. Purpose To conduct a systematic review and meta-analysis to determine whether the presence of moderate or marked BPE in women undergoing breast MRI negatively affects diagnostic performance compared with minimal or mild BPE. Materials and Methods On May 6, 2024, a systematic review of PubMed and Google Scholar was conducted on studies assessing the diagnostic performance of contrast-enhanced MRI in detecting breast cancer. Studies published until May 2024 were included if they provided raw data to extract or calculate true-positive, false-positive, true-negative, and false-negative results. Data were integrated using a bivariate random-effects model, and the sensitivity and specificity were compared between minimal or mild and moderate or marked BPE. Sources of heterogeneity were explored using meta-regression analysis. Summary receiver operating characteristic analysis was performed to compare overall diagnostic performance at different BPE levels by using a Z test. Results Eight studies of 6044 women (mean age, 52 years) were included. Minimal or mild BPE was associated with higher sensitivity (95.3% vs 84.1%; P = .02) and higher specificity (89.0% vs 78.7%; P = .02) compared with moderate or marked BPE. Diagnostic performance was higher for minimal or mild BPE (area under the receiver operating characteristic curve [AUC], 0.95; 95% CI: 0.92, 0.96) compared with moderate or marked BPE (AUC, 0.91; 95% CI: 0.88,0.93; Z score, 2.69; P = .007). Moderate or marked BPE and publication year in cases of moderate or marked BPE were covariates influencing the diagnostic odds ratio. Moderate or marked BPE remained an independent predictor of the diagnostic performance at multivariable analysis (diagnostic odds ratio, -1.33; P = .002). Conclusion The degree of BPE influences the diagnostic performance of breast MRI, with minimal or mild BPE being associated with higher sensitivity and specificity and moderate or marked BPE being associated with lower diagnostic performance. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Bahl in this issue.

Novel Wash-In Characteristics of Background Parenchymal Enhancement on Ultrafast Dynamic Contrast-Enhanced Breast MRI

Background - Ultrafast MRI (UFMRI) can minimize background parenchymal enhancement (BPE), improve cancer visualization, and inform characterization of malignancy. Although BPE is a biomarker for breast cancer risk, washin characteristics of BPE are unknown. Objective - The purpose of this study was to delineate wash-in behavior of normal BPE in healthy women on UFMRI and determine association with patient characteristics. Methods - This retrospective study evaluated consecutive normal screening breast MRI examinations (BI-RADS category 1) (January 2020 to May 2022) with 1 year of negative follow-up MRI. Characteristics including age, menopausal status, and cancer risk factors were recorded. Fibroglandular tissue and BPE on conventional postcontrast sequences were documented. UFMR images were analyzed for level, time to enhancement (TTE), and maximum slope (MS) of BPE as indicators of wash-in characteristics. Ordinal logistic regressions were conducted using a significance level of .05 (two-sided). Results - The final sample included 222 women (median age, 50 years; range, 25-81 years): 110 (49.5%) premenopausal and 112 (50.5%) postmenopausal. BPE was lower on UFMRI than on conventional MRI in 98.5% of examinations with moderate or marked BPE and 85.4% of examinations with mild to marked BPE on conventional postcontrast images (p < .001). BPE on UFMRI was marked in 0% and moderate in 4.1% of examinations. BPE was significantly associated with menopausal status, inversely related to age, and significantly associated with TTE. The odds of high BPE on UFMRI were 7.815 times greater in premenopausal women (95% CI, 4.461-13.689) (p < .001), 1.067 times less per 1-year increase in age (95% CI, 1.046-10.890) (p < .001), and 1.113 times greater per 1-second decrease in TTE (95% CI, 1.589-6.383) (p = .01). MS was higher in premenopausal women but was not statistically significant. BPE was not associated with cancer risk factors. Conclusion - UFMRI mitigates BPE, essentially eliminating marked and moderate BPE. TTE varies by age and menopausal status, suggesting hormonal underpinning. Clinical impact - Minimizing BPE on UFMRI could improve diagnostic accuracy. Wash-in kinetic parameters of BPE have potential to serve as biomarkers in breast cancer risk prediction.

Hormonal Regulation of Background Parenchymal Enhancement at Contrast-enhanced Mammography

Background Background parenchymal enhancement (BPE) is an important diagnostic and prognostic imaging biomarker. Although hormonal regulation of BPE at breast MRI has been investigated, information regarding hormonal regulation of BPE at contrast-enhanced mammography (CEM) remains scarce. Purpose To investigate how BPE at CEM changes across various short- and long-term physiologic and pharmacologic hormonal effects, including menopausal status, lactation, hormone replacement therapy (HRT), and tamoxifen therapy and its cessation. Materials and Methods This retrospective study included CEM examinations performed between December 2012 and January 2024. A computational search was performed to identify CEMs performed in patients with various hormonal statuses and several subgroups of patients were identified, including premenopausal, postmenopausal, lactating, HRT, and tamoxifen subgroups. For patients who received tamoxifen therapy, the first follow-up image at treatment cessation was included, when available. The four ordinal BPE grades, ranging from minimal to marked, as reported in the official radiologic reports were used for analysis. Subgroup comparisons were performed using the Kruskal-Wallis rank sum test and χ2 test or Fisher exact test. Results A total of 507 female patients (mean age, 49.8 years ± 10.8 [SD]; range, 25-75 years) were included. Premenopausal patients (n = 200) exhibited higher BPE compared with postmenopausal patients (n = 200) (median grade, 1.0 [IQR, 0-2.0] vs 0 [IQR, 0-1.0]; P < .001). Lactating patients (n = 16) exhibited higher BPE (median grade, 3.0; IQR, 2.0-3.0) compared with nonlactating controls (median grade, 1.0; IQR, 0-2.0; P < .001). Patients receiving HRT (n = 14) exhibited higher BPE (median grade, 1.5; IQR, 0-3.0) compared with postmenopausal controls (median grade, 0; IQR, 0-1.0; P < .001). Patients receiving tamoxifen therapy (n = 77) exhibited lower BPE (median grade, 1.0; IQR, 0-2.0) compared with nontreated control patients (9% of patients with high BPE vs 31% for controls, P < .001) and increased BPE (median grade, 2.0; IQR, 1.5-2.5; P = .003) at the cessation of tamoxifen therapy. Conclusion Hormonal effects, including menopausal status, lactation, HRT, and tamoxifen therapy, influenced the degree of BPE at CEM. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Slanetz in this issue.

Asymmetric background parenchymal enhancement on contrast-enhanced mammography: associated factors, diagnostic workup, and clinical outcome

OBJECTIVES

To summarize our institutional experience with contrast-enhanced mammography (CEM) exams reporting asymmetric background parenchymal enhancement (BPE).

MATERIALS AND METHODS

Consecutive CEMs performed between December 2012 and July 2023 were retrospectively reviewed to identify exams reporting asymmetric BPE. Associated factors, the level of reporting certainty, BI-RADS score, diagnostic workup, and clinical outcome were summarized. BPE grades and BI-RADS were compared between initial CEM vs. immediate MRI and 6-month follow-up CEM, when indicated, using the Sign test.

RESULTS

Overall, 175/12,856 (1.4%) CEMs (140 female patients, mean age, 46 ± 8.0 years) reported asymmetric BPE. Reporting certainty was mostly high (n = 86), then moderate (n = 59) and low (n = 30). Associated factors included contralateral irradiation (n = 94), recent ipsilateral breast treatment (n = 14), and unilateral breastfeeding (n = 4). BI-RADS scores were 0 (n = 21), 1/2 (n = 75), 3 (n = 67), 4 (n = 3), and 6 (n = 1), or given for a finding other than asymmetric BPE (n = 8). Initial diagnostic-workup often included targeted-US (n = 107). Immediate MRI (n = 65) and/or 6-month CEM follow-up (n = 69) downgraded most cases, with a significant decrease in BPE grade compared to the initial CEM (p < 0.01 for both). On follow-up, two underlying cancers were diagnosed in the area of questionable asymmetric BPE.

CONCLUSION

Apparent asymmetric BPE is most often a benign finding with an identifiable etiology. However, rarely, it may mask an underlying malignancy presenting as non-mass enhancement, thus requiring additional scrutiny.

CLINICAL RELEVANCE STATEMENT

The variability in the diagnostic-workup of apparent asymmetric background parenchymal enhancement stresses the clinical challenge of this radiological finding. Further studies are required to verify these initial observations and to establish standardized management guidelines.

KEY POINTS

Apparent asymmetric background parenchymal enhancement usually represents a benign clinical correlate, though rarely it may represent malignancy. Evaluation of asymmetric background parenchymal enhancement varied considerably in the metrics that were examined. Targeted US and MRI can be useful in evaluating unexplained asymmetric background parenchymal enhancement.

Background parenchymal enhancement in CEM and MRI: Is there always a high agreement?

INTRODUCTION

Background parenchymal enhancement (BPE) refers to the physiological enhancement of breast fibroglandular tissue. This study aimed to determine the agreement of BPE evaluation between contrast enhanced mammography (CEM) and magnetic resonance imaging (MRI) and investigate potential confounders.

MATERIALS AND METHODS

This retrospective, IRB-approved study included women recalled from screening or with inconclusive findings on mammography and/or ultrasound, who underwent both CEM and MRI between 2018 and 2022. Imaging protocols followed international recommendations. Two breast radiology fellows assessed density and BPE on CEM and MRI using BI-RADS, evaluating the early post-contrast acquisition (EP). In addition, BPE on MRI was assessed in the late post-contrast acquisition (LP). Data on menopausal status, breast thickness, and compression force were retrieved. Univariate and multivariate analyses were used.

RESULTS

343 patients were consecutively enrolled. Post-menopausal patients showed lower BPE levels (p < 0.001). Agreement on BPE levels between CEM and MRI in the EP was fair (R1 κ = 0.342, R2 κ = 0.383). In the LP agreement was moderate for R1 (κ = 0.432) and fair for R2 (κ 0.368). There was a significant correlation between BPE and density in CEM (R1 ρ 0.399, R2 ρ 0.441; p < 0.001). A negative correlation was found on CEM between BPE and compression force (ρ -0.100, p = 0.001). Inter-reader agreement was high with both modalities (CEM κ = 0.678, MRI-EP κ = 0.690, MRI-EP κ = 0.692).

CONCLUSIONS

The agreement of BPE assessment between MRI and CEM was fair to moderate and reproducibility among readers was high. Compression force and mammographic breast density seem to influence BPE levels in CEM.

Breast Suspicious Microcalcifications on Contrast-Enhanced Mammograms: Practice and Reflection

Purpose

To evaluate the use of contrast enhanced mammography (CEM) in suspicious microcalcifications and to discuss strategies to cope with its diagnostic limitations.

Methods

We retrospectively evaluated patients with suspicious calcifications who underwent CEM at our institution. We collected and analyzed morphological findings, enhancement patterns and pathological findings of suspicious microcalcifications on CEM. A small proportion of these cases underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The enhancement patterns of CEM in this study were classified into three categories: enhancement, no enhancement, and indeterminate. CEM imaging was independently analyzed by two breast imaging specialists.

Results

A total of 44 patients with 46 lesions were collected from January 2022 to July 2024. Overall, 20 cases (43.5%) microcalcifications showed enhancement on CEM; 23 (50.0%) showed no enhancement; and 3 (6.5%) were indeterminate. Of the 20 enhancement cases, mass enhancement was seen in 9 (45%), and non-mass enhancement (NME) in 11 (55%). DCE-MRI was performed in 13 cases. One case of invasive ductal carcinoma (IDC) showed enhancement on MRI but was indeterminate on CEM due to the masking effect of background parenchymal enhancement (BPE), and one case of ductal carcinoma in situ (DCIS) lacked enhancement on CEM but had significant enhancement on MRI.

Conclusion

CEM provides additional information on the enhancement associated with breast suspicious microcalcifications. It is not perfect for diagnosis and strategies are needed to cope with its limitations.

Influence of Breast Density and Menopausal Status on Background Parenchymal Enhancement in Contrast-Enhanced Mammography: Insights from a Retrospective Analysis

Background: Contrast-enhanced mammography (CEM) has recently gained recognition as an effective alternative to breast magnetic resonance imaging (MRI) for assessing breast lesions, offering both morphological and functional imaging capabilities. However, the phenomenon of background parenchymal enhancement (BPE) remains a critical consideration, as it can affect the interpretation of images by obscuring or mimicking lesions. While the impact of BPE has been well-documented in MRI, limited data are available regarding the factors influencing BPE in CEM and its relationship with breast cancer (BC) characteristics. Materials: This retrospective study included 116 patients with confirmed invasive BC who underwent CEM prior to biopsy and surgery. Data collected included patient age, breast density, receptor status, tumor grading, and the Ki-67 proliferation index. BPE was evaluated by two radiologists using the 2022 ACR BI-RADS lexicon for CEM. Statistical analyses were conducted to assess the relationship between BPE, patient demographics, and tumor characteristics. Results: The study found a significant association between higher levels of BPE and specific patient characteristics. In particular, increased BPE was more commonly observed in patients with higher breast density (p < 0.001) and those who were pre-menopausal (p = 0.029). Among patients categorized under density level B, the majority exhibited minimal BPE, while those in categories C and D showed progressively higher levels of BPE, indicating a clear trend correlating higher breast density with increased enhancement. Additionally, pre-menopausal patients demonstrated a higher likelihood of moderate to marked BPE compared to post-menopausal patients. Despite these significant associations, the analysis did not reveal a meaningful correlation between BPE intensity and tumor subtypes (p = 0.77) or tumor grade (p = 0.73). The inter-reader agreement for BPE assessment was substantial, as indicated by a weighted kappa of 0.78 (95% CI: 0.68-0.89), demonstrating consistent evaluation between radiologists. Conclusions: These findings suggest that BPE in CEM is influenced by factors like breast density and age, aligning with patterns observed in MRI studies. However, BPE intensity was not associated with tumor subtypes or grades, indicating a poorer prognosis. These insights highlight the potential of BPE as a risk biomarker in preventive follow-up, particularly for patients with high breast density and pre-menopausal status. Further multicentric and prospective studies are needed to validate these results and deepen the understanding of BPE's role in CEM diagnostics.

Are background breast parenchymal features on preoperative breast MRI associated with disease-free survival in patients with invasive breast cancer?

OBJECTIVE

To evaluate whether breast parenchymal features of the contralateral breast on preoperative MRI are associated with primary breast cancer characteristics and disease-free survival (DFS) in women with invasive breast cancer.

MATERIALS AND METHODS

Women with newly diagnosed invasive breast cancer who underwent preoperative breast MRI followed by surgery were retrospectively evaluated. Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI and background diffusion signal (BDS) on diffusion-weighted MRI of the contralateral breast were qualitatively assessed using a four-category scale: minimal, mild, moderate, or marked. Primary breast cancer characteristics were compared based on the degree of BPE or BDS. Cox proportional hazards models were used to evaluate the association between MRI parenchymal features and DFS after adjusting for clinicopathologic features.

RESULTS

A total of 515 women (mean age, 54 years) were included. Of whom, 46 (8.9%) patients who developed disease recurrence at a median follow-up of 60 months were observed. A high level (moderate/marked) of BPE or BDS was associated with younger age (≤ 45) and premenopausal status (all P < 0.05) compared to a low level (minimal/mild), but it was not associated with primary cancer characteristics such as tumor stage, grade, or subtype. Multivariable Cox proportional hazards analysis demonstrated that larger tumor size (> 2 cm) (hazard ratio [HR], 3.877; P < . 001), triple-negative subtype (HR, 2.440; P = .013), and axillary node metastasis (HR, 1.823; P = .049) were associated with worse DFS. No associations were observed between background parenchymal features and disease outcomes.

CONCLUSIONS

MRI parenchymal features, including BPE and BDS, of the contralateral breast showed no associations with primary breast cancer characteristics or DFS in women with invasive breast cancer.

Contrast-Enhanced Mammography in Local Staging of Screen-Detected Breast Cancer

BACKGROUND

BreastScreen Australia, the population mammographic screening program for breast cancer, uses two-view digital screening mammography ± ultrasound followed by percutaneous biopsy to detect breast cancer. Secondary breast imaging for further local staging, not performed at BreastScreen, may identify additional clinically significant breast lesions. Staging options include further mammography, bilateral ultrasound, and/or contrast-based imaging (CBI) [magnetic resonance imaging (MRI) or contrast-enhanced mammography (CEM)]. CBI for local staging of screen-detected cancer was introduced at an academic hospital breast service in Melbourne, VIC, Australia. We report findings for otherwise occult disease and resulting treatment changes.

MATERIAL AND METHODS

Patients staged using CEM between November 2018 and April 2022 were identified from hospital records. Data were extracted from radiology, pathology, and breast unit databases. CEM-detected abnormalities were documented as true positive (TP) for invasive cancer or ductal carcinoma in situ (DCIS), or otherwise false positive (FP). The impact on surgical decisions was assessed.

RESULTS

Of 202 patients aged 44-84 years, 60 (30%) had 74 additional findings [34 (46%) TP, 40 (54%) FP]. These were malignant in 29/202 (14%) patients (79% invasive cancers, 21% DCIS). CEM resulted in surgical changes in 43/202 (21%) patients: wider resection (24/43), conversion to mastectomy (6/43), contralateral breast surgery (6/43), additional ipsilateral excision (5/43), and bracketing (2/43). Additional findings were more common for patients with larger index lesions and for invasive cancer, but there was no significant variation by age, breast density, or index lesion grade.

CONCLUSIONS

CEM for local staging of screen-detected breast cancers identified occult malignancy in 14% of patients. CEM improves local staging and may facilitate appropriate management of screen-detected breast cancers.

Recommendations of the German Radiological Society's breast imaging working group regarding breast MRI

· Breast MRI is an essential part of breast imaging. · The recommendations for performing breast MRI have been updated. · A table provides a compact and quick overview. More detailed comments supplement the table.. · The "classic" breast MRI can be performed based on the recommendations. Tips for special clinical questions, such as implant rupture, mammary duct pathology or local lymph node status, are included.. CITATION FORMAT: · Wenkel E, Wunderlich P, Fallenberg E et al. Aktualisierung der Empfehlungen der AG Mammadiagnostik der Deutschen Röntgengesellschaft zur Durchführung der Mamma-MRT. Fortschr Röntgenstr 2024; 196: 939 - 944.

Contrast-enhanced Mammography versus MR Imaging of the Breast

Breast MR imaging and contrast-enhanced mammography (CEM) are both techniques that employ intravenously injected contrast agent to assess breast lesions. This approach is associated with a very high sensitivity for malignant lesions that typically exhibit rapid enhancement due to the leakiness of neovasculature. CEM may be readily available at the breast imaging department and can be performed on the spot. Breast MR imaging provides stronger enhancement than the x-ray-based techniques and offers higher sensitivity. From a patient perspective, both modalities have their benefits and downsides; thus, patient preference could also play a role in the selection of the imaging technique.

Background Parenchymal Enhancement: A Comprehensive Update

Breast MR imaging is a complementary screening tool for patients at high risk for breast cancer and has been used in the diagnostic setting. Normal enhancement of breast tissue on MR imaging is called breast parenchymal enhancement (BPE), which occurs after administration of an intravenous contrast agent. BPE varies widely due to menopausal status, use of exogenous hormones, and breast cancer treatment. Degree of BPE has also been shown to influence breast cancer risk and may predict treatment outcomes. The authors provide a comprehensive update on BPE with review of the recent literature.

MRI of the Lactating Breast

The breasts undergo marked physiologic changes during lactation that can make conventional imaging evaluation with mammography and US challenging. MRI can be a valuable diagnostic aid to differentiate physiologic and benign processes from malignancy in patients who are lactating. In addition, MRI may allow more accurate delineation of disease involvement than does conventional imaging and assists in locoregional staging, screening of the contralateral breast, assessment of response to neoadjuvant chemotherapy, and surgical planning. Although the American College of Radiology recommends against patients undergoing contrast-enhanced MRI during pregnancy because of fetal safety concerns, contrast-enhanced MRI is safe during lactation. As more women delay childbearing, the incidence of pregnancy-associated breast cancer (PABC) and breast cancer in lactating women beyond the 1st year after pregnancy is increasing. Thus, MRI is increasingly being performed in lactating women for diagnostic evaluation and screening of patients at high risk. PABC is associated with a worse prognosis than that of non-PABCs, with delays in diagnosis contributing to an increased likelihood of advanced-stage disease at diagnosis. Familiarity with the MRI features of the lactating breast and the appearance of various pathologic conditions is essential to avoid diagnostic pitfalls and prevent delays in cancer diagnosis and treatment. The authors review clinical indications for breast MRI during lactation, describe characteristic features of the lactating breast at MRI, and compare MRI features of a spectrum of benign and malignant breast abnormalities. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Chikarmane in this issue.

Added value of clinical decision rules for the management of enhancing breast MRI lesions: A systematic comparison of the Kaiser score and the Göttingen score

PURPOSE

We investigated the added value of two internationally used clinical decision rules in the management of enhancing lesions on breast MRI.

METHODS

This retrospective, institutional review board approved study included consecutive patients from two different populations. Patients received breast MRI according to the recommendations of the European Society of Breast Imaging (EUSOBI). Initially, all examinations were assessed by expert readers without using clinical decision rules. All lesions rated as category 4 or 5 according to the Breast Imaging Reporting and Data System were histologically confirmed. These lesions were re-evaluated by an expert reader blinded to the histology. He assigned each lesion a Göttingen score (GS) and a Kaiser score (KS) on different occasions. To provide an estimate on inter-reader agreement, a second fellowship-trained reader assessed a subset of these lesions. Subgroup analyses based on lesion type (mass vs. non-mass), size (>1 cm vs. ≤ 1 cm), menopausal status, and significant background parenchymal enhancement were conducted. The areas under the ROC curves (AUCs) for the GS and KS were compared, and the potential to avoid unnecessary biopsies was determined according to previously established cutoffs (KS > 4, GS > 3) RESULTS: 527 lesions in 506 patients were included (mean age: 51.8 years, inter-quartile-range: 43.0-61.0 years). 131/527 lesions were malignant (24.9 %; 95 %-confidence-interval: 21.3-28.8). In all subgroups, the AUCs of the KS (median = 0.91) were higher than those of the GS (median = 0.83). Except for "premenopausal patients" (p = 0.057), these differences were statistically significant (p ≤ 0.01). Kappa agreement was higher for the KS (0.922) than for the GS (0.358).

CONCLUSION

Both the KS and the GS provided added value for the management of enhancing lesions on breast MRI. The KS was superior to the GS in terms of avoiding unnecessary biopsies and showed superior inter-reader agreement; therefore, it may be regarded as the clinical decision rule of choice.

Breast Fibroglandular Tissue Segmentation for Automated BPE Quantification With Iterative Cycle-Consistent Semi-Supervised Learning

Background Parenchymal Enhancement (BPE) quantification in Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) plays a pivotal role in clinical breast cancer diagnosis and prognosis. However, the emerging deep learning-based breast fibroglandular tissue segmentation, a crucial step in automated BPE quantification, often suffers from limited training samples with accurate annotations. To address this challenge, we propose a novel iterative cycle-consistent semi-supervised framework to leverage segmentation performance by using a large amount of paired pre-/post-contrast images without annotations. Specifically, we design the reconstruction network, cascaded with the segmentation network, to learn a mapping from the pre-contrast images and segmentation predictions to the post-contrast images. Thus, we can implicitly use the reconstruction task to explore the inter-relationship between these two-phase images, which in return guides the segmentation task. Moreover, the reconstructed post-contrast images across multiple auto-context modeling-based iterations can be viewed as new augmentations, facilitating cycle-consistent constraints across each segmentation output. Extensive experiments on two datasets with various data distributions show great segmentation and BPE quantification accuracy compared with other state-of-the-art semi-supervised methods. Importantly, our method achieves 11.80 times of quantification accuracy improvement along with 10 times faster, compared with clinical physicians, demonstrating its potential for automated BPE quantification. The code is available at https://github.com/ZhangJD-ong/Iterative-Cycle-consistent-Semi-supervised-Learning-for-fibroglandular-tissue-segmentation.

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

PURPOSE

To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE).

MATERIALS AND METHODS

We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate).

RESULTS

Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3).

CONCLUSION

Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.

Correlation of background parenchymal enhancement on breast MRI with breast cancer

AIM

To evaluate the prognostic value of background parenchymal enhancement (BPE) in breast magnetic resonance imaging (MRI) in women referred to radiological department as a high risk for breast cancer.

MATERIALS AND METHODS

A retrospective, cross-sectional study included 327 consecutive patients (mean age: 60 years, age range: 30-90 years) who underwent breast MRI and tissue biopsy between 2007 and 2016. All MRI images (T1, T2, and subtraction images) were evaluated visually. The relationship of BPE with patient age, fibroglandular tissue (FGT), Breast Imaging Reporting and Data System (BIRADS) categories, presence of breast cancer, and expression of human epidermal growth factor receptor 2 (HER2), progesterone receptor (PR), oestrogen receptor (ER), and Ki67 were analysed. Furthermore, all variables were correlated with pre- and postmenopausal status.

RESULTS

BPE of bilateral breast showed a weak correlation with FGT (right BPE: r=-0.14, p=0.004; left BPE: r=0.16, p=0.003), a weak negative correlation with patient age (right BPE: r=-0.14, p=0.007; left BPE: r=-0.15, p=0.006), and significant correlation with HER2 (right BPE, p=0.02), left BPE with HER2 was not significant. Among the correlations between BPE and BIRADS, only between right BPE and right BIRADS was significant (p=0.031). No clear evidence of an association between breast MRI BPE and breast cancer in premenopausal and postmenopausal status was observed, and no difference was found between the right and left breasts.

CONCLUSIONS

The results of the present study showed no significant correlations between BPE and breast cancer. In addition, there was no significant difference between the right and left breast. Hence, BPE of MRI may not be a reliable biomarker of breast cancer development.

The Role of Diffusion-Weighted Imaging Based on Maximum-Intensity Projection in Young Patients with Marked Background Parenchymal Enhancement on Contrast-Enhanced Breast MRI

Diffusion-weighted imaging (DWI) utilizing maximum-intensity projection (MIP) was suggested as a cost-effective alternative tool without the risk of gadolinium-based contrast agents. The purpose of this study was to investigate whether DWI MIPs played a supportive role in young (≤60) patients with marked background parenchymal enhancement (BPE) on contrast-enhanced MRI (CE-MRI). The research included 1303 patients with varying degrees of BPE, and correlations between BPE on CE-MRI, the background diffusion signal (BDS) on DWI, and clinical parameters were analyzed. Lesion detection scores were compared between CE-MRI and DWI, with DWI showing higher scores. Among the 186 lesions in 181 patients with marked BPE on CE-MRI, the main lesion on MIPs of CE-MRI was partially or completely seen in 88.7% of cases, while it was not seen in 11.3% of cases. On the other hand, the main lesion on MIPs of DWI was seen in 91.4% of cases, with only 8.6% of cases showing no visibility. DWI achieved higher scores for lesion detection compared to CE-MRI. The presence of a marked BDS was significantly associated with a lower likelihood of a higher DWI score (p < 0.001), and non-mass lesions were associated with a decreased likelihood of a higher DWI score compared with mass lesions (p = 0.196). In conclusion, the inclusion of MIPs of DWI in the preoperative evaluation of breast cancer patients, particularly young women with marked BPE, proved highly beneficial in improving the overall diagnostic process.

Association of Clinical Factors and Degree of Early Background Parenchymal Enhancement on Contrast-Enhanced Mammography

BACKGROUND. Background parenchymal enhancement (BPE) may impact contrast-enhanced mammography (CEM) interpretation, although factors influencing the degree of BPE on CEM are poorly understood. OBJECTIVE. The purpose of our study was to evaluate relationships between clinical factors and the degree of early BPE on CEM. METHODS. This retrospective study included 207 patients (median age, 46 years) who underwent CEM between April 2020 and September 2021. Two radiologists independently assessed the degree of BPE on CEM as minimal, mild, moderate, or marked on the basis of two criteria (criterion 1, using the first of four obtained views; criterion 2, using the first two of four obtained views). The radiologists reached consensus for breast density on CEM. The EMR was reviewed for clinical factors. Radiologists' agreement for degree of BPE was assessed using weighted kappa coefficients. Univariable and multivariable analyses were performed to assess relationships between clinical factors and degree of BPE, treating readers' independent assessments as repeated measurements. RESULTS. Interreader agreement for degree of BPE, expressed as kappa, was 0.80 for both criteria. For both criteria, univariable analyses found degree of BPE to be negatively associated with age (both OR = 0.94), personal history of breast cancer (OR = 0.22-0.30), history of chemotherapy (OR = 0.18-0.21), history of radiation therapy (OR = 0.20-0.21), perimenopausal status (OR = 0.22-0.34), and postmenopausal status (OR = 0.10-0.11) and to be positively associated with dense breasts (OR = 4.13-4.26) and premenopausal status with irregular menstrual cycles (OR = 7.94-14.02). Among premenopausal patients with regular menstrual cycles, degree of BPE was lowest (using postmenopausal patients as reference) for patients in menstrual cycle days 8-14 (OR = 2.56-3.30). In multivariable analysis for both criteria, the only independent predictors of degree of BPE related to menstrual status and time of menstrual cycle (e.g., using premenopausal patients in days 1-7 as reference: OR = 0.21 for both criteria for premenopausal patients in days 8-14 and OR = 0.03-0.04 for postmenopausal patients). CONCLUSION. Clinical factors, including history of breast cancer or breast cancer treatment, breast density, menstrual status, and time of menstrual cycle, are associated with degree of early BPE on CEM. In premenopausal patients, the degree of BPE is lowest on days 8-14 of the menstrual cycle. CLINICAL IMPACT. Given the potential impact of BPE on diagnostic performance, the findings have implications for CEM scheduling and interpretation.

Characterization of True and False Positive Findings on Contrast-Enhanced Mammography

RATIONALE AND OBJECTIVES

The purpose of this paper is to characterize true and false positive findings on contrast-enhanced mammography (CEM) and correlate enhancement pattern and method of detection with pathology outcomes.

MATERIALS AND METHODS

This was an IRB-approved retrospective review of diagnostic CEM performed from December 2015 through December 2019 for which biopsy was recommended. Background parenchymal enhancement, tissue density, finding features, pathologic/clinical outcomes, and method of detection were captured. CEM includes low-energy images (LE), similar to standard 2D mammography, and recombined images (RI) that show enhancement. 'MG-detected' findings were identified on mammography or LE. 'RI-detected' findings were identified due to enhancement on RI. The positive predictive value (PPV2) was calculated on a per-case and a per-finding level. Comparisons were performed using Pearson chi-square and Fisher exact tests.

RESULTS

One hundred sixty CEM cases with 220 findings were evaluated with a case PPV2 of 58.1%. 32.3% (71/220) of lesions were RI-detected.  The PPV2 of RI-detected enhancement was 40.8% with subanalysis revealing PPV2 of 22.2%, 32%, and 51.4% for foci, NME, and masses, respectively. The PPV2 of MG-detected enhancement was 73.5% with subanalysis revealing PPV2 of 50%, 54.1%, and 83.8% for foci, NME, and masses, respectively. There were 100 false positives findings, 42 of which were RI-detected.

CONCLUSION

PPV2 of diagnostic CEM is within the range of other diagnostic breast imaging exams. However false positives remain a challenge, especially for RI-detected findings. Additional efforts to improve specificity of RI-detected findings are worthwhile.

Enhancement Type at Contrast-enhanced Mammography and Association with Malignancy

Background Despite the increasing use of contrast-enhanced mammography (CEM), there are limited data on the evaluation of findings on recombined images and the association with malignancy. Purpose To determine the rates of malignancy of enhancement findings on CEM images in the presence or absence of low-energy findings using the Breast Imaging Reporting and Data System (BI-RADS) lexicon developed for mammography and MRI. Materials and Methods All diagnostic CEM examinations performed at one academic institution between December 2015 and December 2019 had low-energy and recombined images retrospectively. Data were independently reviewed by three breast imaging radiologists with 5-25 years of experience using the BI-RADS mammography and MRI lexicon. Outcome was determined with pathologic analysis or 1-year imaging or clinical follow-up. The χ2 and Fisher exact tests were used for analysis. Results A total of 371 diagnostic CEM studies were performed in 371 women (mean age, 54 years ± 11[SD]). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value of enhancement on CEM images was 95% (104 of 109 [95% CI: 90, 98]), 67% (176 of 262 [95% CI: 61, 73]), 55% (104 of 190 [95% CI: 47, 62]), and 97% (176 of 181 [95% CI: 94, 99]), respectively. Among 190 CEM studies with enhancing findings, enhancing lesions were more likely to be malignant when associated with low-energy findings (26% vs 59%, P < .001). Among enhancement types, mass enhancement composed 71% (99 of 140) of all malignancies with PPV of 63% when associated with low-energy findings. Foci, non-mass enhancement, and mass enhancement without low-energy findings had PPV of 6%, 24%, and 38%, respectively. Neither background parenchymal enhancement nor density was associated with enhancement type (P = .19 and P = .28, respectively). Conclusion Mass enhancement on recombined images using CEM was most commonly associated with malignancy, especially when associated with low-energy findings. Enhancement types were more likely to be benign when not associated with low-energy findings; however, they should still be viewed with suspicion, given the high association with malignancy. © RSNA, 2022 Online supplemental material is available for this article.

Assessment of breast lesions by the Kaiser score for differential diagnosis on MRI: the added value of ADC and machine learning modeling

OBJECTIVES

To evaluate the diagnostic performance of Kaiser score (KS) adjusted with the apparent diffusion coefficient (ADC) (KS+) and machine learning (ML) modeling.

METHODS

A dataset of 402 malignant and 257 benign lesions was identified. Two radiologists assigned the KS. If a lesion with KS > 4 had ADC > 1.4 × 10^-3 mm²/s, the KS was reduced by 4 to become KS+. In order to consider the full spectrum of ADC as a continuous variable, the KS and ADC values were used to train diagnostic models using 5 ML algorithms. The performance was evaluated using the ROC analysis, compared by the DeLong test. The sensitivity, specificity, and accuracy achieved using the threshold of KS > 4, KS+ > 4, and ADC ≤ 1.4 × 10^-3 mm²/s were obtained and compared by the McNemar test.

RESULTS

The ROC curves of KS, KS+, and all ML models had comparable AUC in the range of 0.883-0.921, significantly higher than that of ADC (0.837, p < 0.0001). The KS had sensitivity = 97.3% and specificity = 59.1%; and the KS+ had sensitivity = 95.5% with significantly improved specificity to 68.5% (p < 0.0001). However, when setting at the same sensitivity of 97.3%, KS+ could not improve specificity. In ML analysis, the logistic regression model had the best performance. At sensitivity = 97.3% and specificity = 65.3%, i.e., compared to KS, 16 false-positives may be avoided without affecting true cancer diagnosis (p = 0.0015).

CONCLUSION

Using dichotomized ADC to modify KS to KS+ can improve specificity, but at the price of lowered sensitivity. Machine learning algorithms may be applied to consider the ADC as a continuous variable to build more accurate diagnostic models.

KEY POINTS

• When using ADC to modify the Kaiser score to KS+, the diagnostic specificity according to the results of two independent readers was improved by 9.4-9.7%, at the price of slightly degraded sensitivity by 1.5-1.8%, and overall had improved accuracy by 2.6-2.9%. • When the KS and the continuous ADC values were combined to train models by machine learning algorithms, the diagnostic specificity achieved by the logistic regression model could be significantly improved from 59.1 to 65.3% (p = 0.0015), while maintaining at the high sensitivity of KS = 97.3%, and thus, the results demonstrated the potential of ML modeling to further evaluate the contribution of ADC. • When setting the sensitivity at the same levels, the modified KS+ and the original KS have comparable specificity; therefore, KS+ with consideration of ADC may not offer much practical help, and the original KS without ADC remains as an excellent robust diagnostic method.

The potential of predictive and prognostic breast MRI (P2-bMRI)

Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.

MRI background parenchymal enhancement in patients with invasive lobular carcinoma: Endocrine hormonal treatment effect

OBJECTIVES

High background parenchymal enhancement (BPE) levels and asymmetric distribution could cause diagnostic uncertainty due to morphological similarity to breast cancer, especially invasive lobular carcinoma (ILC). We investigated BPE in ILC patients, its association with the tumor hormonal profile, and the effect of endocrine treatment (ET).

METHODS

The analysis included all MRI examinations performed at our institution between 2010 and 2019 for ILC-diagnosed patients. Baseline study and the first follow-up study were reviewed. Digital medical records were reviewed to retrieve demographics/pathology results/treatment information. BPE and fibroglandular tissue were assessed qualitatively on the contralateral breast according to the criteria of the Breast Imaging Reporting and Data System (BI-RADS).

RESULTS

The study included 129 patients. Most (91%) had pure ILC. All received ET; 12% also received chemotherapy; 90% had surgery first; 70% by breast conservation. On the baseline MRI, 70% had mild or moderate BPE; whereas, on the follow-up study, the majority (59%) had minimal BPE. Most BPE reductions were by 2 degrees. In the baseline study, additional biopsies were required in 59% of cases, and in 17%, a short-term follow-up was recommended. In the follow-up study, biopsies were recommended in 10%, and a short-term follow-up was requested in 16%. A correlation between progesterone receptor intensity index and baseline BPE level was observed (r = 0.3, p = 0.004).

CONCLUSION

ILC patients usually exhibit high BPE. ET decreases BPE, and therefore may decrease false-positive interpretations. Additional research is needed to explore whether study can be performed on ET without compromising sensitivity.

KEY POINTS

∙ High background parenchymal enhancement levels reduces breast MRI sensitivity, yielding high false positive rates especially when reporting cases of invasive lobular carcinoma [ILC].∙Treatment of ILC with endocrine therapy reduces background parenchymal enhancement and thus could decrease these false-positive interpretations.

Accuracy of conventional ultrasound, contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging in assessing the size of breast cancer

OBJECTIVE

This study was performed to investigate the accuracy of conventional ultrasound (US), contrast-enhanced US (CEUS), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the size of breast cancer.

METHODS

In total, 49 breast cancer lesions of 48 patients were included in this study. The inclusion criteria were the performance of total mastectomy or breast-conserving surgery for treatment of breast cancer in our hospital from January 2017 to December 2020 with complete pathological results, as well as the performance of conventional US, CEUS, and DCE-MRI examinations with complete results. The exclusion criteria were non-mass breast cancer shown on conventional US or DCE-MRI, including that found on CEUS with no boundary with surrounding tissues and no confirmed tumor scope; a tumor too large to be completely displayed in the US section, thus affecting the measurement results; the presence of two nodules in the same breast that were too close to each other to be distinguished by any of the three imaging methods; and treatment with preoperative chemotherapy. Preoperative conventional US, CEUS, and DCE-MRI examinations were performed. The postoperative pathological results were taken as the gold standard. The lesion size was represented by its maximum diameter. The accuracy, overestimation, and underestimation rates of conventional US, CEUS, and DCE-MRI were compared.

RESULTS

The maximum lesion diameter on US, CEUS, DCE-MRI and pathology were 1.62±0.63 cm (range, 0.6-3.5 cm), 2.05±0.75 cm (range, 1.0-4.0 cm), 1.99±0.74 cm (range, 0.7-4.2 cm) and 1.92±0.83 cm (range, 0.5-4.0 cm), respectively. The lesion size on US was significantly smaller than that of postoperative pathological tissue (P <  0.05). However, there was no significant difference between the CEUS or DCE-MRI results and the pathological results. The underestimation rate of conventional US (55.1%, 27/49) was significantly higher than that of CEUS (20.4%, 10/49) and DCE-MRI (24.5%, 12/49) (P <  0.001 and P = 0.002, respectively). There was no significant difference in the accuracy of CEUS (36.7%, 18/49) and DCE-MRI (34.7%, 17/49) compared with conventional US (26.5%, 13/49); however, the accuracy of both groups tended to be higher than that of conventional US. The overestimation rate of CEUS (42.9%, 21/49) and DCE-MRI (40.8%, 20/49) was significantly higher than that of conventional US (18.4%, 9/49) (P = 0.001 and P = 0.015, respectively).

CONCLUSIONS

CEUS and DCE-MRI show similar performance when evaluating the size of breast cancer. However, CEUS is more convenient, has a shorter operation time, and has fewer restrictions on its use. Notably, conventional US is more prone to underestimate the size of lesions, whereas CEUS and DCE-MRI are more prone to overestimate the size.

MRI as a biomarker for breast cancer diagnosis and prognosis

Breast cancer (BC) is the most frequently diagnosed female invasive cancer in Western countries and the leading cause of cancer-related death worldwide. Nowadays, tumor heterogeneity is a well-known characteristic of BC, since it includes several nosological entities characterized by different morphologic features, clinical course and response to treatment. Thus, with the spread of molecular biology technologies and the growing knowledge of the biological processes underlying the development of BC, the importance of imaging biomarkers as non-invasive information about tissue hallmarks has progressively grown. To date, breast magnetic resonance imaging (MRI) is considered indispensable in breast imaging practice, with widely recognized indications such as BC screening in females at increased risk, locoregional staging and neoadjuvant therapy (NAT) monitoring. Moreover, breast MRI is increasingly used to assess not only the morphologic features of the pathological process but also to characterize individual phenotypes for targeted therapies, building on developments in genomics and molecular biology features. The aim of this review is to explore the role of breast multiparametric MRI in providing imaging biomarkers, leading to an improved differentiation of benign and malignant breast lesions and to a customized management of BC patients in monitoring and predicting response to treatment. Finally, we discuss how breast MRI biomarkers offer one of the most fertile ground for artificial intelligence (AI) applications. In the era of personalized medicine, with the development of omics-technologies, machine learning and big data, the role of imaging biomarkers is embracing new opportunities for BC diagnosis and treatment.

Evaluation of Breast Cancer Size Measurement by Computer-Aided Diagnosis (CAD) and a Radiologist on Breast MRI

Purpose: This study aimed to evaluate cancer size measurement by computer-aided diagnosis (CAD) and radiologist on breast magnetic resonance imaging (MRI) relative to histopathology and to determine clinicopathologic and MRI factors that may affect measurements. Methods: Preoperative MRI of 208 breast cancers taken between January 2017 and March 2021 were included. We evaluated correlation between CAD-generated size and pathologic size as well as that between radiologist-measured size and pathologic size. We classified size discrepancies into accurate and inaccurate groups. For both CAD and radiologist, clinicopathologic and imaging factors were compared between accurate and inaccurate groups. Results: The mean sizes as predicted by CAD, radiologist and pathology were 2.66 ± 1.68 cm, 2.54 ± 1.68 cm, and 2.30 ± 1.61 cm, with significant difference (p < 0.001). Correlation coefficients of cancer size measurement by radiologist and CAD in reference to pathology were 0.898 and 0.823. Radiologist’s measurement was more accurate than CAD, with statistical significance (p < 0.001). CAD-generated measurement was significantly more inaccurate for cancers of larger pathologic size (>2 cm), in the presence of an extensive intraductal component (EIC), with positive progesterone receptor (PR), and of non-mass enhancement (p = 0.045, 0.045, 0.03 and 0.002). Radiologist-measured size was significantly more inaccurate for cancers in presence of an in situ component, EIC, positive human epidermal growth factor receptor 2 (HER2), and non-mass enhancement (p = 0.017, 0.008, 0.003 and <0.001). Conclusion: Breast cancer size measurement showed a very strong correlation between CAD and pathology and radiologist and pathology. Radiologist-measured size was significantly more accurate than CAD size. Cancer size measurement by CAD and radiologist can both be inaccurate for cancers with EIC or non-mass enhancement.

[Non-genetic indications for risk reducing mastectomies: Guidelines of the National College of French Gynecologists and Obstetricians (CNGOF)]

OBJECTIVE

To determine the value of performing a risk-reducting mastectomy (RRM) in the absence of a deleterious variant of a breast cancer susceptibility gene, in 4 clinical situations at risk of breast cancer.

DESIGN

The CNGOF Commission of Senology, composed of 26 experts, developed these recommendations. A policy of declaration and monitoring of links of interest was applied throughout the process of making the recommendations. Similarly, the development of these recommendations did not benefit from any funding from a company marketing a health product. The Commission of Senology adhered to the AGREE II (Advancing guideline development, reporting and evaluation in healthcare) criteria and followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method to assess the quality of the evidence on which the recommendations were based. The potential drawbacks of making recommendations in the presence of poor quality or insufficient evidence were highlighted.

METHODS

The Commission of Senology considered 8 questions on 4 topics, focusing on histological, familial (no identified genetic abnormality), radiological (of unrecognized cancer), and radiation (history of Hodgkin's disease) risk. For each situation, it was determined whether performing RRM compared with surveillance would decrease the risk of developing breast cancer and/or increase survival.

RESULTS

The Commission of Senology synthesis and application of the GRADE method resulted in 11 recommendations, 6 with a high level of evidence (GRADE 1±) and 5 with a low level of evidence (GRADE 2±).

CONCLUSION

There was significant agreement among the Commission of Senology members on recommendations to improve practice for performing or not performing RRM in the clinical setting.

A Comparative Assessment of MR BI-RADS 4 Breast Lesions With Kaiser Score and Apparent Diffusion Coefficient Value

Objectives

To investigate the diagnostic performance of the Kaiser score and apparent diffusion coefficient (ADC) to differentiate Breast Imaging Reporting and Data System (BI-RADS) Category 4 lesions at dynamic contrast-enhanced (DCE) MRI.

Methods

This was a single-institution retrospective study of patients who underwent breast MRI from March 2020 to June 2021. All image data were acquired with a 3-T MRI system. Kaiser score of each lesion was assigned by an experienced breast radiologist. Kaiser score+ was determined by combining ADC and Kaiser score. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of Kaiser score+, Kaiser score, and ADC. The area under the curve (AUC) values were calculated and compared by using the Delong test. The differences in sensitivity and specificity between different indicators were determined by the McNemar test.

Results

The study involved 243 women (mean age, 43.1 years; age range, 18-67 years) with 268 MR BI-RADS 4 lesions. Overall diagnostic performance for Kaiser score (AUC, 0.902) was significantly higher than for ADC (AUC, 0.81; p = 0.004). There were no significant differences in AUCs between Kaiser score and Kaiser score+ (p = 0.134). The Kaiser score was superior to ADC in avoiding unnecessary biopsies (p < 0.001). Compared with the Kaiser score alone, the specificity of Kaiser score+ increased by 7.82%, however, at the price of a lower sensitivity.

Conclusion

For MR BI-RADS category 4 breast lesions, the Kaiser score was superior to ADC mapping regarding the potential to avoid unnecessary biopsies. However, the combination of both indicators did not significantly contribute to breast cancer diagnosis of this subgroup.

Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review

Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.

Current and Future Directions of Breast MRI

Magnetic resonance imaging (MRI) is the most sensitive exam for detecting breast cancer. The American College of Radiology recommends women with 20% or greater lifetime risk of developing breast cancer be screened annually with MRI. However, other high-risk populations would also benefit. Hartmann et al. reported women with atypical hyperplasia have nearly a 30% incidence of breast cancer at 25-year follow-up. Women with dense breast tissue have up to a 4-fold increased risk of breast cancer when compared to average-risk women; their cancers are more likely to be mammographically occult. Because multiple cohorts of women are at high risk for developing breast cancer, there has been a movement to develop an abbreviated MRI (abMRI) protocol to expand the availability of MRI screening. Studies on abMRI effectiveness have been promising, with Weinstein et al. demonstrating a cancer detection rate of 27.4/1000 in women with dense breasts after a negative digital breast tomosynthesis. Breast MRI is also used to evaluate the extent of disease as part of preoperative assessment in women with newly diagnosed breast cancer, and to assess a patient's response to neoadjuvant chemotherapy. This paper aims to explore the current uses of MRI and propose future indications and directions.

Fibroglandular Tissue and Background Parenchymal Enhancement on Breast MR Imaging Correlates With Breast Cancer

Objectives

To evaluate the association of breast cancer with both the background parenchymal enhancement intensity and volume (BPE_I and BPE_V, respectively) and the amount of fibroglandular tissue (FGT) using an automatic quantitative assessment method in breast magnetic resonance imaging (MRI).

Materials and Methods

Among 17,274 women who underwent breast MRI, 132 normal women (control group), 132 women with benign breast lesions (benign group), and 132 women with breast cancer (cancer group) were randomly selected and matched by age and menopausal status. The area under the receiver operating characteristic curve (AUC) was compared in Cancer vs Control and Cancer vs Benign groups to assess the discriminative ability of BPE_I, BPE_V and FGT.

Results

Compared with the control groups, the cancer group showed a significant difference in BPE_V with a maximum AUC of 0.715 and 0.684 for patients in premenopausal and postmenopausal subgroup, respectively. And the cancer group showed a significant difference in BPE_V with a maximum AUC of 0.622 and 0.633 for patients in premenopausal and postmenopausal subgroup, respectively, when compared with the benign group. FGT showed no significant difference when breast cancer group was compared with normal control and benign lesion group, respectively. Compared with the control groups, BPE_I showed a slight difference in the cancer group. Compared with the benign group, no significant difference was seen in cancer group.

Conclusion

Increased BPE_V is correlated with a high risk of breast cancer While FGT is not.

Screening Breast MRI and the Science of Premenopausal Background Parenchymal Enhancement

The significance of background parenchymal enhancement (BPE) on screening and diagnostic breast MRI continues to be elucidated. Background parenchymal enhancement was initially deemed probably benign and followed or thought of as an artifact degrading the accuracy of breast cancer detection on breast MRI examinations. Subsequent research has focused on understanding the role of BPE regarding screening breast MRI. Today, there is growing evidence that a myriad of factors affect BPE, which in turn may influence patient outcomes. Additionally, BPE could represent an important risk factor for the future development of breast cancer. This article aims to describe the most up-to-date research on BPE as it relates to screening breast MRI in premenopausal women.

Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review

Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.

A Multicentric Comparison of Apparent Diffusion Coefficient Mapping and the Kaiser Score in the Assessment of Breast Lesions

MATERIALS AND METHODS

In this multicentric study, individual patient data from 3 different centers were analyzed. Consecutive patients receiving standardized multiparametric breast magnetic resonance imaging for standard nonscreening indications were included. At each center, 2 experienced radiologists with more than 5 years of experience retrospectively interpreted the examinations in consensus and applied the KS to every histologically verified lesion. The corresponding mean ADC of each lesion was measured using a Wielema type 4 region of interest. According to established methods, the KS and ADC were combined, yielding the KS+ score. Diagnostic accuracy was evaluated by the area under the receiver operating characteristics curve (AUROC) and compared between the KS, ADC, and KS+ (DeLong test). Likewise, the potential to help avoid unnecessary biopsies was compared between the KS, ADC, and KS+ based on established high sensitivity thresholds (McNemar test).

RESULTS

A total of 450 lesions in 414 patients (mean age, 51.5 years; interquartile range, 42-60.8 years) were included, with 219 lesions being malignant (48.7%; 95% confidence interval [CI], 44%-53.4%). The performance of the KS (AUROC, 0.915; CI, 0.886-0.939) was significantly better than that of the ADC (AUROC, 0.848; CI, 0.811-0.880; P < 0.001). The largest difference between these parameters was observed when assessing subcentimeter lesions (AUROC, 0.909 for KS; CI, 0.849-0.950 vs 0.811 for ADC; CI, 0.737-0.871; P = 0.02).The use of the KS+ (AUROC, 0.918; CI, 0.889-0.942) improved the performance slightly, but without any significant difference relative to a single KS or ADC reading (P = 0.64).When applying high sensitivity thresholds for avoiding unnecessary biopsies, the KS and ADC achieved equal sensitivity (97.7% for both; cutoff values, >4 for KS and ≤1.4 × 10-3 mm2/s for ADC). However, the rate of potentially avoidable biopsies was higher when using the KS (specificity: 65.4% for KS vs 32.9% for ADC; P < 0.0001). The KS was superior to the KS+ in avoiding unnecessary biopsies.

CONCLUSIONS

Both the KS and ADC may be used to distinguish benign from malignant breast lesions. However, KS proved superior in this task including, most of all, when assessing small lesions less than 1 cm. Using the KS may avoid twice as many unnecessary biopsies, and the combination of both the KS and ADS does not improve diagnostic performance.

Contrast-enhanced Mammography: How Does It Work?

Contrast-enhanced mammography (CEM) is an imaging technique that uses iodinated contrast medium to improve visualization of breast lesions and assessment of tumor neovascularity. Through modifications in x-ray energy, high- and low-energy images of the breast are combined to highlight areas of contrast medium pooling. The use of contrast material introduces different workflows, artifacts, and risks related to the contrast medium dose. In addition, the need to acquire multiple images in each view introduces different workflows, artifacts, and risks associated with the radiation dose. Although CEM and conventional mammography share many underlying principles, it is important to understand how these two mammographic examinations differ and the mechanisms that facilitate image contrast at CEM. ^©RSNA, 2021.

[Impact of the menstrual cycle on the quality of interpretation of the MRI result in the follow-up of women at genetic risk for breast]

INTRODUCTION

Breast MRI is used as a reference for screening breast cancer among women with a genetic high risk. Its sensitivity and specificity might decrease because of the background parenchymal enhancement. Therefore, it is recommended to plan the MRI between the 7th and the 14th day of the menstrual cycle despite of the burden of this organization. Our aim was to evaluate the interpretation (performance) of the MRI performance when it was done out of this period.

METHODS

We analyzed the MRI done in the Tenon Hospital among patients with a genetic high risk, without a history of breast cancer, between 2006 and 2016. We analyzed the rate of enhancement hindering the interpretation (EH) - that is to say grade III and IV -, the rate of additional explorations (MRI and biopsy), and the occurrence of interval events in 2 groups according to the programming of the examination: appropriate programming (D7-D14) and inappropriate programming (outside this period).

RESULTS

In total, 126 MRI were analyzed, done in a population of 62 women with a genetic predisposition to Breast Cancer (BRCA 1 or 2: 91%, others: 9%), median age was 34.5 years old. 84 were in appropriate programming and 42 were in an inappropriate one. The rate of EH was comparable between the two groups (respectively 31% and 35.7%, P=1), as well as the rate of additional explorations (respectively 31% and 45%, P=0.11).

CONCLUSION

Our results suggest that the programming of screening MRI could be simplified among patients with a genetic predisposition of breast cancer.

Additive value of texture analysis based on breast MRI for distinguishing between benign and malignant non-mass enhancement in premenopausal women

BACKGROUND

Non-mass enhancement (NME) is a diagnostic dilemma and highly reliant on the experience of the radiologists. Texture analysis (TA) could serve as an objective method to quantify lesion characteristics. However, it remains unclear what role TA plays in a predictive model based on routine MRI characteristics. The purpose of this study was to explore the value of TA in distinguishing between benign and malignant NME in premenopausal women.

METHODS

Women in whom NME was histologically proven (n = 147) were enrolled (benign: 58; malignant: 89) was retrospective. Then, 102 and 45 patients were classified as the training and validation groups, respectively. Scanning sequences included Fat-suppressed T2-weighted and fat-suppressed contrast-enhanced T1-weighted which were acquired on a 1.5T MRI system. Clinical and routine MR characteristics (CRMC) were evaluated by two radiologists according to the Breast Imaging and Reporting and Data system (2013). Texture features were extracted from all post-contrast sequences in the training group. The combination model was built and then assessed in the validation group. Pearson's chi-square test and Mann-Whitney U test were used to compare categorical variables and continuous variables, respectively. Logistic regression analysis and receiver operating characteristic curve were employed to assess the diagnostic performance of CRMC, TA, and their combination model in NME diagnosis.

RESULTS

The combination model showed superior diagnostic performance in differentiating between benign and malignant NME compared to that of CRMC or TA alone (AUC, 0.887 vs 0.832 vs 0.74). Moreover, compared to CRMC, the model showed high specificity (72.5% vs 80%). The results obtained in the validation group confirmed the model was promising.

CONCLUSIONS

With the combined use of TA and CRMC could afford an improved diagnostic performance in differentiating between benign and malignant NME.

Radiomics- Quantitative Biomarker Analysis for Breast Cancer Diagnosis and Prediction: A Review

BACKGROUND

Cancer of the breast has become a global problem for women's health. Though concerns regarding early detection and accurate diagnosis were raised, an effort is required for precision medicine as well as personalized treatment. In the past years, the area of medicinal imaging has seen an unprecedented growth that leads to an advancement of radiomics, which provides countless quantitative biomarkers extracted from modern diagnostic images, including a detailed tumor characterization of breast malignancy.

DISCUSSION

In this research, we presented the methodology and implementation of radiomics, together with its future trends and challenges by the basis of published papers. Radiomics could distinguish between malignant from benign tumors, predict prognostic factors, molecular subtypes of breast carcinoma, treatment response to neoadjuvant chemotherapy (NAC), and recurrence survival. The incorporation of quantitative knowledge with clinical, histopathological and genomic information will enable physicians to afford customized care of treatment for patients with breast cancer.

CONCLUSION

Our research was intended to help physicians and radiologists learn fundamental knowledge about radiomics and also to work collaboratively with researchers to explore evidence for further usage in clinical practice.

Breast cancer and background parenchymal enhancement at breast magnetic resonance imaging: a meta-analysis

Background

The background parenchymal enhancement at breast magnetic resonance imaging use to predict breast cancer attracts many searchers to draw a possible relationship. However, the results of their relationships were conflicting. This meta-analysis was performed to assess breast cancer frequency associations with background parenchymal enhancement.

Methods

A systematic literature search up to January 2020 was performed to detect studies recording associations between breast cancer frequency and background parenchymal enhancement. We found thirteen studies including 13,788 women at the start with 4046 breast cancer. We calculated the odds ratio (OR) and the 95% confidence intervals (CIs) between breast cancer frequency and background parenchymal enhancement by the dichotomous technique with a random or fixed-effect model.

Results

Women with minimal or mild background parenchymal enhancement at breast magnetic resonance imaging did not have any risk of breast cancer compared to control women (OR, 1.20; 95% CI 0.54–2.67). However, high background parenchymal enhancement at breast magnetic resonance imaging (OR, 2.66; 95% CI 1.36–5.19) and moderate (OR, 2.51; 95% CI 1.49–4.21) was associated with a significantly higher rate of breast cancer frequency compared to control women.

Conclusions

Our meta-analysis showed that the women with high and moderate background parenchymal enhancement at breast magnetic resonance imaging have higher risks, up to 2.66 fold, of breast cancer. We suggest that women with high or moderate background parenchymal enhancement at breast magnetic resonance imaging to be scheduled for more frequent follow-up and screening for breast cancer to avoid any complications.

Preoperative breast MR imaging in newly diagnosed breast cancer: Comparison of outcomes based on mammographic modality, breast density and breast parenchymal enhancement

PURPOSE

To compare the role of MR for assessment of extent of disease in women newly diagnosed with breast cancer imaged with digital mammography (DM) alone versus digital breast tomosynthesis (DBT).

METHODS

Retrospective review was conducted of 401 consecutive breast MR exams (10/1/2013-7/31/2015) from women who underwent preoperative MR for newly diagnosed breast cancer by either DM or DBT, leaving 388 exams (201 DM and 187 DBT). MR detection of additional, otherwise occult, disease was stratified by modality, breast density, and background parenchymal enhancement. A true-positive finding was defined as malignancy in the ipsilateral-breast >2 cm away from the index-lesion or in the contralateral breast.

RESULTS

50 additional malignancies were detected in 388 exams (12.9%), 37 ipsilateral and 13 contralateral. There was no difference in the MR detection of additional disease in women imaged by either DM versus DBT (p = 0.53). In patients with DM, there was no significant difference in the rate of MR additional cancer detection in dense versus non-dense breasts (p = 0.790). However, in patients with DBT, MR detected significantly more additional sites of malignancy in dense compared to non-dense breasts (p = 0.017). There was no difference in false-positive MR exams (p = 0.470) for DM versus DBT. For both DM and DBT cohorts, higher MR background parenchymal enhancement was associated with higher false-positive (p = 0.040) but no significant difference in true-positive exams.

CONCLUSIONS

Among patients with DBT imaging at cancer diagnosis, women with dense breasts appear to benefit more from preoperative MR than non-dense women. In women imaged only with DM, MR finds additional malignancy across all breast densities.

MRI background parenchymal enhancement, fibroglandular tissue, and mammographic breast density in patients with invasive lobular breast cancer on adjuvant endocrine hormonal treatment: associations with survival

BACKGROUND

To investigate if baseline and/or changes in contralateral background parenchymal enhancement (BPE) and fibroglandular tissue (FGT) measured on magnetic resonance imaging (MRI) and mammographic breast density (MD) can be used as imaging biomarkers for overall and recurrence-free survival in patients with invasive lobular carcinomas (ILCs) undergoing adjuvant endocrine treatment.

METHODS

Women who fulfilled the following inclusion criteria were included in this retrospective HIPAA-compliant IRB-approved study: unilateral ILC, pre-treatment breast MRI and/or mammography from 2000 to 2010, adjuvant endocrine treatment, follow-up MRI, and/or mammography 1-2 years after treatment onset. BPE, FGT, and mammographic MD of the contralateral breast were independently graded by four dedicated breast radiologists according to BI-RADS. Associations between the baseline levels and change in levels of BPE, FGT, and MD with overall survival and recurrence-free survival were assessed using Kaplan-Meier survival curves and Cox regression analysis.

RESULTS

Two hundred ninety-eight patients (average age = 54.1 years, range = 31-79) fulfilled the inclusion criteria. The average follow-up duration was 11.8 years (range = 2-19). Baseline and change in levels of BPE, FGT, and MD were not significantly associated with recurrence-free or overall survival. Recurrence-free and overall survival were affected by histological subtype (p < 0.0001), number of metastatic axillary lymph nodes (p < 0.0001), age (p = 0.01), and adjuvant endocrine treatment duration (p < 0.001).

CONCLUSIONS

Qualitative evaluation of BPE, FGT, and mammographic MD changes cannot predict which patients are more likely to benefit from adjuvant endocrine treatment.

Abbreviated Screening Breast MRI in Women at Higher-than-Average Risk for Breast Cancer with Prior Normal Full Protocol MRI

OBJECTIVE

To compare the performance of abbreviated screening breast MRI (ABMR) versus full protocol MRI (FPMR) in women at higher-than-average risk for breast cancer with a prior normal FPMR.

METHODS

ABMR was performed on higher-than-average-risk women who had a prior normal FPMR. ABMR protocol consisted of short inversion time inversion recovery imaging, precontrast, and two early postcontrast sequences acquired in under 10 minutes. Retrospective review of ABMR examinations performed from July 2016 to July 2018 was compared with a control group who underwent routine screening with FPMR who had a prior normal FPMR performed from July 2014 to June 2016. Screening outcome metrics were calculated and compared, adjusting for differences in patient demographics.

RESULTS

The study cohort included 481 ABMR examinations, while the control group included 440 FPMR studies. There was no significant difference in the abnormal interpretation rate (AIR) or cancer detection rate (CDR) for the ABMR versus the FPMR group (AIR 6.0% vs 6.8% respectively, odds ratio (OR) 0.91, 95% confidence interval (CI): 0.53-1.5, P = 0.73; CDR 8.3 vs 11 cancers detected per 1000 examinations respectively, OR 0.73, 95% CI: 0.20-2.7, P = 0.64). The PPV2 and PPV3 for the ABMR group was 19% and 21% versus 16% and 16% for the FPMR group, with no statistical difference. Sensitivity was 100% in each group with no interval cancers. There was no difference in specificity between the ABMR and FPMR groups, 93% versus 94%, respectively (P = 0.73).

CONCLUSION

ABMR may be used to screen higher-than-average-risk women with a prior normal FPMR as outcome metrics are equivalent to FPMR.

Factors Associated With Background Parenchymal Enhancement on Contrast-Enhanced Mammography

OBJECTIVE. The purpose of this study was to determine the relationship between background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM) and breast tissue density, menstrual status, endocrine therapy, and risk factors for breast cancer and also to evaluate interreader agreement on classification of BPE on CEM. MATERIALS AND METHODS. Five subspecialty-trained breast radiologists independently and blindly graded tissue density (with fatty tissue and scattered fibroglandular tissue classified as nondense tissue and with heterogeneously dense and extremely dense classified as dense tissue) and BPE (with minimal or mild BPE categorized as low BPE and moderate or marked BPE categorized as high BPE) on CEM examinations performed from 2014 to 2018. Electronic medical charts were reviewed for information on menstrual status, endocrine therapy, history of breast surgery, and other risk factors for breast cancer. Comparisons were performed using the Kruskal-Wallis test, Mann-Whitney test, and Spearman rank correlation. Interreader agreement was estimated using the Fleiss kappa test. RESULTS. A total of 202 patients (mean [± SD] age, 54 ± 10 years; range, 25-84 years) underwent CEM. Tissue density was categorized as fatty in two patients (1%), scattered fibroglandular in 67 patients (33%), heterogeneously dense in 117 patients (58%), and extremely dense in 16 patients (8%). Among the 202 patients, BPE was minimal in 77 (38%), mild in 80 (40%), moderate in 31 (15%), and marked in 14 (7%). Dense breasts, younger age, premenopausal status, no history of endocrine therapy, and no history of breast cancer were significantly associated with high BPE. Among premenopausal patients, no association was found between BPE and time from last menstrual period to CEM. Overall interreader agreement on BPE was moderate (κ = 0.41; 95% CI, 0.40-0.42). Interreader agreement on tissue density was substantial (κ = 0.67; 95% CI, 0.66-0.69). CONCLUSION. Women with dense breasts, premenopausal status, and younger age are more likely to have greater BPE. Targeting CEM to the last menstrual period is not indicated.

Possible Breast Cancer Risk Related to Background Parenchymal Enhancement at Breast MRI: A Meta-Analysis Study

BACKGROUND

The higher level of background parenchymal enhancement (BPE) at breast magnetic resonance imaging (MRI) has drawn considerable attention in the early detection and prediction of breast cancer. It has been reported that there is a possible relationship between the level of BPE at breast MRI and the presence of breast cancer. This meta-analysis was performed to evaluate this relationship.

METHODS

Through a systematic literature search up to December 2019, 12 studies with 9541 females, 3870 of them were breast cancer. They were identified reporting relationships between breast cancer and BPE at breast MRI with its different categories (10 related to minimal or mild BPE, eight related to moderate BPE and nine related to high BPE). Odd ratio(OR) with 95% confidence intervals (CIs) was calculated comparing breast cancer prevalence and BPE at breast MRI using dichotomous method with a random or fixed effect model.

RESULTS

Females with high (OR, 2.93; 95% CI, 1.24-6.88) and moderate (OR, 2.89; 95% CI, 1.51-5.52) BPE at breast MRI was related with high odds to breast cancer compared to control females. However, females with minimal or mild BPE at breast MRI (OR, 1.33; 95% CI, 0.56-3.17) did not have such risk on breast cancer. The impact of BPE on breast cancer may have a great influence as a tool for improving early detection and prevention of breast cancer.

CONCLUSIONS

Based on this meta-analysis, females with high or moderate BPE at breast MRI may have an independent relationship with the risk of breast cancer. This relationship forces us to recommend follow up with those with high or moderate BPE at breast MRI to avoid any complication.

Breast density, MR imaging biomarkers, and breast cancer risk

Mammographic breast density and various breast MRI features are imaging biomarkers that can predict a woman's future risk of breast cancer. While mammographic density (MD) has been established as an independent risk factor for the development of breast cancer, MD assessment methods need to be accurate and reproducible for widespread clinical use in stratifying patients based on their risk. In addition, a number of breast MRI biomarkers using contrast-enhanced and noncontrast-enhanced techniques are also being investigated as risk predictors. The validation and standardization of these breast MRI biomarkers will be necessary for population-based clinical implementation of patient risk stratification, as well. This review provides an update on MD assessment methods, breast MRI biomarkers, and their ability to predict breast cancer risk.

Current Landscape of Breast Cancer Imaging and Potential Quantitative Imaging Markers of Response in ER-Positive Breast Cancers Treated with Neoadjuvant Therapy

In recent years, neoadjuvant treatment trials have shown that breast cancer subtypes identified on the basis of genomic and/or molecular signatures exhibit different response rates and recurrence outcomes, with the implication that subtype-specific treatment approaches are needed. Estrogen receptor-positive (ER+) breast cancers present a unique set of challenges for determining optimal neoadjuvant treatment approaches. There is increased recognition that not all ER+ breast cancers benefit from chemotherapy, and that there may be a subset of ER+ breast cancers that can be treated effectively using endocrine therapies alone. With this uncertainty, there is a need to improve the assessment and to optimize the treatment of ER+ breast cancers. While pathology-based markers offer a snapshot of tumor response to neoadjuvant therapy, non-invasive imaging of the ER disease in response to treatment would provide broader insights into tumor heterogeneity, ER biology, and the timing of surrogate endpoint measurements. In this review, we provide an overview of the current landscape of breast imaging in neoadjuvant studies and highlight the technological advances in each imaging modality. We then further examine some potential imaging markers for neoadjuvant treatment response in ER+ breast cancers.

Relationship Between Breast Ultrasound Background Echotexture and Magnetic Resonance Imaging Background Parenchymal Enhancement and the Effect of Hormonal Status Thereon

We studied the relationship between breast ultrasound background echotexture (BET) and magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and whether this relationship varied with hormonal status and amount of fibroglandular tissue (FGT) on MRI. Two hundred eighty-three Korean women (52.1 years; range = 27-79 years) with newly diagnosed primary breast cancer who underwent preoperative breast ultrasound and MRI were retrospectively studied. Background echotexture, BPE, and FGT were classified into 4 categories, and age, menopausal status, menstrual cycle regularity, and menstrual cycle stage at MRI were recorded. Background echotexture and BPE relationship was assessed overall, and in menopausal, FGT, menstrual cycle regularity, and menstrual cycle stage subgroups. Background echotexture and BPE correlated in women overall, and menopausal, FGT, and menstrual cycle subgroups and those in the first half of the cycle (all P < 0.001). Background echotexture reflects BPE, regardless of menopausal status, menstrual cycle regularity, and FGT and may be a biomarker of breast cancer risk.

Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer among women worldwide, and early detection remains a principal factor for improved patient outcomes and reduced mortality. Clinically, magnetic resonance imaging (MRI) techniques are routinely used in determining benign and malignant tumor phenotypes and for monitoring treatment outcomes. Static MRI techniques enable superior structural contrast between adipose and fibroglandular tissues, while dynamic MRI techniques can elucidate functional characteristics of malignant tumors. The preferred clinical procedure-dynamic contrast-enhanced MRI-illuminates the hypervascularity of breast tumors through a gadolinium-based contrast agent; however, accumulation of the potentially toxic contrast agent remains a major limitation of the technique, propelling MRI research toward finding an alternative, noninvasive method. Three such techniques are magnetic resonance spectroscopy, chemical exchange saturation transfer, and non-contrast diffusion weighted imaging. These methods shed light on underlying chemical composition, provide snapshots of tissue metabolism, and more pronouncedly characterize microstructural heterogeneity. This review article outlines the present state of clinical MRI for breast cancer and examines several research techniques that demonstrate capacity for clinical translation. Ultimately, multi-parametric MRI-incorporating one or more of these emerging methods-presently holds the best potential to afford improved specificity and deliver excellent accuracy to clinics for the prediction, detection, and monitoring of breast cancer.