Background parenchymal enhancement in breast MRI before and after neoadjuvant chemotherapy: correlation with tumour response

Advances in analytical approaches for background parenchymal enhancement in predicting breast tumor response to neoadjuvant chemotherapy: A systematic review

BACKGROUND

Breast cancer (BC) continues to pose a substantial global health concern, necessitating continuous advancements in therapeutic approaches. Neoadjuvant chemotherapy (NAC) has gained prominence as a key therapeutic strategy, and there is growing interest in the predictive utility of Background Parenchymal Enhancement (BPE) in evaluating the response of breast tumors to NAC. However, the analysis of BPE as a predictive biomarker, along with the techniques used to model BPE changes for accurate and timely predictions of treatment response presents several obstacles. This systematic review aims to thoroughly investigate recent advancements in the analytical methodologies for BPE analysis, and to evaluate their reliability and effectiveness in predicting breast tumor response to NAC, ultimately contributing to the development of personalized and effective therapeutic strategies.

METHODS

A comprehensive and structured literature search was conducted across key electronic databases, including Cochrane Database of Systematic Reviews, Google Scholar, PubMed, and IEEE Xplore covering articles published up to May 10, 2024. The inclusion criteria targeted studies focusing on breast cancer cohorts treated with NAC, involving both pre-treatment and at least one post-treatment breast dynamic contrast-enhanced Magnetic Resonance Imaging (DCE-MRI) scan, and analyzing BPE utility in predicting breast tumor response to NAC. Methodological quality assessment and data extraction were performed to synthesize findings and identify commonalities and differences among various BPE analytical approaches.

RESULTS

The search yielded a total of 882 records. After meticulous screening, 78 eligible records were identified, with 13 studies ultimately meeting the inclusion criteria for the systematic review. Analysis of the literature revealed a significant evolution in BPE analysis, from early studies focusing on single time-point BPE analysis to more recent studies adopting longitudinal BPE analysis. The review uncovered several gaps that compromise the accuracy and timeliness of existing longitudinal BPE analysis methods, such as missing data across multiple imaging time points, manual segmentation of the whole-breast region of interest, and over reliance on traditional statistical methods like logistic regression for modeling BPE and pathological complete response (pCR).

CONCLUSION

This review provides a thorough examination of current advancements in analytical approaches for BPE analysis in predicting breast tumor response to NAC. The shift towards longitudinal BPE analysis has highlighted significant gaps, suggesting the need for alternative analytical techniques, particularly in the realm of artificial intelligence (AI). Future longitudinal BPE research work should focus on standardization in longitudinal BPE measurement and analysis, through integration of deep learning-based approaches for automated tumor segmentation, and implementation of advanced AI technique that can better accommodate varied breast tumor responses, non-linear relationships and complex temporal dynamics in BPE datasets, while also handling missing data more effectively. Such integration could lead to more precise and timely predictions of breast tumor responses to NAC, thereby enhancing personalized and effective breast cancer treatment strategies.

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.

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures. Existing quantitative approaches, like radiomics and deep learning models, lack explicit quantification of intricate and subtle parenchymal structures, including fibroglandular tissue. To address this, we propose a novel topological approach that explicitly extracts multi-scale topological structures to better approximate breast parenchymal structures, and then incorporates these structures into a deep-learning-based prediction model via an attention mechanism. Our topology-informed deep learning model, TopoTxR, leverages topology to provide enhanced insights into tissues critical for disease pathophysiology and treatment response. We empirically validate TopoTxR using the VICTRE phantom breast dataset, showing that the topological structures extracted by our model effectively approximate the breast parenchymal structures. We further demonstrate TopoTxR's efficacy in predicting response to neoadjuvant chemotherapy. Our qualitative and quantitative analyses suggest differential topological behavior of breast tissue in treatment-naïve imaging, in patients who respond favorably to therapy as achieving pathological complete response (pCR) versus those who do not. In a comparative analysis with several baselines on the publicly available I-SPY 1 dataset (N = 161, including 47 patients with pCR and 114 without) and the Rutgers proprietary dataset (N = 120, with 69 patients achieving pCR and 51 not), TopoTxR demonstrates a notable improvement, achieving a 2.6% increase in accuracy and a 4.6% enhancement in AUC compared to the state-of-the-art method.

Increased background parenchymal enhancement on peri-menopausal breast magnetic resonance imaging

Objectives

To examine the background parenchymal enhancement (BPE) levels in peri-menopausal breast MRI compared with pre- and post-menopausal breast MRI.

Methods

This study included 562 patients (55.8±12.3 years) who underwent contrast-enhanced dynamic breast MRI between 2011 and 2015 for clinical indications. We evaluated the BPE level, amount of fibroglandular tissue (FGT), and social and clinical variables. The inter-reader agreement for the amount of FGT and the BPE level was evaluated using interclass correlation coefficients. Associations between the BPE level and body mass index (BMI), ages of menarche and menopause, childbirth history, number of children, and the amount of FGT were determined using Spearman's correlation coefficients or Mann-Whitney U-test. Pearson's χ2 test was used to assess the difference in the frequency of BPE categories among the age-groups.

Results

The inter-reader agreement was 0.864 for the amount of FGT and 0.840 for the BPE level, both indicating almost perfect agreement. The BPE level showed a weak positive correlation with the amount of FGT (Spearman's ρ=0.271, P<0.001). BPE was not significantly correlated with BMI, childbirth history, number of births, or ages of menarche or menopause. BPE was greater in the peri-menopausal age-group compared with the corresponding pre- and post-menopausal age-groups, both with benign and malignant lesions.

Conclusions

BPE was greater in the peri-menopausal stage than in the pre- and post-menopausal stages. Our results suggest that BPE showed a non-linear decrease with age and that the hormonal disbalance in the peri-menopausal period has a greater effect on the BPE level than was previously assumed.

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.

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.

Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization

Background The level of background parenchymal enhancement (BPE) at breast MRI provides predictive and prognostic information and can have diagnostic implications. However, there is a lack of standardization regarding BPE assessment. Purpose To investigate how well results of quantitative BPE assessment methods correlate among themselves and with assessments made by radiologists experienced in breast MRI. Materials and Methods In this pseudoprospective analysis of 5773 breast MRI examinations from 3207 patients (mean age, 60 years ± 10 [SD]), the level of BPE was prospectively categorized according to the Breast Imaging Reporting and Data System by radiologists experienced in breast MRI. For automated extraction of BPE, fibroglandular tissue (FGT) was segmented in an automated pipeline. Four different published methods for automated quantitative BPE extractions were used: two methods (A and B) based on enhancement intensity and two methods (C and D) based on the volume of enhanced FGT. The results from all methods were correlated, and agreement was investigated in comparison with the respective radiologist-based categorization. For surrogate validation of BPE assessment, how accurately the methods distinguished premenopausal women with (n = 50) versus without (n = 896) antihormonal treatment was determined. Results Intensity-based methods (A and B) exhibited a correlation with radiologist-based categorization of 0.56 ± 0.01 and 0.55 ± 0.01, respectively, and volume-based methods (C and D) had a correlation of 0.52 ± 0.01 and 0.50 ± 0.01 (P < .001). There were notable correlation differences (P < .001) between the BPE determined with the four methods. Among the four quantitation methods, method D offered the highest accuracy for distinguishing women with versus without antihormonal therapy (P = .01). Conclusion Results of different methods for quantitative BPE assessment agree only moderately among themselves or with visual categories reported by experienced radiologists; intensity-based methods correlate more closely with radiologists' ratings than volume-based methods. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Mann in this issue.

Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer patients: use of MRI radiomics data from three regions with multiple machine learning algorithms

OBJECTIVE

To construct a multi-region MRI radiomics model for predicting pathological complete response (pCR) in breast cancer (BCa) patients who received neoadjuvant chemotherapy (NACT) and provide a theoretical basis for the peritumoral microenvironment affecting the efficacy of NACT.

METHODS

A total of 133 BCa patients who received NACT, including 49 with confirmed pCR, were retrospectively analyzed. The radiomics features of the intratumoral region, peritumoral region, and background parenchymal enhancement (BPE) were extracted, and the most relevant features were obtained after dimensional reduction. Then, combining different areas, multivariate logistic regression analysis was used to select the optimal feature set, and six different machine learning models were used to predict pCR. The optimal model was selected, and its performance was evaluated using receiver operating characteristic (ROC) analysis. SHAP analysis was used to examine the relationship between the features of the model and pCR.

RESULTS

For signatures constructed using three individual regions, BPE provided the best predictions of pCR, and the diagnostic performance of the intratumoral and peritumoral regions improved after adding the BPE signature. The radiomics signature from the combination of all the three regions with the XGBoost machine learning algorithm provided the best predictions of pCR based on AUC (training set: 0.891, validation set: 0.861), sensitivity (training set: 0.882, validation set: 0.800), and specificity (training set: 0.847, validation set: 0.84). SHAP analysis demonstrated that LZ_log.sigma.2.0.mm.3D_glcm_ClusterShade_T12 made the greatest contribution to the predictions of this model.

CONCLUSION

The addition of the BPE MRI signature improved the prediction of pCR in BCa patients who received NACT. These results suggest that the features of the peritumoral microenvironment are related to the efficacy of NACT.

Predictive value of background parenchymal enhancement on breast magnetic resonance imaging for pathological tumor response to neoadjuvant chemotherapy in breast cancers: a systematic review

OBJECTIVES

This review aimed to assess the predictive value of background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) as an imaging biomarker for pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT).

METHODS

Two reviewers independently performed a systemic literature search using the PubMed, MEDLINE, and Embase databases for studies published up to 11 June 2022. Data from relevant articles were extracted to assess the relationship between BPE and pCR.

RESULTS

This systematic review included 13 studies with extensive heterogeneity in population characteristics, MRI follow-up points, MRI protocol, NACT protocol, pCR definition, and BPE assessment. Baseline BPE levels were not associated with pCR, except in 1 study that reported higher baseline BPE of the younger participants (< 55 years) in the pCR group than the non-pCR group. A total of 5 studies qualitatively assessed BPE levels and indicated a correlation between reduced BPE after NACT and pCR; however, among the studies that quantitatively measured BPE, the same association was observed only in the subgroup analysis of 2 articles that assessed the status of hormone receptor and human epidermal growth factor receptor 2. In addition, the predictive ability of early BPE changes for pCR was reported in several articles and remains controversial.

CONCLUSIONS

Changes in BPE may be a promising imaging biomarker for predicting pCR in breast cancer. Because current studies remain insufficient, particularly those that quantitatively measure BPE, prospective and multicenter large-sample studies are needed to confirm this relationship.

Bilateral asymmetry of quantitative parenchymal kinetics at ultrafast DCE-MRI predict response to neoadjuvant chemotherapy in patients with HER2+ breast cancer

PURPOSE

To assess whether measurement of the bilateral asymmetry of semiquantitative and quantitative perfusion parameters from ultrafast dynamic contrast-enhanced MRI (DCE-MRI), allows early prediction of pathologic response after neoadjuvant chemotherapy (NAC) in patients with HER2+ breast cancer.

MATERIALS AND METHODS

Twenty-eight female patients with HER2+ breast cancer treated with NAC who underwent pre-NAC ultrafast DCE-MRI (3-9 s/phase) were enrolled for this study. Four semiquantitative and two quantitative parenchymal parameters were calculated for each patient. Ipsilateral/contralateral (I/C) ratio (for four parameters) and the difference between (for two parameters) ipsi- and contra-lateral parenchymal kinetic parameters (kBPE) were compared for patients with pathologic complete response (pCR) and those having residual disease. Lasso regression with leave-one-out cross validation was used to determine the optimal combination of parameters for a regression model and multivariable logistic regression was used to identify independent predictors for pCR. Chi-squared test, two-sided t-test and Kruskal-Wallis test were used.

RESULTS

The Ktrans I/C ratio cutoff value of 1.11 had a sensitivity of 83.3% and specificity of 75% for pCR. The ve I/C ratio cutoff value of 1.1 had a sensitivity of 75% and specificity of 81.3% for pCR. The area under the receiver operating characteristic curve of the three-kBPE parameter model, including initial area under the enhancement curve (AUC30) I/C ratio, KtransI/C ratio and ve I/C ratio, was 0.89 with sensitivity of 91.7% at specificity of 81.3%.

CONCLUSION

Quantitative assessment of bilateral asymmetry kBPE from pre-NAC ultrafast DCE-MRI can predict pCR in patients with HER2+ breast cancer.

A Diagnostic Dilemma: New Enhancing Suspicious Findings on Breast MRI Following Neoadjuvant Chemotherapy

OBJECTIVE

Evaluate the incidence and outcome of new enhancing findings on breast MRI after neoadjuvant chemotherapy (NAC).

METHODS

This IRB-approved retrospective review included women with breast cancer undergoing MRI to evaluate NAC response at our institution from January 1, 1998 to March 3, 2021. Post-NAC MRIs given BI-RADS 4 or 5 with new enhancing findings were identified. Patients were excluded if they lacked pretreatment MRI or insufficient follow-up, or if the finding was a satellite of the primary tumor. Medical records and imaging studies were reviewed to identify patients and to find characteristics and outcomes.

RESULTS

Over the study period, 2880 post-NAC breast MRIs were performed. Of 128 post-NAC MRIs given BI-RADS 4 or 5 (4.4%), 35 new suspicious findings were found on 32 MRIs, incidence rate 1.1% (32/2880). Most were characterized as nonmass enhancement (17/35, 49%), followed by mass (11/35, 31%), and then focus (7/35, 20%), with an average maximum dimension of 1.3 cm (range 0.3-7.1 cm). New findings were ipsilateral to the index cancer in 20/35 (57%) of cases. Of the 35 suspicious findings, 22 underwent image-guided biopsy (62%), 1 was surgically excised (3%), 7 underwent mastectomy (20%), 5 were stable or resolved on follow-up (8%), and none were malignant. Thirty-three were benign (94%), and two were benign high-risk lesions (atypical ductal hyperplasia, radial scar) (6%).

CONCLUSION

New suspicious breast MRI findings after NAC are uncommon with a low likelihood of malignancy. Further study is warranted using multi-institutional data for this low incidence finding.

Molecular hallmarks of breast multiparametric magnetic resonance imaging during neoadjuvant chemotherapy

PURPOSE

To identify molecular basis of four parameters obtained from dynamic contrast-enhanced magnetic resonance imaging, including functional tumor volume (FTV), longest diameter (LD), sphericity, and contralateral background parenchymal enhancement (BPE).

MATERIAL AND METHODS

Pretreatment-available gene expression profiling and different treatment timepoints MRI features were integrated for Spearman correlation analysis. MRI feature-related genes were submitted to hypergeometric distribution-based gene functional enrichment analysis to identify related Kyoto Encyclopedia of Genes and Genomes annotation. Gene set variation analysis was utilized to assess the infiltration of distinct immune cells, which were used to determine relationships between immune phenotypes and medical imaging phenotypes. The clinical significance of MRI and relevant molecular features were analyzed to identify their prediction performance of neoadjuvant chemotherapy (NAC) and prognostic impact.

RESULTS

Three hundred and eighty-three patients were included for integrative analysis of MRI features and molecular information. FTV, LD, and sphericity measurements were most positively significantly correlated with proliferation-, signal transmission-, and immune-related pathways, respectively. However, BPE did not show marked correlation relationships with gene expression alteration status. FTV, LD and sphericity all showed significant positively or negatively correlated with some immune-related processes and immune cell infiltration levels. Sphericity decreased at 3 cycles after treatment initiation was also markedly negatively related to baseline sphericity measurements and immune signatures. Its decreased status could act as a predictor for prediction of response to NAC.

CONCLUSION

Different MRI features capture different tumor molecular characteristics that could explain their corresponding clinical significance.

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected patients.

Differences Between Ipsilateral and Contralateral Early Parenchymal Enhancement Kinetics Predict Response of Breast Cancer to Neoadjuvant Therapy

RATIONALE AND OBJECTIVES

To determine whether kinetics measured with ultrafast dynamic contrast-enhanced magnetic resonance imaging in tumor and normal parenchyma pre- and post-neoadjuvant therapy (NAT) can predict the response of breast cancer to NAT.

MATERIALS AND METHODS

Twenty-four patients with histologically confirmed invasive breast cancer were enrolled. They were scanned with ultrafast dynamic contrast-enhanced magnetic resonance imaging (3-7 seconds/frame) pre- and post-NAT. Four kinetic parameters were calculated in the segmented tumors, and ipsi- and contra-lateral normal parenchyma: (1) tumor (tSE30) or background parenchymal relative enhancement at 30 seconds (BPE30), (2) maximum relative enhancement slope (MaxSlope), (3) bolus arrival time (BAT), and (4) area under relative signal enhancement curve for the initial 30 seconds (AUC30). The tumor kinetics and the differences between ipsi- and contra-lateral parenchymal kinetics were compared for patients achieving pathologic complete response (pCR) vs those who had residual disease after NAT. The chi-squared test and two-sided t-test were used for baseline demographics. The Wilcoxon rank sum test and one-way analysis of variance were used for differential responses to therapy.

RESULTS

Patients with similar pre-NAT mean BPE30, median BAT and mean AUC30 in the ipsi- and contralateral normal parenchyma were more likely to achieve pCR following NAT (p < 0.02). Patients classified as having residual cancer burden (RCB) II after NAT showed higher post-NAT tSE30 and tumor AUC30 and higher post-NAT MaxSlope in ipsilateral normal parenchyma compared to those classified as RCB I or pCR (p < 0.05).

CONCLUSION

Bilateral asymmetry in normal parenchyma could predict treatment outcome prior to NAT. Post-NAT tumor kinetics could evaluate the aggressiveness of residual tumor.

Ultrasound Strain Elastography and Contrast-Enhanced Ultrasound in Predicting the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer: A Nomogram Integrating Ki-67 and Ultrasound Features

OBJECTIVES

To explore whether conventional elastography and contrast-enhanced ultrasound (CEUS) combined with histopathology can monitor the efficacy of neoadjuvant chemotherapy (NAC) for breast cancer (BC), and develop a Nomogram prediction model monitoring response to NAC.

METHODS

From February 2010 to November 2015, 91 BC patients who received NAC were recruited. The maximum diameter, stiffness, and CEUS features were assessed. Core biopsy, surgical pathology immunophenotype, and Miller-Payne (MP) evaluation were documented. Univariate and multivariate analysis was performed using receiver operating characteristic (ROC) analysis and logistic regression analysis.

RESULTS

There were 37 cases showing pathological complete response (pCR) and 54 of non-pCR. The changes of maximal diameter were correlated with MP (P < .05). The sensitivity (SEN), specificity (SPE), and area under the ROC curve (AUC) of baseline size predicting pCR were 57.40%, 70.30%, and 0.64 (P = .024). Baseline Ki-67 index of pCR group is significantly higher than that of non-pCR group (P = .029), and the ROC analysis of baseline Ki-67 indicates the SEN, SPE, and AUC of 51.70%, 78.00%, and 0.638 (P = .050). When combined with size, CEUS features, stiffness, and Ki-67 of baseline, the ROC curve shows good performance with SEN, SPE, and AUC of 70.00%, 76.19%, 0.821 (P = .004). Incorporating the change of characteristics into multivariate regression analysis, the results demonstrate excellent performance (SEN 100.00%, SPE 95.24%, AUC 0.986, P = .000).

CONCLUSIONS

The change of the maximum size was correlated with MP score, which can provide reference to predict efficacy of NAC and evaluate residual lesions. When combining with elastography, CEUS, and Ki-67, better performance in predicting pathological response was shown.

Comparison of background parenchymal enhancement (BPE) on contrast-enhanced cone-beam breast CT (CE-CBBCT) and breast MRI

OBJECTIVES

To compare the background parenchymal enhancement (BPE) levels on contrast-enhanced cone-beam breast CT (CE-CBBCT) and MRI, evaluate inter-reader reliability, and analyze the relationship between clinical factors and BPE level on CE-CBBCT.

METHODS

In this retrospective study, patients who underwent both CE-CBBCT and MRI were analyzed. BPE levels on CE-CBBCT and MRI were assessed by five specialists independently in random fashion, with a wash-out period of 4 weeks. Weighted kappa was used to analyze the agreement between CE-CBBCT and MRI, and intraclass correlation coefficient (ICC) was used to evaluate the inter-reader reliability for each modality. The association between BPE level on CE-CBBCT and clinical factors was evaluated by univariate and multivariate logistic regression.

RESULTS

A total of 221 patients from January 2017 to April 2021 were enrolled. CE-CBBCT showed substantial agreement (weighted kappa = 0.690) with MRI for BPE evaluation, with good degree of inter-reader reliability on both CE-CBBCT (ICC = 0.712) and MRI (ICC = 0.757). Based on majority reports, BPE levels on CE-CBBCT were lower than MRI (p < 0.001). BPE level on CE-CBBCT was significantly associated with menstrual status (odds ratio, OR = 0.125), breast density (OR = 2.308), and previously treated breast cancer (OR = 0.052) (all p < 0.05). BPE level for premenopausal patients was associated with menstrual cycle, with lower BPE level for the 2^nd week of menstrual cycle (OR = 0.246).

CONCLUSIONS

CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation, indicating that the corresponding BI-RADS lexicons could be used to describe BPE level on CE-CBBCT. The 2^nd week of menstrual cycle timing is suggested as the optimal examination period for CE-CBBCT.

KEY POINTS

• CE-CBBCT showed substantial agreement and comparable inter-reader reliability with MRI for BPE evaluation. • Menstrual status, breast density, and previously treated breast cancer were associated with the BPE level on CE-CBBCT images. • The 2^ndweek of the menstrual cycle is suggested as the optimal examination period for CE-CBBCT.

Post-Processing Bias Field Inhomogeneity Correction for Assessing Background Parenchymal Enhancement on Breast MRI as a Quantitative Marker of Treatment Response

Background parenchymal enhancement (BPE) of breast fibroglandular tissue (FGT) in dynamic contrast-enhanced breast magnetic resonance imaging (MRI) has shown an association with response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. Fully automated segmentation of FGT for BPE calculation is a challenge when image artifacts are present. Low spatial frequency intensity nonuniformity due to coil sensitivity variations is known as bias or inhomogeneity and can affect FGT segmentation and subsequent BPE measurement. In this study, we utilized the N4ITK algorithm for bias correction over a restricted bilateral breast volume and compared the contralateral FGT segmentations based on uncorrected and bias-corrected images in three MRI examinations at pre-treatment, early treatment and inter-regimen timepoints during NAC. A retrospective analysis of 2 cohorts was performed: one with 735 patients enrolled in the multi-center I-SPY 2 TRIAL and the sub-cohort of 340 patients meeting a high-quality benchmark for segmentation. Bias correction substantially increased the FGT segmentation quality for 6.3–8.0% of examinations, while it substantially decreased the quality for no examination. Our results showed improvement in segmentation quality and a small but statistically significant increase in the resulting BPE measurement after bias correction at all timepoints in both cohorts. Continuing studies are examining the effects on pCR prediction.

Background parenchymal enhancement in contrast-enhanced MR imaging suggests systemic effects of intrauterine contraceptive devices

OBJECTIVES

Levonorgestrel-releasing intrauterine contraceptive devices (LNG-IUDs) are designed to exhibit only local hormonal effects. There is an ongoing debate on whether LNG-IUDs can have side effects similar to systemic hormonal medication. Benign background parenchymal enhancement (BPE) in dynamic contrast-enhanced (DCE) MRI has been established as a sensitive marker of hormonal stimulation of the breast. We investigated the association between LNG-IUD use and BPE in breast MRI to further explore possible systemic effects of LNG-IUDs.

METHODS

Our hospital database was searched to identify premenopausal women without personal history of breast cancer, oophorectomy, and hormone replacement or antihormone therapy, who had undergone standardized DCE breast MRI at least twice, once with and without an LNG-IUD in place. To avoid confounding aging-related effects on BPE, half of included women had their first MRI without, the other half with, LNG-IUD in place. Degree of BPE was analyzed according to the ACR categories. Wilcoxon-matched-pairs signed-rank test was used to compare the distribution of ACR categories with vs. without LNG-IUD.

RESULTS

Forty-eight women (mean age, 46 years) were included. In 24/48 women (50% [95% CI: 35.9-64.1%]), ACR categories did not change with vs. without LNG-IUDs. In 23/48 women (48% [33.9-62.1%]), the ACR category was higher with vs. without LNG-IUDs; in 1/48 (2% [0-6%]), the ACR category was lower with vs. without LNG-IUDs. The change of ACR category depending on the presence or absence of an LNG-IUD proved highly significant (p < 0.001).

CONCLUSION

The use of an LNG-IUD can be associated with increased BPE in breast MRI, providing further evidence that LNG-IUDs do have systemic effects.

KEY POINTS

• The use of levonorgestrel-releasing intrauterine contraceptive devices is associated with increased background parenchymal enhancement in breast MRI. • This suggests that hormonal effects of these devices are not only confined to the uterine cavity, but may be systemic. • Potential systemic effects of levonorgestrel-releasing intrauterine contraceptive devices should therefore be considered.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Response Predictivity to Neoadjuvant Therapies in Breast Cancer: A Qualitative Analysis of Background Parenchymal Enhancement in DCE-MRI

Background: For assessing the predictability of oncology neoadjuvant therapy results, the background parenchymal enhancement (BPE) parameter in breast magnetic resonance imaging (MRI) has acquired increased interest. This work aims to qualitatively evaluate the BPE parameter as a potential predictive marker for neoadjuvant therapy. Method: Three radiologists examined, in triple-blind modality, the MRIs of 80 patients performed before the start of chemotherapy, after three months from the start of treatment, and after surgery. They identified the portion of fibroglandular tissue (FGT) and BPE of the contralateral breast to the tumor in the basal control pre-treatment (baseline). Results: We observed a reduction of BPE classes in serial MRI checks performed during neoadjuvant therapy, as compared to baseline pre-treatment conditions, in 61.3% of patients in the intermediate step, and in 86.7% of patients in the final step. BPE reduction was significantly associated with sequential anthracyclines/taxane administration in the first cycle of neoadjuvant therapy compared to anti-HER2 containing therapies. The therapy response was also significantly related to tumor size. There were no associations with menopausal status, fibroglandular tissue (FGT) amount, age, BPE baseline, BPE in intermediate, and in the final MRI step. Conclusions: The measured variability of this parameter during therapy could predict therapy effectiveness in early stages, improving decision-making in the perspective of personalized medicine. Our preliminary results suggest that BPE may represent a predictive factor in response to neoadjuvant therapy in breast cancer, warranting future investigations in conjunction with radiomics.

The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy

PURPOSE

This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer.

METHOD

Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue.

RESULTS

The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints).

CONCLUSION

The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.

Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for the Prediction of Neoadjuvant Chemotherapy-Insensitive Breast Cancers

Purpose

We developed and validated a contrast-enhanced spectral mammography (CESM)-based radiomics nomogram to predict neoadjuvant chemotherapy (NAC)-insensitive breast cancers prior to treatment.

Methods

We enrolled 117 patients with breast cancer who underwent CESM examination and NAC treatment from July 2017 to April 2019. The patients were grouped randomly into a training set (n = 97) and a validation set (n = 20) in a ratio of 8:2. 792 radiomics features were extracted from CESM images including low-energy and recombined images for each patient. Optimal radiomics features were selected by using analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation, to develop a radiomics score in the training set. A radiomics nomogram incorporating the radiomics score and independent clinical risk factors was then developed using multivariate logistic regression analysis. With regard to discrimination and clinical usefulness, radiomics nomogram was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC) and decision curve analysis (DCA).

Results

The radiomics nomogram that incorporates 11 radiomics features and 3 independent clinical risk factors, including Ki-67 index, background parenchymal enhancement (BPE) and human epidermal growth factor receptor-2 (HER-2) status, showed an encouraging discrimination power with AUCs of 0.877 [95% confidence interval (CI) 0.816 to 0.924] and 0.81 (95% CI 0.575 to 0.948) in the training and validation sets, respectively. DCA revealed the increased clinical usefulness of this nomogram.

Conclusion

The proposed radiomics nomogram that integrates CESM-derived radiomics features and clinical parameters showed potential feasibility for predicting NAC-insensitive breast cancers.

Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography

BACKGROUND

The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR).

METHODS

In this retrospective evaluation of 105 patients with stage II-III breast cancer, oxy-hemoglobin (ctO₂Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2-3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO₂Hb changes across chemotherapy when corrected for pCR status, age, and BMI.

RESULTS

Patients who achieved pCR to NAC had an overall decrease of 3.88 μM for ctO₂Hb (95% CI, 1.39 to 6.37 μM), p = .004, after 2-3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 μM (95% CI, - 1.30 to 1.58 μM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO₂Hb levels with BMI and age.

CONCLUSIONS

This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2-3 weeks of chemotherapy.

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine-Learning Models

BACKGROUND

Automated measurement and classification models with objectivity and reproducibility are required for accurate evaluation of the breast cancer risk of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE).

PURPOSE

To develop and evaluate a machine-learning algorithm for breast FGT segmentation and BPE classification.

STUDY TYPE

Retrospective.

POPULATION

A total of 794 patients with breast cancer, 594 patients assigned to the development set, and 200 patients to the test set.

FIELD STRENGTH/SEQUENCE

3T and 1.5T; T₂ -weighted, fat-saturated T₁ -weighted (T₁ W) with dynamic contrast enhancement (DCE).

ASSESSMENT

Manual segmentation was performed for the whole breast and FGT regions in the contralateral breast. The BPE region was determined by thresholding using the subtraction of the pre- and postcontrast T₁ W images and the segmented FGT mask. Two radiologists independently assessed the categories of FGT and BPE. A deep-learning-based algorithm was designed to segment and measure the volume of whole breast and FGT and classify the grade of BPE.

STATISTICAL TESTS

Dice similarity coefficients (DSC) and Spearman correlation analysis were used to compare the volumes from the manual and deep-learning-based segmentations. Kappa statistics were used for agreement analysis. Comparison of area under the receiver operating characteristic (ROC) curves (AUC) and F1 scores were calculated to evaluate the performance of BPE classification.

RESULTS

The mean (±SD) DSC for manual and deep-learning segmentations was 0.85 ± 0.11. The correlation coefficient for FGT volume from manual- and deep-learning-based segmentations was 0.93. Overall accuracy of manual segmentation and deep-learning segmentation in BPE classification task was 66% and 67%, respectively. For binary categorization of BPE grade (minimal/mild vs. moderate/marked), overall accuracy increased to 91.5% in manual segmentation and 90.5% in deep-learning segmentation; the AUC was 0.93 in both methods.

DATA CONCLUSION

This deep-learning-based algorithm can provide reliable segmentation and classification results for BPE.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

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.

Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- Patients

OBJECTIVE

Women with advanced HER2- breast cancer have limited treatment options. Breast MRI functional tumor volume (FTV) is used to predict pathologic complete response (pCR) to improve treatment efficacy. In addition to FTV, background parenchymal enhancement (BPE) may predict response and was explored for HER2- patients in the I-SPY-2 TRIAL.

METHODS

Women with HER2- stage II or III breast cancer underwent prospective serial breast MRIs during four neoadjuvant chemotherapy timepoints. BPE was quantitatively calculated using whole-breast manual segmentation. Logistic regression models were systematically explored using pre-specified and optimized predictor selection based on BPE or combined with FTV.

RESULTS

A total of 352 MRI examinations in 88 patients (29 with pCR, 59 non-pCR) were evaluated. Women with hormone receptor (HR)+HER2- cancers who achieved pCR demonstrated a significantly greater decrease in BPE from baseline to pre-surgery compared to non-pCR patients (odds ratio 0.64, 95% confidence interval (CI): 0.39-0.92, P = 0.04). The associated BPE area under the curve (AUC) was 0.77 (95% CI: 0.56-0.98), comparable to the range of FTV AUC estimates. Among multi-predictor models, the highest cross-validated AUC of 0.81 (95% CI: 0.73-0.90) was achieved with combined FTV+HR predictors, while adding BPE to FTV+HR models had an estimated AUC of 0.82 (95% CI: 0.74-0.92).

CONCLUSION

Among women with HER2- cancer, BPE alone demonstrated association with pCR in women with HR+HER2- breast cancer, with similar diagnostic performance to FTV. BPE predictors remained significant in multivariate FTV models, but without added discrimination for pCR prediction. This may be due to small sample size limiting ability to create subtype-specific multivariate models.

Contralateral parenchymal enhancement on breast MRI before and during neoadjuvant endocrine therapy in relation to the preoperative endocrine prognostic index

Objectives

To investigate whether contralateral parenchymal enhancement (CPE) on MRI during neoadjuvant endocrine therapy (NET) is associated with the preoperative endocrine prognostic index (PEPI) of ER+/HER2− breast cancer.

Methods

This retrospective observational cohort study included 40 unilateral ER+/HER2− breast cancer patients treated with NET. Patients received NET for 6 to 9 months with MRI response monitoring after 3 and/or 6 months. PEPI was used as endpoint. PEPI is based on surgery-derived pathology (pT- and pN-stage, Ki67, and ER-status) and stratifies patients in three groups with distinct prognoses. Mixed effects and ROC analysis were performed to investigate whether CPE was associated with PEPI and to assess discriminatory ability.

Results

The median patient age was 61 (interquartile interval: 52, 69). Twelve patients had PEPI-1 (good prognosis), 15 PEPI-2 (intermediate), and 13 PEPI-3 (poor). High pretreatment CPE was associated with PEPI-3: pretreatment CPE was 39.4% higher on average (95% CI = 1.3, 91.9%; p = .047) compared with PEPI-1. CPE decreased after 3 months in PEPI-2 and PEPI-3. The average reduction was 24.4% (95% CI = 2.6, 41.3%; p = .032) in PEPI-2 and 29.2% (95% CI = 7.8, 45.6%; p = .011) in PEPI-3 compared with baseline. Change in CPE was predictive of PEPI-1 vs PEPI-2+3 (AUC = 0.77; 95% CI = 0.57, 0.96).

Conclusions

CPE during NET is associated with PEPI-group in ER+/HER2− breast cancer: a high pretreatment CPE and a decrease in CPE during NET were associated with a poor prognosis after NET on the basis of PEPI.

Key Points

• Change in contralateral breast parenchymal enhancement on MRI during neoadjuvant endocrine therapy distinguished between patients with a good and intermediate/poor prognosis at final pathology.

• Patients with a poor prognosis at final pathology showed higher baseline parenchymal enhancement on average compared to patients with a good prognosis.

• Patients with an intermediate/poor prognosis at final pathology showed a higher average reduction in parenchymal enhancement after 3 months of neoadjuvant endocrine therapy.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07058-3) contains supplementary material, which is available to authorized users.

Fully automatic classification of breast MRI background parenchymal enhancement using a transfer learning approach

Marked enhancement of the fibroglandular tissue on contrast-enhanced breast magnetic resonance imaging (MRI) may affect lesion detection and classification and is suggested to be associated with higher risk of developing breast cancer. The background parenchymal enhancement (BPE) is qualitatively classified according to the BI-RADS atlas into the categories "minimal," "mild," "moderate," and "marked." The purpose of this study was to train a deep convolutional neural network (dCNN) for standardized and automatic classification of BPE categories.This IRB-approved retrospective study included 11,769 single MR images from 149 patients. The MR images were derived from the subtraction between the first post-contrast volume and the native T1-weighted images. A hierarchic approach was implemented relying on 2 dCNN models for detection of MR-slices imaging breast tissue and for BPE classification, respectively. Data annotation was performed by 2 board-certified radiologists. The consensus of the 2 radiologists was chosen as reference for BPE classification. The clinical performances of the single readers and of the dCNN were statistically compared using the quadratic Cohen's kappa.Slices depicting the breast were classified with training, validation, and real-world (test) accuracies of 98%, 96%, and 97%, respectively. Over the 4 classes, the BPE classification was reached with mean accuracies of 74% for training, 75% for the validation, and 75% for the real word dataset. As compared to the reference, the inter-reader reliabilities for the radiologists were 0.780 (reader 1) and 0.679 (reader 2). On the other hand, the reliability for the dCNN model was 0.815.Automatic classification of BPE can be performed with high accuracy and support the standardization of tissue classification in MRI.

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.

Background parenchymal enhancement: behavior during neoadjuvant chemotherapy for breast cancer and relationship with a pathological complete response

Objective

To evaluate background parenchymal enhancement (BPE) and its characteristics, as well as its behavior before and after neoadjuvant chemotherapy (NAC), in both breasts of patients with unilateral breast cancer.

Materials and Methods

This was a retrospective, cross-sectional observational study involving a consecutive sample of women with invasive breast cancer who underwent breast magnetic resonance imaging (MRI) between July 2007 and July 2017, as well as undergoing dynamic contrast-enhanced MRI before and after NAC. In both breasts, we evaluated the BPE in accordance with the Breast Imaging Reporting and Data System. We applied logistic regression analysis, and values of p < 0.05 were considered significant.

Results

We evaluated 150 women. The mean age was 45.2 years (range, 20-74 years). The variables correlating independently with a high pre-NAC BPE, in the affected and contralateral breasts, were being under 50 years of age (odds ratio [OR] = 6.55; 95% confidence interval [95% CI]: 2.32-18.46, for both breasts) and a post-NAC BPE reduction (OR = 17.75; 95% CI: 4.94-63.73 and OR = 18.47; 95% CI: 5.19-66.49, respectively).

Conclusion

Patients with invasive unilateral breast cancer who have a high pre-NAC BPE in both breasts tend to be under 50 years of age and to show a post-NAC reduction in BPE.

Quantitative background parenchymal enhancement to predict recurrence after neoadjuvant chemotherapy for breast cancer

Breast background parenchymal enhancement (BPE) is an increasingly studied MRI parameter that reflects the microvasculature of normal breast tissue, which has been shown to change during neoadjuvant chemotherapy (NAC) for breast cancer. We aimed at evaluating the BPE in patients undergoing NAC and its prognostic value to predict recurrence. MRI BPE was visually and quantitatively evaluated before and after NAC in a retrospective cohort of 102 women with unilateral biopsy-proven invasive breast cancer. Pre-therapeutic BPE was not predictive of pathological response or recurrence. Quantitative post-therapeutic BPE was significantly decreased compared to pre-therapeutic value. Post-therapeutic quantitative BPE significantly predicted recurrence (HR = 6.38 (0.71, 12.06), p < 0.05).

Prophylactic breast irradiation reduces background parenchymal enhancement (BPE) on MRI: A secondary analysis

PURPOSE

We recently showed that prophylactic breast irradiation (PBI) reduces the risk of contralateral breast cancer in BRCA mutation carriers undergoing treatment for early breast cancer. It has been suggested that Background Parenchymal Enhancement (BPE) may be a biomarker for increased risk of breast cancer.

METHODS

For participants in the trial we reviewed the MRI prior to enrollment and following radiation treatment and scored the contralateral breast for BPE and density.

RESULTS

Significant reduction of BPE was more commonly noted following PBI (p = 0.011) compared to the control group.

CONCLUSION

Reduction of BPE by PBI may contribute to its prophylactic effect.

Population-Based Assessment of the Association Between Magnetic Resonance Imaging Background Parenchymal Enhancement and Future Primary Breast Cancer Risk

PURPOSE

To evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk.

PATIENTS AND METHODS

We examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression.

RESULTS

Among 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80% v 66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio [HR], 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (P = .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05).

CONCLUSION

BPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.

Background parenchymal enhancement on breast MRI: A comprehensive review

The degree of normal fibroglandular tissue that enhances on breast MRI, known as background parenchymal enhancement (BPE), was initially described as an incidental finding that could affect interpretation performance. While BPE is now established to be a physiologic phenomenon that is affected by both endogenous and exogenous hormone levels, evidence supporting the notion that BPE frequently masks breast cancers is limited. However, compelling data have emerged to suggest BPE is an independent marker of breast cancer risk and breast cancer treatment outcomes. Specifically, multiple studies have shown that elevated BPE levels, measured qualitatively or quantitatively, are associated with a greater risk of developing breast cancer. Evidence also suggests that BPE could be a predictor of neoadjuvant breast cancer treatment response and overall breast cancer treatment outcomes. These discoveries come at a time when breast cancer screening and treatment have moved toward an increased emphasis on targeted and individualized approaches, of which the identification of imaging features that can predict cancer diagnosis and treatment response is an increasingly recognized component. Historically, researchers have primarily studied quantitative tumor imaging features in pursuit of clinically useful biomarkers. However, the need to segment less well-defined areas of normal tissue for quantitative BPE measurements presents its own unique challenges. Furthermore, there is no consensus on the optimal timing on dynamic contrast-enhanced MRI for BPE quantitation. This article comprehensively reviews BPE with a particular focus on its potential to increase precision approaches to breast cancer risk assessment, diagnosis, and treatment. It also describes areas of needed future research, such as the applicability of BPE to women at average risk, the biological underpinnings of BPE, and the standardization of BPE characterization. Level of Evidence: 3 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2020;51:43-61.

Relationship between Background Parenchymal Enhancement on High-risk Screening MRI and Future Breast Cancer Risk

RATIONALE AND OBJECTIVES

To determine if background parenchymal enhancement (BPE) on screening breast magnetic resonance imaging (MRI) in high-risk women correlates with future cancer.

MATERIALS AND METHODS

All screening breast MRIs (n = 1039) in high-risk women at our institution from August 1, 2004, to July 30, 2013, were identified. Sixty-one patients who subsequently developed breast cancer were matched 1:2 by age and high-risk indication with patients who did not develop breast cancer (n = 122). Five fellowship-trained breast radiologists independently recorded the BPE. The median reader BPE for each case was calculated and compared between the cancer and control cohorts.

RESULTS

Cancer cohort patients were high-risk because of a history of radiation therapy (10%, 6 of 61), high-risk lesion (18%, 11 of 61), or breast cancer (30%, 18 of 61); BRCA mutation (18%, 11 of 61); or family history (25%, 15 of 61). Subsequent malignancies were invasive ductal carcinoma (64%, 39 of 61), ductal carcinoma in situ (30%, 18 of 61) and invasive lobular carcinoma (7%, 4of 61). BPE was significantly higher in the cancer cohort than in the control cohort (P = 0.01). Women with mild, moderate, or marked BPE were 2.5 times more likely to develop breast cancer than women with minimal BPE (odds ratio = 2.5, 95% confidence interval: 1.3-4.8, P = .005). There was fair interreader agreement (κ = 0.39).

CONCLUSIONS

High-risk women with greater than minimal BPE at screening MRI have increased risk of future breast cancer.

Changes in background parenchymal enhancement in HER2-positive breast cancer before and after neoadjuvant chemotherapy: Association with pathologic complete response

This study aimed to analyze the relationship between pathologic complete response (pCR) and changes in background parenchymal enhancement (BPE) levels in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer and who received neoadjuvant chemotherapy (NAC).The pre- and post-NAC magnetic resonance imaging results of 51 patients with confirmed unilateral HER2-positive breast cancer were retrospectively analyzed by 2 experienced radiologists. Pre- and post-NAC of contralateral BPE levels were classified into 4 categories (1 = minimal, 2 = mild, 3 = moderate, and 4 = marked). The 4 categories of BPE were defined by the visually estimated enhancement of fibroglandular tissue of the breast. Changes in BPE before and after NAC were compared between the premenopausal and postmenopausal groups and between the pCR and non-pCR groups. The associations between BPE and pCR and between BPE and tumor size were analyzed before and after NAC.Twenty-three patients achieved pCR, and 28 patients achieved non-pCR. Premenopausal patients had significantly higher baseline BPE levels than postmenopausal women (P = .023). The post-NAC BPE levels of premenopausal patients significantly decreased relative to those of postmenopausal patients (P = .027). The baseline BPE levels of the pCR group were not significantly different from those of the non-pCR group (P = .892). However, the decrease in BPE levels in the pCR group was more drastic than that in the non-pCR group (P < .001). Decreased BPE levels were directly associated with pCR and tumor size reduction (P < .05). Women with hormone receptor (HR)-negative tumors were more likely to exhibit pCR than those with HR-positive tumors (P = .007).Decreased BPE of patients with HER2-positive breast cancer may serve as an indicator of NAC effectiveness. Furthermore, women with HR-negative tumors were more likely to exhibit pCR than women with HR-positive tumors.

Background parenchymal enhancement in breast magnetic resonance imaging: A review of current evidences and future trends

Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) is a dynamic process, which varies among women and within the same woman over time due to different factors. BPE has profound implications for women with or at risk of breast cancer. Breast radiologist should be aware of factors that could potentially influence BPE and have to be familiar with its typical appearance. Marked BPE could indeed affect the diagnostic accuracy of breast MRI, but this shortcoming can be minimized through evaluation by dedicated radiologists, in order to correctly interpret and properly manage the additional findings. BPE shows promise as an imaging biomarker but many issues need to be addressed before it can be used either to determine screening strategy or the value of risk-reducing interventions. This review analyzes the clinical influence of BPE on breast MRI interpretation, breast cancer staging and surgical outcome and discusses current available evidences about BPE as an imaging biomarker.

Decreased background parenchymal enhancement of the contralateral breast after two cycles of neoadjuvant chemotherapy is associated with tumor response in HER2-positive breast cancer

Background Several recent studies have focused on the association between background parenchymal enhancement (BPE) and tumor response to neoadjuvant chemotherapy (NAC), but early prediction of tumor response based on BPE has yet not been investigated. Purpose To retrospectively investigate whether changes in the BPE of the contralateral breast following NAC could help predict tumor response in early stage HER2-positive breast cancer. Material and Methods Data from 71 patients who were diagnosed with unilateral HER2 positive breast cancer and then underwent NAC with trastuzumab before surgery were analyzed retrospectively. Two experienced radiologists independently categorized the patients' levels of BPE of the contralateral breast into four categories (1 = minimal, 2 = mild, 3 = moderate, 4 = marked) at baseline and after the second cycle of NAC. After undergoing surgery, 34 patients achieved pathologic complete response (pCR) and 37 patients had residual disease (non-pCR). The association between BPE and histopathologic tumor response was analyzed. Result The level of BPE was higher in premenopausal than post-menopausal women both at baseline and after the second cycle of NAC ( P < 0.005). A significant reduction in BPE ( P < 0.001) was observed after the second NAC cycle; however, a more obvious decrease in BPE was identified in premenopausal relative to post-menopausal women ( P = 0.041). No significant association was identified between pCR and baseline BPE ( P = 0.287). However, after the second NAC cycle, decreased BPE was significantly associated with pCR ( P = 0.003). Conclusion For HER2-positive patients, changes in BPE may serve as an additional imaging biomarker of treatment response at an early stage.

Contrast-enhanced spectral mammography in patients with MRI contraindications

Background Contrast-enhanced spectral mammography (CESM) is a novel breast imaging technique providing comparable diagnostic accuracy to breast magnetic resonance imaging (MRI). Purpose To show that CESM in patients with MRI contraindications is feasible, accurate, and useful as a problem-solving tool, and to highlight its limitations. Material and Methods A total of 118 patients with MRI contraindications were examined by CESM. Histology was obtained in 94 lesions and used as gold standard for diagnostic accuracy calculations. Imaging data were reviewed retrospectively for feasibility, accuracy, and technical problems. The diagnostic yield of CESM as a problem-solving tool and for therapy response evaluation was reviewed separately. Results CESM was more accurate than mammography (MG) for lesion categorization (r = 0.731, P < 0.0001 vs. r = 0.279, P = 0.006) and for lesion size estimation (r = 0.738 vs. r = 0.689, P < 0.0001). Negative predictive value of CESM was significantly higher than of MG (85.71% vs. 30.77%, P < 0.0001). When used for problem-solving, CESM changed patient management in 2/8 (25%) cases. Superposition artifacts and timing problems affected diagnostic utility in 3/118 (2.5%) patients. Conclusion CESM is a feasible and accurate alternative for patients with MRI contraindications, but it is necessary to be aware of the method's technical limitations.

Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: Perfusion metrics of dynamic contrast enhanced MRI

The purpose of this study was to investigate imaging parameters predicting pathologic complete response (pCR) in pretreatment dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in breast cancer patients who were treated with neoadjuvant chemotherapy (NAC). A total of 74 patients who received NAC followed by surgery were retrospectively reviewed. All patients underwent breast MRI before NAC. Perfusion parameters including Ktrans, Kep and Ve of tumor were measured three-dimensionally. These perfusion parameters of background parenchyma of contralateral breasts were analyzed two-dimensionally. Receiver-operating characteristic (ROC) analysis and multivariable logistic regression analysis were performed to compare the ability of perfusion parameters to predict pCR. Of 74 patients, 13 achieved pCR in final pathology. The fiftieth percentile and skewness of each perfusion parameter - Ktrans, Kep, and Ve of tumor were associated with pCR. Perfusion parameters of contralateral breast parenchyma in 2D analysis also showed predictive ability for pCR. The model combining perfusion parameters of contralateral breast background parenchyma and those of the tumor had higher predictive value than each single parameter. Thus, perfusion parameters of tumor, background parenchyma of contralateral breast and their combinations in pretreatment breast MRI allow early prediction for pCR of breast cancer.

Relationship between background parenchymal enhancement on breast MRI and pathological tumor response in breast cancer patients receiving neoadjuvant chemotherapy

OBJECTIVE

To evaluate the impact of background parenchymal enhancement (BPE) on breast MRI and pathological tumor responses to neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

A panel of 372 MRI from 186 pathologically confirmed breast cancer patients who underwent breast MRI before and after NAC were selected. BPE was classified into four categories before and after NAC. The association between BPE and the pathological tumor response to NAC, recurrence-free survival (RFS) and molecular subtypes were analyzed. We also evaluated the associations between the baseline BPE before NAC and menopausal status or mammographic parenchymal density.

RESULTS

Baseline BPE did not differ significantly according to the pathological tumor response to NAC (p = 0.2019). However, changes in BPE after NAC were significantly greater in the pathological complete remission (pCR) group than in the non-pCR group (p = 0.0008). There was no statistically significant association between BPE and RFS or molecular subtypes. The baseline BPE of pre-menopausal females (2.77 ± 0.86) were greater than those of post-menopausal females (2.05 ± 0.69), with statistical significance (p < 0.0001). Baseline BPE showed no significant difference according to mammographic parenchymal density.

CONCLUSION

The degree of BPE reduction in breast MRI correlates with the pathological tumor response to NAC in breast cancer patients. No significant difference in BPE was observed according to RFS or molecular subtypes of tumors. Advances in knowledge: This study suggests that the change in BPE may have potential as a biomarker of tumor response in breast cancer patients receiving NAC.

Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients

OBJECTIVES

To assess whether contralateral parenchymal enhancement reproduces as an independent biomarker for patient survival in an independent patient cohort from a different cancer institution.

METHODS

This is a HIPAA-compliant IRB approved retrospective study. Patients with ER-positive/HER2-negative operable invasive ductal carcinoma and preoperative dynamic contrast-enhanced MRI were consecutively included between 2005 and 2009. The parenchyma of the breast contralateral to known cancer was segmented automatically on MRI and contralateral parenchymal enhancement (CPE) was calculated. CPE was split into tertiles and tested for association with invasive disease-free survival (IDFS) and overall survival (OS). Propensity score analysis with inverse probability weighting (IPW) was used to adjust CPE for patient and tumour characteristics as well as systemic therapy.

RESULTS

Three hundred and two patients were included. The median age at diagnosis was 48 years (interquartile range, 42-57). Median follow-up was 88 months (interquartile range, 76-102); 15/302 (5%) patients died and 37/302 (13%) had a recurrence or died. In context of multivariable analysis, IPW-adjusted CPE was associated with IDFS [hazard ratio (HR) = 0.27, 95% confidence interval (CI) = 0.05-0.68, p = 0.004] and OS (HR = 0.22, 95% CI = 0.00-0.83, p = 0.032).

CONCLUSIONS

Contralateral parenchymal enhancement on pre-treatment dynamic contrast-enhanced MRI as an independent biomarker of survival in patients with ER-positive/HER2-negative breast cancer has been upheld in this study. These findings are a promising next step towards a practical and inexpensive test for risk stratification of ER-positive/HER2-negative breast cancer.

KEY POINTS

• High parenchymal-enhancement in the disease-free contralateral breast reproduces as biomarker for survival. • This is in patients with ER-positive/HER2-negative breast cancer from an independent cancer centre. • This is independent of patient and pathology parameters and systemic therapy.

Quantitative analysis of background parenchymal enhancement in whole breast on MRI: Influence of menstrual cycle and comparison with a qualitative analysis

OBJECTIVE

We quantitatively analyzed background parenchymal enhancement (BPE) in whole breast according to menstrual cycle and compared it with a qualitative analysis method.

MATERIALS AND METHODS

A data set of breast magnetic resonance imaging (MRI) from 273 breast cancer patients was used. For quantitative analysis, we used semiautomated in-house software with MATLAB. From each voxel of whole breast, the software calculated BPE using following equation: [(signal intensity [SI] at 1 min 30 s after contrast injection - baseline SI)/baseline SI] × 100%.

RESULTS

In total, 53 patients had minimal, 108 mild, 87 moderate, and 25 marked BPE. On quantitative analysis, mean BPE values were 33.1% in the minimal, 42.1% in the mild, 59.1% in the moderate, and 81.9% in the marked BPE group showing significant difference (p = .009 for minimal vs. mild, p < 0.001 for other comparisons). Spearman's correlation test showed that there was strong significant correlation between qualitative and quantitative BPE (r = 0.63, p < 0.001). The mean BPE value was 48.7% for patients in the first week of the menstrual cycle, 43.5% in the second week, 49% in the third week, and 49.4% for those in the fourth week. The difference between the second and fourth weeks was significant (p = .005). Median, 90th percentile, and 10th percentile values were also significantly different between the second and fourth weeks but not different in other comparisons (first vs. second, first vs. third, first vs. fourth, second vs. third, or third vs. fourth).

CONCLUSION

Quantitative analysis of BPE correlated well with the qualitative BPE grade. Quantitative BPE values were lowest in the second week and highest in the fourth week.