Background parenchymal enhancement at breast MR imaging and breast cancer risk

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.

Breast density implications and supplemental screening

Digital breast tomosynthesis (DBT) has been widely implemented in place of 2D mammography, although it is less effective in women with extremely dense breasts. Breast ultrasound detects additional early-stage, invasive breast cancers when combined with mammography; however, its relevant limitations, including the shortage of trained operators, operator dependence and small field of view, have limited its widespread implementation. Automated breast sonography (ABS) is a promising technique but the time to interpret and false-positive rates need to be improved. Supplemental screening with contrast-enhanced magnetic resonance imaging (MRI) in high-risk women reduces late-stage disease; abbreviated MRI protocols may reduce cost and increase accessibility to women of average risk with dense breasts. Contrast-enhanced digital mammography (CEDM) and molecular breast imaging improve cancer detection but require further validation for screening and direct biopsy guidance should be implemented for any screening modality. This article reviews the status of screening women with dense breasts. KEY POINTS: • The sensitivity of mammography is reduced in women with dense breasts. Supplemental screening with US detects early-stage, invasive breast cancers. • Tomosynthesis reduces recall rate and increases cancer detection rate but is less effective in women with extremely dense breasts. • Screening MRI improves early diagnosis of breast cancer more than ultrasound and is currently recommended for women at high risk. Risk assessment is needed, to include breast density, to ascertain who should start early annual MRI screening.

Impact of short-term low-dose tamoxifen on molecular breast imaging background parenchymal uptake: a pilot study

BACKGROUND

High background parenchymal uptake (BPU) on molecular breast imaging (MBI) has been identified as a breast cancer risk factor. We explored the feasibility of offering a short-term intervention of low-dose oral tamoxifen to women with high BPU and examined whether this intervention would reduce BPU.

METHODS

Women with a history of high BPU and no breast cancer history were invited to the study. Participants had an MBI exam, followed by 30 days of low-dose oral tamoxifen at either 5 mg or 10 mg/day, and a post-tamoxifen MBI exam. BPU on pre- and post-tamoxifen MBI exams was quantitatively assessed as the ratio of average counts in breast fibroglandular tissue vs. average counts in subcutaneous fat. Pre-tamoxifen and post-tamoxifen BPU were compared with paired t tests.

RESULTS

Of 47 women invited, 22 enrolled and 21 completed the study (10 taking 5 mg tamoxifen, 11 taking 10 mg tamoxifen). Mean age was 47.7 years (range 41-56 years). After 30 days low-dose tamoxifen, 8 of 21 women (38%) showed a decline in BPU, defined as a decrease from the pre-tamoxifen MBI of at least 15%; 11 of 21 (52%) had no change in BPU (within ± 15%); 2 of 21 (10%) had an increase in BPU of greater than 15%. Overall, the average post-tamoxifen BPU was not significantly different from pre-tamoxifen BPU (1.34 post vs. 1.43 pre, p = 0.11). However, among women taking 10 mg tamoxifen, 5 of 11 (45%) showed a decline in BPU; average BPU was 1.19 post-tamoxifen vs. 1.34 pre-tamoxifen (p = 0.005). In women taking 5 mg tamoxifen, 2 of 10 (20%) showed a decline in BPU; average BPU was 1.51 post-tamoxifen vs.1.53 pre-tamoxifen (p = 0.99).

CONCLUSIONS

Short-term intervention with low-dose tamoxifen may reduce high BPU on MBI for some patients. Our preliminary findings suggest that 10 mg tamoxifen per day may be more effective than 5 mg for inducing declines in BPU within 30 days. Given the variability in BPU response to tamoxifen observed among study participants, future study is warranted to determine if BPU response could predict the effectiveness of tamoxifen for breast cancer risk reduction within an individual.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02979301 . Registered 01 December 2016.

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

Background parenchymal enhancement assessment: Inter- and intra-rater reliability across breast MRI sequences

OBJECTIVE

To evaluate inter- and intra-rater reliability of background parenchymal enhancement (BPE) assessment across breast MRI sequences.

MATERIALS AND METHODS

Institutional review board approval was obtained and the requirement for consent was waived. Three radiologists qualitatively categorized BPE on 150 breast MRI using a four-point scale (minimal, mild, moderate or marked) according to BI-RADS category system. According to MR-sequence used for the assessment of BPE, inter-rater and intra-rater reliability across a simulated reading strategy with four options was performed: (1) initial contrast-enhanced (CE) fat-suppressed T1-weighted images (2) initial CE subtracted images (3) maximum-intensity-projection (MIP) of the first CE subtracted images (4) combination of initial CE fat-suppressed T1-weighted, initial CE subtracted and MIP images. Raters repeated BPE assessment of 45 breast MRI four weeks after the initial assessment. Gwet's AC1 index with ordinal weights was used to assess reliabilities.

RESULTS

Gwet's index for the reliability among the three raters was 0.68 (0.63-0.74) using initial contrast-enhanced fat-suppressed T1 weighted images, 0.74 (0.69-0.80) using subtracted images, 0.80 (0.76-0.83) using MIP, 0.80 (0.77-0.84) using a combination of the initial contrast-enhanced fat-suppressed T1 weighted, initial contrast-enhanced subtracted and MIP images. Test-retest reliability was 0.81 (0.60-1.00) for rater 1, 0.77 (0.55-0.98) for rater 2, 0.79 (0.59-0.99) for rater 3 using the combination of initial contrast-enhanced fat-suppressed T1 weighted, initial contrast-enhanced subtracted and MIP images.

CONCLUSIONS

Overall, the combination of all CE MRI images showed the highest reliability of BPE assessment. However, MIP showed a high reliability with lower reading time compared to the combination of all CE MRI images.

Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program : A retrospective cohort study

Objectives

The purpose of this study is to evaluate the predictive value of the amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE), measured at baseline on breast MRI, for breast cancer development and risk of false-positive findings in women at increased risk for breast cancer.

Methods

Negative baseline MRI scans of 1533 women participating in a screening program for women at increased risk for breast cancer between January 1, 2003, and January 1, 2014, were selected. Automated tools based on deep learning were used to obtain quantitative measures of FGT and BPE. Logistic regression using forward selection was used to assess relationships between FGT, BPE, cancer detection, false-positive recall, and false-positive biopsy.

Results

Sixty cancers were detected in follow-up. FGT was only associated to short-term cancer risk; BPE was not associated with cancer risk. High FGT and BPE did lead to more false-positive recalls at baseline (OR 1.259, p = 0.050, and OR 1.475, p = 0.003) and to more frequent false-positive biopsies at baseline (OR 1.315, p = 0.049, and OR 1.807, p = 0.002), but were not predictive for false-positive findings in subsequent screening rounds.

Conclusions

FGT and BPE, measured on baseline MRI, are not predictive for overall breast cancer development in women at increased risk. High FGT and BPE lead to more false-positive findings at baseline.

Key Points

• Amount of fibroglandular tissue is only predictive for short-term breast cancer risk in women at increased risk.

• Background parenchymal enhancement measured on baseline MRI is not predictive for breast cancer development in women at increased risk.

• High amount of fibroglandular tissue and background parenchymal enhancement lead to more false-positive findings at baseline MRI.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06020-2) contains supplementary material, which is available to authorized users.

Breast MRI background parenchymal enhancement as an imaging bridge to molecular cancer sub-type

PURPOSE

To evaluate the distribution of MRI breast parenchymal enhancement (BPE) among different breast cancer subtypes searching for any significant difference in terms of immunohistochemical and receptorial patterns (Estrogen Receptor -ER, Progesterone Receptor - PR, Human Epidermal Growth Factor Receptor 2 - HER2).

METHODS

82 consecutive patients affected by breast cancer underwent breast DCE-MRI. Two radiologists retrospectively evaluated all subtracted MR enhanced images for classifying BPE. ER, PR and HER2 expression was assessed by immunohistochemical analysis. ER and PR status was evaluated using Allred score (positive values: score ≥3). The intensity of the cerbB-2 staining was scored as 0, 1+, 2+, or 3+ (positive values: ≥ 3+; negative:0 and 1+; 2+ value assessed with silver in-situ hybridization). Patients were classified into five categories based on cancer subtypes: Luminal A, Luminal B HER2 negative, Luminal B HER2 positive, HER2 positive non luminal, triple negative. The χ2 test was used for evaluating the significance of BPE type distribution into the five groups of tumor subtypes and the distribution of the five breast cancer subtypes among every single BPE type. The correlation of BPE with factors such as age, menopausal status and lesion diameter was investigated using multivariate regression analysis and logistic regression. Cohen's kappa statistics was used in order to assess inter-observer agreement for classifying BPE.

RESULTS

6/82 cases were Luminal A-like (7.3%), 42/82 Luminal B-like (HER2-) (51.2%), 12/82 Luminal B-like (HER2+) (14.6%), 4/82 Non Luminal (HER+) (4.9%), 18/82 Triple Negative (ductal) (22%). 16/82 cases showed minimal BPE, 28/82 mild BPE, 22/82 moderate BPE, 16/82 marked BPE. Mild BPE pattern was significantly more prevalent (p = 0.0001) than other BPE types only in the luminal B (HER-) tumors. Moderate and marked BPE prevailed over minimal and mild, in triple negatives. Among all patients with mild BPE, luminal B (HER2-) tumors were significantly higher (p = 0.0001). Among all patients with marked BPE, triple negative subtypes were significantly higher (p = 0.0074). No significant confounder to BPE qualitative evaluation was found (p = 0.39). The inter-rater agreement in evaluating BPE patterns on MRI was almost perfect with Cohen's k = 0.83.

CONCLUSIONS

BPE could play a crucial role as an imaging bridge to molecular breast cancer subtype allowing an additional risk stratification in the field of breast MRI and targeted screening tests. Luminal B (HER2-) tumors could prevail in case of mild BPE on CE-MRI examinations and TN tumors in patients with marked BPE. Further studies on larger series are needed to confirm this hypothesis.

An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets

PURPOSE

Accurate segmentation of the breast is required for breast density estimation and the assessment of background parenchymal enhancement, both of which have been shown to be related to breast cancer risk. The MRI breast segmentation task is challenging, and recent work has demonstrated that convolutional neural networks perform well for this task. In this study, we have investigated the performance of several two-dimensional (2D) U-Net and three-dimensional (3D) U-Net configurations using both fat-suppressed and nonfat-suppressed images. We have also assessed the effect of changing the number and quality of the ground truth segmentations.

MATERIALS AND METHODS

We designed eight studies to investigate the effect of input types and the dimensionality of the U-Net operations for the breast MRI segmentation. Our training data contained 70 whole breast volumes of T1-weighted sequences without fat suppression (WOFS) and with fat suppression (FS). For each subject, we registered the WOFS and FS volumes together before manually segmenting the breast to generate ground truth. We compared four different input types to the U-nets: WOFS, FS, MIXED (WOFS and FS images treated as separate samples), and MULTI (WOFS and FS images combined into a single multichannel image). We trained 2D U-Nets and 3D U-Nets with these data, which resulted in our eight studies (2D-WOFS, 3D-WOFS, 2D-FS, 3D-FS, 2D-MIXED, 3D-MIXED, 2D-MULTI, and 3D-MULT). For each of these studies, we performed a systematic grid search to tune the hyperparameters of the U-Nets. A separate validation set with 15 whole breast volumes was used for hyperparameter tuning. We performed Kruskal-Walis test on the results of our hyperparameter tuning and did not find a statistically significant difference in the ten top models of each study. For this reason, we chose the best model as the model with the highest mean dice similarity coefficient (DSC) value on the validation set. The reported test results are the results of the top model of each study on our test set which contained 19 whole breast volumes annotated by three readers fused with the STAPLE algorithm. We also investigated the effect of the quality of the training annotations and the number of training samples for this task.

RESULTS

The study with the highest average DSC result was 3D-MULTI with 0.96 ± 0.02. The second highest average is 2D WOFS (0.96 ± 0.03), and the third is 2D MULTI (0.96 ± 0.03). We performed the Kruskal-Wallis one-way ANOVA test with Dunn's multiple comparison tests using Bonferroni P-value correction on the results of the selected model of each study and found that 3D-MULTI, 2D-MULTI, 3D-WOFS, 2D-WOFS, 2D-FS, and 3D-FS were not statistically different in their distributions, which indicates that comparable results could be obtained in fat-suppressed and nonfat-suppressed volumes and that there is no significant difference between the 3D and 2D approach. Our results also suggested that the networks trained on single sequence images or multiple sequence images organized in multichannel images perform better than the models trained on a mixture of volumes from different sequences. Our investigation of the size of the training set revealed that training a U-Net in this domain only requires a modest amount of training data and results obtained with 49 and 70 training datasets were not significantly different.

CONCLUSIONS

To summarize, we investigated the use of 2D U-Nets and 3D U-Nets for breast volume segmentation in T1 fat-suppressed and without fat-suppressed volumes. Although our highest score was obtained in the 3D MULTI study, when we took advantage of information in both fat-suppressed and nonfat-suppressed volumes and their 3D structure, all of the methods we explored gave accurate segmentations with an average DSC on >94% demonstrating that the U-Net is a robust segmentation method for breast MRI volumes.

Association of distant recurrence-free survival with algorithmically extracted MRI characteristics in breast cancer

BACKGROUND

While important in diagnosis of breast cancer, the scientific assessment of the role of imaging in prognosis of outcomes and treatment planning is limited.

PURPOSE

To evaluate the potential of using quantitative imaging variables for stratifying risk of distant recurrence in breast cancer patients.

STUDY TYPE

Retrospective.

POPULATION

In all, 892 female invasive breast cancer patients.

SEQUENCE

Dynamic contrast-enhanced MRI with field strength 1.5 T and 3 T.

ASSESSMENT

Computer vision algorithms were applied to extract a comprehensive set of 529 imaging features quantifying size, shape, enhancement patterns, and heterogeneity of the tumors and the surrounding tissue. Using a development set with 446 cases, we selected 20 imaging features with high prognostic value.

STATISTICAL TESTS

We evaluated the imaging features using an independent test set with 446 cases. The principal statistical measure was a concordance index between individual imaging features and patient distant recurrence-free survival (DRFS).

RESULTS

The strongest association with DRFS that persisted after controlling for known prognostic clinical and pathology variables was found for signal enhancement ratio (SER) partial tumor volume (concordance index [C] = 0.768, 95% confidence interval [CI]: 0.679-0.856), tumor major axis length (C = 0.742, 95% CI: 0.650-0.834), kurtosis of the SER map within tumor (C = 0.640, 95% CI: 0.521-0.760), tumor cluster shade (C = 0.313, 95% CI: 0.216-0.410), and washin rate information measure of correlation (C = 0.702, 95% CI: 0.601-0.803).

DATA CONCLUSION

Quantitative assessment of breast cancer features seen in a routine breast MRI might be able to be used for assessment of risk of distant recurrence.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2019.

Assessment of Quantitative Magnetic Resonance Imaging Background Parenchymal Enhancement Parameters to Improve Determination of Individual Breast Cancer Risk

OBJECTIVES

The aims of this study were to identify optimal quantitative breast magnetic resonance imaging background parenchymal enhancement (BPE) parameters associated with breast cancer risk and compare performance to qualitative assessments.

METHODS

Using a matched case-control cohort of 46 high-risk women who underwent screening magnetic resonance imaging (23 who developed breast cancer matched to 23 who did not), fibroglandular tissue area, BPE area, and intensity metrics (mean, SD, quartiles, skewness, and kurtosis) were quantitatively measured at varying enhancement thresholds. Optimal thresholds for discriminating between cancer and control cohorts were identified for each metric and performance summarized using area under the receiver operating characteristic curve.

RESULTS

Women who developed breast cancer exhibited greater BPE area (adjusted P = 0.004) and higher intensity statistics (adjusted P < 0.004, except skewness and kurtosis with P > 0.99) than did control subjects, with areas under the receiver operating characteristic curve ranging from 0.75 to 0.78 at optimized thresholds.

CONCLUSIONS

Elevated quantitative BPE parameters, related to both area and intensity of enhancement, are associated with breast cancer development.

Multimodality Imaging of Breast Parenchymal Density and Correlation with Risk Assessment

Purpose of Review

Breast density, or the amount of fibroglandular tissue in the breast, has become a recognized and independent marker for breast cancer risk. Public awareness of breast density as a possible risk factor for breast cancer has resulted in legislation for risk stratification purposes in many US states. This review will provide a comprehensive overview of the currently available imaging modalities for qualitative and quantitative breast density assessment and the current evidence on breast density and breast cancer risk assessment.

Recent Findings

To date, breast density assessment is mainly performed with mammography and to some extent with magnetic resonance imaging. Data indicate that computerized, quantitative techniques in comparison with subjective visual estimations are characterized by higher reproducibility and robustness.

Summary

Breast density reduces the sensitivity of mammography due to a masking effect and is also a recognized independent risk factor for breast cancer. Standardized breast density assessment using automated volumetric quantitative methods has the potential to be used for risk prediction and stratification and in determining the best screening plan for each woman.

Machine learning-based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high-risk screening MRI

BACKGROUND

Preliminary work has demonstrated that background parenchymal enhancement (BPE) assessed by radiologists is predictive of future breast cancer in women undergoing high-risk screening MRI. Algorithmically assessed measures of BPE offer a more precise and reproducible means of measuring BPE than human readers and thus might improve the predictive performance of future cancer development.

PURPOSE

To determine if algorithmically extracted imaging features of BPE on screening breast MRI in high-risk women are associated with subsequent development of cancer.

STUDY TYPE

Case-control study.

POPULATION

In all, 133 women at high risk for developing breast cancer; 46 of these patients developed breast cancer subsequently over a follow-up period of 2 years.

FIELD STRENGTH/SEQUENCE

5 T or 3.0 T T₁ -weighted precontrast fat-saturated and nonfat-saturated sequences and postcontrast nonfat-saturated sequences.

ASSESSMENT

Automatic features of BPE were extracted with a computer algorithm. Subjective BPE scores from five breast radiologists (blinded to clinical outcomes) were also available.

STATISTICAL TESTS

Leave-one-out crossvalidation for a multivariate logistic regression model developed using the automatic features and receiver operating characteristic (ROC) analysis were performed to calculate the area under the curve (AUC). Comparison of automatic features and subjective features was performed using a generalized regression model and the P-value was obtained. Odds ratios for automatic and subjective features were compared.

RESULTS

The multivariate model discriminated patients who developed cancer from the patients who did not, with an AUC of 0.70 (95% confidence interval: 0.60-0.79, P < 0.001). The imaging features remained independently predictive of subsequent development of cancer (P < 0.003) when compared with the subjective BPE assessment of the readers.

DATA CONCLUSION

Automatically extracted BPE measurements may potentially be used to further stratify risk in patients undergoing high-risk screening MRI.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:456-464.

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.

Developing global image feature analysis models to predict cancer risk and prognosis

In order to develop precision or personalized medicine, identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest recently. Most of these research approaches use the similar concepts of the conventional computer-aided detection schemes of medical images, which include steps in detecting and segmenting suspicious regions or tumors, followed by training machine learning models based on the fusion of multiple image features computed from the segmented regions or tumors. However, due to the heterogeneity and boundary fuzziness of the suspicious regions or tumors, segmenting subtle regions is often difficult and unreliable. Additionally, ignoring global and/or background parenchymal tissue characteristics may also be a limitation of the conventional approaches. In our recent studies, we investigated the feasibility of developing new computer-aided schemes implemented with the machine learning models that are trained by global image features to predict cancer risk and prognosis. We trained and tested several models using images obtained from full-field digital mammography, magnetic resonance imaging, and computed tomography of breast, lung, and ovarian cancers. Study results showed that many of these new models yielded higher performance than other approaches used in current clinical practice. Furthermore, the computed global image features also contain complementary information from the features computed from the segmented regions or tumors in predicting cancer prognosis. Therefore, the global image features can be used alone to develop new case-based prediction models or can be added to current tumor-based models to increase their discriminatory power.

Diagnostic Value of Contrast-Enhanced Digital Mammography versus Contrast-Enhanced Magnetic Resonance Imaging for the Preoperative Evaluation of Breast Cancer

Purpose

This study aimed to compare the diagnostic performance of contrast-enhanced digital mammography (CEDM) and contrast-enhanced magnetic resonance imaging (CEMRI) in preoperative evaluations, and to evaluate the effect of each modality on the surgical management of women with breast cancer.

Methods

This single-center, prospective study was approved by the Institutional Review Board, and informed consent was obtained from all patients. From November 2016 to October 2017, 84 patients who were diagnosed with invasive carcinoma (69/84) and ductal carcinoma in situ (15/84), and underwent both CEDM and CEMRI, were enrolled. Imaging findings and surgical management were correlated with pathological results and compared. The diagnostic performance of both modalities in the detection of index and secondary cancers (multifocality and multicentricity), and occult cancer in the contralateral breast, was compared. The authors also evaluated whether CEDM or CEMRI resulted in changes in the surgical management of the affected breast due to imaging-detected findings.

Results

Eighty-four women were included in the analysis. Compared with CEMRI, CEDM demonstrated a similar sensitivity (92.9% [78/84] vs. 95.2% [80/84]) in detecting index cancer (p=0.563). For the detection of secondary cancers in the ipsilateral breast and occult cancer in the contralateral breast, no significant differences were found between CEDM and CEMRI (p=0.999 and p=0.999, respectively). Regarding changes in surgical management, CEDM resulted in similar changes compared with CEMRI (30.9% [26/84] vs. 29.7% [25/84], p=0.610). Regarding changes in surgical management due to false-positive findings, no significant differences were found between CEDM and CEMRI (34.6% [9/26] vs. 44.0% [11/25], p=0.782).

Conclusion

CEDM demonstrated a diagnostic performance comparable with CEMRI in depicting index cancers, secondary cancers, and occult cancer in the contralateral breast. CEDM demonstrated similar changes in surgical management compared with CEMRI.

Dedicated Breast Gamma Camera Imaging and Breast PET: Current Status and Future Directions

Recent advances in nuclear medicine instrumentation have led to the emergence of improved molecular imaging techniques to image breast cancer: dedicated gamma cameras using γ-emitting ^99mTc-sestamibi and breast-specific PET cameras using ¹⁸F-fluorodeoxyglucose. This article focuses on the current role of such approaches in the clinical setting including diagnosis, assessing local extent of disease, monitoring response to therapy, and, for gamma camera imaging, possible supplemental screening in women with dense breasts. Barriers to clinical adoption and technologies and radiotracers under development are also discussed.

Role of contrast-enhanced spectral mammography in the post biopsy management of B3 lesions: Preliminary results

PURPOSE

To evaluate the role of contrast-enhanced spectral mammography (CESM) in the post biopsy management of breast lesions classified as lesions of uncertain malignant potential (B3) by core needle biopsy and vacuum-assisted biopsy (VAB).

METHODS

The local ethics committee approved this retrospective study and for this type of study formal consent is not required. A total of 42 B3 lesions in 40 women aged 41-77 years were included in our study. All patients underwent CESM 2-3 weeks after the biopsy procedure and surgical excision was subsequently performed within 60 days of the CESM procedure. Three radiologists reviewed the images independently. The results were then compared with histologic findings.

RESULTS

The sensitivity, specificity, and positive and negative predictive values for confirmed demonstration of malignancy at CESM were 33.3%, 87.2%, 16.7%, and 94.4% for reader 1; 66.7%, 76.9%, 18.2%, and 96.7% for reader 2; 66.7%, 74.4%, 16.7%, and 96.7% for reader 3. Overall agreement on detection of malignant lesions using CESM among readers ranged from moderate to substantial (κ = .451-.696), for categorization of BPE from moderate to substantial (κ = .562-.711), and for evaluation of lesion intensity enhancement from fair to moderate (κ = .346-.459).

CONCLUSION

In cases of Breast Imaging Reporting and Data System (BI-RADS) 1, BI-RADS 2, or BI-RADS 3 results at CESM, follow-up or VAB rather than surgical biopsy might be performed.

Preliminary analysis: Background parenchymal 18F-FDG uptake in breast cancer patients appears to correlate with background parenchymal enhancement and to vary by distance from the index cancer

PURPOSE

To investigate how breast parenchymal uptake (BPU) of 18F-FDG on positron emission tomography/ magnetic resonance imaging (PET/MRI) in patients with breast cancer is related to background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and age, as well as whether BPU varies as a function of distance from the primary breast cancer.

MATERIALS AND METHODS

In this institutional review board (IRB)-approved retrospective study, 40 patients (all female, ages 32-80 years, mean 52 years) gave informed consent prior to undergoing contrast enhanced breast PET/MRI from 3/2015 to 2/2018. Of the 40 patients, 6 were excluded for multicentric or bilateral cancers, 1 for current lactation and 6 because the raw data from their scans were corrupted. The remaining 27 patients (all female, ages 33 to 80 years, mean age 53 years) comprised the study population. Prone PET and contrast-enhanced MR data were acquired simultaneously on a 3-T integrated PET/ MR system. BPU was measured as SUVmax of a 1.5 cm³ volume of interest 1) in the same quadrant of the ipsilateral breast, 5 mm from the index lesion; 2) in the opposite quadrant of the ipsilateral breast; and 3) in contralateral breast, quadrant matched to the opposite quadrant of the ipsilateral breast. The maximum standardized uptake value (SUVmax) of the index cancer was measured using a VOI that included the entire volume of the index lesion. Bleed from the primary tumor was corrected for (PET edge, MIM). FGT and BPE was assessed by 2 readers on a 4-point scale in accordance with BI-RADS lexicon. The Wilcoxon signed rank test and the Spearman rank correlation test were performed.

RESULTS

BPU was significantly greater in the same quadrant as the breast cancer as compared with the opposite quadrant of the same breast (p < 0.001 for both readers) and was significantly greater in the opposite quadrant of the same breast compared to the matched quadrant of the contralateral breast (p = 0.002 for reader 1 and <0.001 for reader 2). While the FGT SUVmax in the same quadrant as the cancer correlated significantly with SUVmax of the index lesion, the FGT SUVmax in the opposite quadrant of the same breast and in the matched quadrant of the contralateral breast did not. The FGT SUVmax in the contralateral breast positively correlated with the degree of BPE and negatively correlated with age, but did not show a significant correlation with the amount of FGT for either reader.

CONCLUSION

There appears to be an inverse correlation between metabolic activity of normal breast parenchyma and distance from the index cancer. BPU significantly correlates with BPE.

Role of texture analysis in breast MRI as a cancer biomarker: A review

Breast cancer is a known heterogeneous disease. Current clinically utilized histopathologic biomarkers may undersample tumor heterogeneity, resulting in higher rates of misdiagnosis for breast cancer. MRI can provide a whole-tumor sampling of disease burden and is widely utilized in clinical care. Texture analysis can provide a localized description of breast cancer, with particular emphasis on quantifying breast lesion heterogeneity. The object of this review is to provide an overview of texture analysis applications towards breast cancer diagnosis, prognosis, and treatment response evaluation and review the role of image-based texture features as noninvasive prognostic and predictive biomarkers. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:927-938.

Background parenchymal enhancement and fibroglandular tissue on breast MRI in women with high genetic risk: Are changes before and after risk-reducing salpingo-oophorectomy associated with breast cancer risk?

BACKGROUND

Parenchymal enhancement and fibroglandular tissue on breast MRI in women with high genetic risk: are changes before and after risk-reducing salpingo-oophorectomy associated with breast cancer risk?

OBJECTIVE

To evaluate changes in the level of background parenchymal enhancement (BPE) and amount of fibroglandular tissue (FGT) on breast MRI before and after risk-reducing oophorectomy (RRSO), and to determine whether these changes correlate with ultimate breast cancer risk.

MATERIALS AND METHODS

The cohort included 146 women with high genetic risk who had undergone pre- and post-RRSO breast MRI. BPE level and FGT amount were retrospectively graded according to BI-RADS classification. Initial values and changes were compared in women with or without later breast cancer after RRSO. Hazard ratios (HR) were estimated using Cox univariate models.

RESULTS

Patients with initial moderate (BI-RADS C category) BPE had a higher risk of subsequent breast cancer of HR = 3.9 (95% CI [1.1-14.3]; p = 0.04) compared to patients with initial minimal (BI-RADS A) BPE. A categorical BPE decrease after RRSO, versus no change, was associated with a higher cancer risk (HR 2.2, 95% CI [1.04-4.8]; p = 0.04). Initially dense (BI-RADS 3 category) FGT correlated with an increased cancer risk compared to fatty (BI-RADS 1 category) parenchyma (HR 8.3, 95% CI [1.1-64]; p = 0.04). After RRSO, there was a trend for higher cancer risk related to a categorical FGT decrease (HR 2.3, 95% CI [0.9-35.4]; p = 0.06).

CONCLUSION

Patients in whom BPE decreases after RRSO might be at higher risk of subsequent breast cancer compared to patients with stable BPE. This finding is consistent with the concept of increased risk associated with high initial BPE, which could be of higher clinical relevance than post-RRSO BPE reduction. A similar trend was observed with high initial FGT.

Abbreviated MRI Protocols in Breast Cancer Diagnostics

Oncologic imaging focused on the detection of breast cancer is of increasing importance, with over 1.7 million new cases detected each year worldwide. MRI of the breast has been described to be one of the most sensitive imaging modalities in breast cancer detection; however, clinical use is limited due to high costs. In the past, the objective and clinical routine of oncologic imaging was to provide one extended imaging protocol covering all potential needs and clinical implications regardless of the specific clinical indication or question. Future protocols might be more focused according to a "keep it short and simple" approach, with a reduction of patient magnet time and a limited number of images to review. Rather than replacing conventional full-diagnostic breast MRI protocols, these approaches aim at introducing a new thinking in oncologic imaging using a diversification of available imaging approaches targeted to the dedicated clinical needs of the individual patient. Here we review current approaches on using abbreviated protocols that aim to increase the clinical availability and use of breast MRI for improved early detection of breast cancer. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:647-658.

Use of Breast-Specific PET Scanners and Comparison with MR Imaging

The goals of this article are to discuss the role of breast-specific PET imaging of women with breast cancer, compare the clinical performance of positron emission mammography (PEM) and MR imaging for current indications, and provide recommendations for when women should undergo PEM instead of breast MR imaging.

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.

Patient-based 4D digital breast phantom for perfusion contrast-enhanced breast CT imaging

Purpose

The purpose of this study was to develop a realistic patient‐based 4D digital breast phantom including time‐varying contrast enhancement for simulation of dedicated breast CT perfusion imaging.

Methods

A 3D static phantom is first created by segmenting a breast CT image from a healthy patient into skin, fibroglandular tissue, adipose tissue, and vasculature. For the creation of abnormal cases, a breast lesion model was developed and can be added to the phantom. After defining the necessary perfusion parameters for each tissue (e.g., arterial input function for vasculature, blood volume and blood flow for the other normal tissues) based on contrast‐enhanced dynamic breast MRI data, the corresponding time‐enhancement curves are computed for each voxel in the phantom, according to tissue type. These curves are calculated by convolution between the arterial input function and a shifted exponential function. This exponential depends on the perfusion parameters associated with each tissue voxel, and, to incorporate normal biological variability, a uniform random distribution is used to vary the perfusion parameters on a voxel‐basis. Finally, a 4D array is produced by sampling the continuous time‐enhancement curves at the desired sampling rate. Beside modeling different enhancement dynamics according to the given input perfusion parameters, the phantom also includes the possibility to realistically simulate different spatial enhancement patterns for the breast parenchyma, taking into account the arterial sources supplying the breast. Finally, different patterns of contrast medium uptake can also be simulated for the tumor models (homogeneous and rim enhancement).

Results

As an example, a typical 4D phantom has dimensions of 426 × 421 × 260 × 559 (x, y, z, t), with a voxel size of 273 μm and a sampling time of 1 s. The characteristics of the tumor model can be modified at will to evaluate perfusion in different types of breast lesions. Results show the expected enhancement of tissues, consistent with the given input parameters. Moreover, the tumor models evaluated in this work show different enhancement dynamics according to the tumor type (defined by different input perfusion parameters), and also present a higher enhancement compared to the other healthy tissues, as expected.

Conclusions

The proposed digital phantom can model the breast tissue perfusion during 4D breast CT image acquisition, displaying the different enhancement dynamics that could be found in a real patient breast. This phantom can be used during the development of dynamic contrast‐enhanced dedicated breast CT imaging, for optimization of image acquisition, image reconstruction, and image analysis. This modality could provide functional information of the breast, resulting in detection, diagnosis, and treatment improvements of breast cancer with breast CT.

Histopathologic characteristics of background parenchymal enhancement (BPE) on breast MRI

PURPOSE

Breast fibroglandular tissue (FGT), as visualized on a mammogram (mammographic density, MD), is one of the strongest known risk factors for breast cancer. FGT is also visible on breast MRI, and increased background parenchymal enhancement (BPE) in the FGT has been identified as potentially a major breast cancer risk factor. The aim of this exploratory study was to examine the biologic basis of BPE.

METHODS

We examined the unaffected contra-lateral breast of 80 breast cancer patients undergoing a prophylactic mastectomy before any treatment other than surgery of their breast cancer. BPE was classified on the BI-RADS scale (minimal/mild/moderate/marked). Slides were stained for microvessel density (MVD), CD34 (another measure of endothelial density), glandular tissue within the FGT and VEGF. Spearman correlations were used to evaluate the associations between BPE and these pathologic variables.

RESULTS

In pre-menopausal patients, BPE was highly correlated with MVD, CD34 and glandular concentration within the FGT, and the pathologic variables were themselves highly correlated. The expression of VEGF was effectively confined to terminal duct lobular unit (TDLU) epithelium. The same relationships of the four pathologic variables with BPE were seen in post-menopausal patients, but the relationships were much weaker and not statistically significant.

CONCLUSION

The strong correlation of BPE and MVD together with the high correlation of MVD with glandular concentration seen in pre-menopausal patients indicates that increased breast cancer risk associated with BPE in pre-menopausal women is likely to result from its association with increased concentration of glandular tissue in the FGT. The effective confinement of VEGF expression to the TDLUs shows that the signal for MVD growth arises directly from the glandular tissue. Further studies are needed to understand the basis of BPE in post-menopausal women.

Comparison of background parenchymal enhancement and fibroglandular density at breast magnetic resonance imaging between BRCA gene mutation carriers and non-carriers

OBJECTIVE

High background parenchymal enhancement and amount of fibroglandular tissue on breast magnetic resonance imaging are related to increased breast cancer risk. This study sought to compare these parameters between BRCA mutation carriers and non-carriers and to evaluate the potential implications of the findings for short term follow-up.

MATERIALS AND METHODS

Magnetic resonance imaging studies of known BRCA mutation carriers, were compared to age-matched non-carrier studies performed in the same center during the same period. The groups were compared for qualitative background parenchymal enhancement and amount of fibroglandular tissue using the Breast Imaging Reporting and Data System (BI-RADS).

RESULTS

Breast parenchymal enhancement was high in up to one-third of the cohort: 22% of carriers and 33% of controls (p = 0.013). These results were sustained on separate analysis of menstrual-cycle-timed examinations. Amount of fibroglandular tissue was high in most cases: 62% of carriers and 75% of controls (p = 0.004). A BI-RADS final assessment score of 3 was more common in patients with high parenchymal enhancement, especially controls.

CONCLUSION

BRCA mutation carriers demonstrated lower levels of breast parenchymal enhancement and amount of fibroglandular tissue than age-matched non-carriers. These differences are probably influenced by hormonal status, as well as highlight different risks in distinctive subgroups of breast cancer (hormone-enriched, mutation-associated defective DNA damage repair), affecting considerations of preventive medical treatment. Differences in the indications for imaging between the carrier and non-carrier groups (screening for mutations and breast cancer evaluation, respectively) probably accounted for the higher rate of BI-RADS 3 in the control group.

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.

A Gradient-Based Approach for Breast DCE-MRI Analysis

Breast cancer is the main cause of female malignancy worldwide. Effective early detection by imaging studies remains critical to decrease mortality rates, particularly in women at high risk for developing breast cancer. Breast Magnetic Resonance Imaging (MRI) is a common diagnostic tool in the management of breast diseases, especially for high-risk women. However, during this examination, both normal and abnormal breast tissues enhance after contrast material administration. Specifically, the normal breast tissue enhancement is known as background parenchymal enhancement: it may represent breast activity and depends on several factors, varying in degree and distribution in different patients as well as in the same patient over time. While a light degree of normal breast tissue enhancement generally causes no interpretative difficulties, a higher degree may cause difficulty to detect and classify breast lesions at Magnetic Resonance Imaging even for experienced radiologists. In this work, we intend to investigate the exploitation of some statistical measurements to automatically characterize the enhancement trend of the whole breast area in both normal and abnormal tissues independently from the presence of a background parenchymal enhancement thus to provide a diagnostic support tool for radiologists in the MRI analysis.

Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter-reader variability in annotating tumors

PURPOSE

To review features used in MRI radiomics of breast cancer and study the inter-reader stability of the features.

METHODS

We implemented 529 algorithmic features that can be extracted from tumor and fibroglandular tissue (FGT) in breast MRIs. The features were identified based on a review of the existing literature with consideration of their usage, prognostic ability, and uniqueness. The set was then extended so that it comprehensively describes breast cancer imaging characteristics. The features were classified into 10 groups based on the type of data used to extract them and the type of calculation being performed. For the assessment of inter-reader variability, four fellowship-trained readers annotated tumors on preoperative dynamic contrast-enhanced MRIs for 50 breast cancer patients. Based on the annotations, an algorithm automatically segmented the image and extracted all features resulting in one set of features for each reader. For a given feature, the inter-reader stability was defined as the intraclass correlation coefficient (ICC) computed using the feature values obtained through all readers for all cases.

RESULTS

The average inter-reader stability for all features was 0.8474 (95% CI: 0.8068-0.8858). The mean inter-reader stability was lower for tumor-based features (0.6348, 95% CI: 0.5391-0.7257) than FGT-based features (0.9984, 95% CI: 0.9970-0.9992). The feature group with the highest inter-reader stability quantifies breast and FGT volume. The feature group with the lowest inter-reader stability quantifies variations in tumor enhancement.

CONCLUSIONS

Breast MRI radiomics features widely vary in terms of their stability in the presence of inter-reader variability. Appropriate measures need to be taken for reducing this variability in tumor-based radiomics.

Role of dynamic contrast-enhanced MRI in evaluating the association between contralateral parenchymal enhancement and survival outcome in ER-positive, HER2-negative, node-negative invasive breast cancer

BACKGROUND

Background parenchymal enhancement (BPE) on dynamic contrast-enhanced (DCE)-MRI has been associated with breast cancer risk, both based on qualitative and quantitative assessments.

PURPOSE

To investigate whether BPE of the contralateral breast on preoperative DCE-MRI is associated with therapy outcome in ER-positive, HER2-negative, node-negative invasive breast cancer.

STUDY TYPE

Retrospective.

POPULATION

In all, 289 patients with unilateral ER-positive, HER2-negative, node-negative breast cancer larger than 5 mm.

FIELD STRENGTH/SEQUENCE

3T, T₁ -weighted DCE sequence.

ASSESSMENT

BPE of the contralateral breast was assessed qualitatively by two dedicated radiologists and quantitatively (using region-of-interest and automatic breast segmentation).

STATISTICAL TESTS

Cox regression analysis was used to determine associations with recurrence-free survival (RFS) and distant metastasis-free survival (DFS). Interobserver variability for parenchymal enhancement was assessed using kappa statistics and intraclass correlation coefficient (ICC).

RESULTS

The median follow-up time was 75.8 months. Multivariate analysis showed receipt of total mastectomy (hazard ratio [HR]: 5.497) and high Ki-67 expression level (HR: 5.956) were independent factors associated with worse RFS (P < 0.05). Only a high Ki-67 expression level was associated with worse DFS (HR: 3.571, P = 0.045). BPE assessments were not associated with outcome (RFS [qualitative BPE: P = 0.75, 0.92 for readers 1 and 2; quantitative BPE: P = 0.38-0.99], DFS, [qualitative BPE: P = 0.41, 0.16 for readers 1 and 2; quantitative BPE: P = 0.68-0.99]). For interobserver variability, there was good agreement between qualitative (κ = 0.700) and good to perfect agreement for most quantitative parameters of BPE.

DATA CONCLUSION

Contralateral BPE showed no association with survival outcome in patients with ER-positive, HER2-negative, node-negative invasive breast cancer. A high Ki-67 expression level was associated with both worse recurrence-free and distant metastasis-free survival.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:1678-1689.

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.

Evaluation of association between degree of background parenchymal enhancement on MRI and breast cancer subtype

PURPOSE

Evaluate possible association between BPE and breast cancer tumor type/prognostic markers.

METHODS

IRB approved retrospective study from 1/2010-1/2014 identified 328 patients who had breast MRI and available clinical/pathology data. BPE was categorized according to BI-RADS. The association between BPE and breast cancer molecular subtype/prognostic factors was evaluated.

RESULTS

No significant association was present between high BPE and the following: HER2+ tumors, basal tumors, tumors with axillary nodal disease, high nuclear grade tumors, high Ki-67 index tumors or larger tumors.

CONCLUSION

Patients with high BPE may be at increased risk for breast cancer but not necessarily for those cancer subtypes with a poor prognosis.

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.

The Assessment of Background Parenchymal Enhancement (BPE) in a High-Risk Population: What Causes BPE?

OBJECTIVE

To investigate promoting factors for background parenchymal enhancement (BPE) in MR mammography (MRM).

METHODS

146 patients were retrospectively evaluated, including 91 high-risk patients (50 BRCA patients, 41 patients with elevated lifetime risk). 56 screening patients were matched to the high-risk cases on the basis of age. The correlation of BPE with factors such as fibroglandular tissue (FGT), age, menopausal status, breast cancer, high-risk precondition as well as motion were investigated using linear regression.

RESULTS

BPE positively correlated with FGT (P<.001) and negatively correlated with menopausal status (P<.001). Cancer did not show an effect on BPE (P>.05). A high-risk precondition showed a significant impact on the formation of BPE (P<.05). However, when corrected for motion, the correlation between BPE and a high-risk precondition became weak and insignificant, and a highly significant association between BPE and motion was revealed (P<.01).

CONCLUSION

BPE positively correlated with FGT and negatively correlated with age. Cancer did not have an effect on BPE. A high-risk precondition appears to have a negative effect on BPE. However, when corrected for motion, high-risk preconditions became insignificant. Technical as well as physiological influences seem to play an important role in the formation of BPE.

Association of preoperative breast MRI features with locoregional recurrence after breast conservation therapy

Background Locoregional recurrence (LRR) following breast conservation therapy (BCT) is associated with an increased risk of distant metastasis and death in patients with breast cancer. Purpose To investigate whether preoperative breast magnetic resonance imaging (MRI) features are associated with the risk of LRR in patients undergoing BCT. Material and Methods A total of 3781 women with primary invasive breast cancer underwent preoperative MRI and BCT between 2003 and 2013. Forty-eight patients who developed LRR comprised the LRR cohort and one-to-one matching (age, tumor stage, grade, and axillary nodal status) of each patient to a control participant was performed in patients who did not develop recurrence. Three readers independently reviewed MR images of the index cancer and the presence of multifocal disease was assessed. Χ² analysis was used to compare imaging and clinical features between LRR and control cohorts, with multivariate logistic regression analysis used to identify independent features. Results Significant differences were found in the proportion of multifocal disease ( P = 0.001), background parenchymal enhancement level ( P = 0.007), and breast cancer molecular subtype ( P = 0.01) between LRR and control cohorts. Multivariate analysis showed that multifocal disease (odds ratio [OR] = 11.9; 95% confidence interval [CI] = 1.4-102.5; P = 0.02) and human epidermal growth factor receptor 2-positive subtype (OR = 12.7; 95% CI = 1.3-127.6; P = 0.03) were both independently associated with LRR. Conclusion Multifocal disease on preoperative breast MRI may indicate an increased risk of LRR in patients treated with BCT.

MRI background parenchymal enhancement, breast density and serum hormones in postmenopausal women

Background parenchymal enhancement (BPE) is the degree to which normal breast tissue enhances on contrast-enhanced magnetic resonance imaging (MRI). MRI-density is a volumetric measure of breast density that is highly correlated with mammographic density, an established breast cancer risk factor. Endogenous estrogen concentrations are positively associated with postmenopausal breast cancer risk and BPE has been shown to be sensitive to hormonal exposures. The objective of our study was to examine the relationship between BPE and MRI-density and serum hormone concentrations in postmenopausal women. This was a study of cancer-free postmenopausal women undergoing contrast-enhanced breast MRI (N = 118). At the time of MRI all women completed a self-administered questionnaire and blood samples were collected for hormone analyses. Serum concentrations of estrone (E1), estradiol (E2) and bioavailable E2 were examined by category of BPE and MRI-density. Compared to women with "minimal" BPE, those who had "marked" BPE had significantly higher serum concentrations of E1, E2 and bioavailable E2 (90% increase, p_trend across all categories = 0.001; 150% increase, p_trend  = 0.001; and 158% increase, p_trend  = 0.001, respectively). These associations were only affected to a minor extent by adjustment for BMI and other variables. After adjustment for BMI, no significant associations between MRI-density and serum E1, E2 and bioavailable E2 were observed. Serum estrogen concentrations were significantly positively associated with BPE. Our study provides further evidence of the hormone-sensitive nature of BPE, indicating a potential role for BPE as an imaging marker of endogenous and exogenous hormonal exposures in the breast.

Quantitative assessment of background parenchymal enhancement in breast magnetic resonance images predicts the risk of breast cancer

The objective of this study was to evaluate the association betweenthe quantitative assessment of background parenchymal enhancement rate (BPER) and breast cancer. From 14,033 consecutive patients who underwent breast MRI in our center, we randomly selected 101 normal controls. Then, we selected 101 women with benign breast lesions and 101 women with breast cancer who were matched for age and menstruation status. We evaluated BPER at early (2 minutes), medium (4 minutes) and late (6 minutes) enhanced time phases of breast MRI for quantitative assessment. Odds ratios (ORs) for risk of breast cancer were calculated using the receiver operating curve. The BPER increased in a time-dependent manner after enhancement in both premenopausal and postmenopausal women. Premenopausal women had higher BPER than postmenopausal women at early, medium and late enhanced phases. In the normal population, the OR for probability of breast cancer for premenopausal women with high BPER was 4.1 (95% CI: 1.7–9.7) and 4.6 (95% CI: 1.7–12.0) for postmenopausal women. The OR of breast cancer morbidity in premenopausal women with high BPER was 2.6 (95% CI: 1.1–6.4) and 2.8 (95% CI: 1.2–6.1) for postmenopausal women. The BPER was found to be a predictive factor of breast cancer morbidity. Different time phases should be used to assess BPER in premenopausal and postmenopausal women.

The role of breast tomosynthesis in a predominantly dense breast population at a tertiary breast centre: breast density assessment and diagnostic performance in comparison with MRI

Objectives

To compare breast density measured on digital breast tomosynthesis (DBT) (BI-RADS-based breast composition and fully-automatic estimation) and magnetic resonance imaging (MRI) (BI-RADS amount of fibroglandular tissue), and to evaluate the diagnostic performance in terms of sensitivity and specificity of DBT and MRI in a predominantly dense breast population.

Methods

Between 2015 and 2016, 152 women with 103 breast malignancies, who underwent 3-T breast MRI and DBT within 2 months’ time, were enrolled in this study. Breast composition/fibroglandular tissue and findings on DBT (two readers) and MRI were reported using BI-RADS 5th edition. Digital mammography images were analysed for breast percent density (PD) using the Libra software tool.

Results

A majority of women had dense breasts as categorised by breast composition c (heterogeneously dense) (68%) and d (extremely dense) (15%). The mean PD was 44% (range, 18-89%) and the correlation between breast composition and PD was r = 0.6. The diagnostic performance of MRI was significantly higher compared to DBT for one reader as described by the area under the receiver operating characteristic (ROC) curve (p = 0.004) and of borderline significance for the other reader (p = 0.052).

Conclusions

MRI had higher diagnostic performance than DBT in a dense breast population in the tertiary setting.

Key Points

• MRI had higher diagnostic performance than DBT in a dense breast population

• Diagnostic performance of DBT was comparable to MRI in women with fatty breasts

• MRI was superior to DBT in preoperative breast cancer size assessment

The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers

PURPOSE

Higher background parenchymal enhancement (BPE) could be used for stratification of MRI screening programs since it might be related to a higher breast cancer risk. Therefore, the purpose of this study is to correlate BPE to patient and tumor characteristics in women with unilateral MRI-screen detected breast cancer who participated in an intermediate and high risk screening program. As BPE in the affected breast may be difficult to discern from enhancing cancer, we assumed that BPE in the contralateral breast is a representative measure for BPE in women with unilateral breast cancer.

MATERIALS AND METHODS

This retrospective study was approved by our local institutional board and a waiver for consent was granted. MR-examinations of women with unilateral breast cancers screen-detected on breast MRI were evaluated by two readers. BPE in the contralateral breast was rated according to BI-RADS. Univariate analyses were performed to study associations. Observer variability was computed.

RESULTS

Analysis included 77 breast cancers in 76 patients (age: 48±9.8 years), including 62 invasive and 15 pure ductal carcinoma in-situ cases. A negative association between BPE and tumor grade (p≤0.016) and a positive association with progesterone status (p≤0.021) was found. The correlation was stronger when only considering invasive disease. Inter-reader agreement was substantial.

CONCLUSION

Lower BPE in the contralateral breast in women with unilateral breast cancer might be associated to higher tumor grade and progesterone receptor negativity. Great care should be taken using BPE for stratification of patients to tailored screening programs.

Performance evaluation of breast cancer diagnosis with mammography, ultrasonography and magnetic resonance imaging

OBJECTIVE

Various imaging modalities have been used to diagnose suspicious breast lesions. Purpose of this study is to compare the diagnostic accuracy for breast cancer using mammography, ultrasonography and magnetic resonance imaging (MRI).

METHODS

Total 107 patients aged from 19 to 62 years are included in this retrospective study. Mammography, ultrasonography and MRI scans were performed for each patient detected with suspected breast tumor within a month. In addition, the tumor diversity (10 types of benign and 5 types of malignant) was confirmed by pathological findings of tumor biopsy. To compare the diagnosis performance of the three imaging modalities, the overall fraction correct (accuracy), positive predict value (PPV), negative predict value (NPV), sensitivity and specificity were calculated. Meanwhile, the receiver operating characteristic (ROC) analysis was also performed.

RESULTS

The diagnostic accuracy ranged from 78.5% to 86.9% among three imaging modalities. All modalities yielded a PPV lower than 77.8% and a NPV higher than 90.0% in identifying the presence of malignant tumors. MRI presented a diagnostic accuracy of 86.9%, as well as a sensitivity of 95.5% and an area under curve (AUC) of 0.948, which are higher than mammography and ultrasonography.

CONCLUSION

By using a diverse dataset and comparing the diagnostic accuracy of three imaging modalities commonly used in breast cancer detection and diagnosis, this study also demonstrated that mammography, ultrasonography and MRI had different diagnostic performance in breast tumor identification. Among them, MRI yielded the highest performance even though the unexpected specificity may lead to over-diagnosis, and ultrosonography is slightly better than mammography.

Metabolic Activity of Normal Glandular Tissue on 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography: Correlation with Menstrual Cycles and Parenchymal Enhancements

Purpose

The aims of our study were to correlate the degree of metabolic activity in normal glandular tissue measured on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) with qualitative background parenchymal enhancement (BPE) grades on magnetic resonance imaging (MRI), and to investigate the change in standardized uptake value (SUV) according to the patients' menstrual cycles.

Methods

From January 2013 to December 2015, 298 consecutive premenopausal patients with breast cancer who underwent both breast MRI and ¹⁸F-FDG PET/CT were identified. BPE was evaluated in the contralateral breast of cancer patients and categorized as minimal, mild, moderate, or marked based on Breast Imaging Reporting and Data System criteria. We analyzed the correlation between BPE and maximum SUV (SUVmax) and mean SUV (SUVmean) values. We also analyzed the metabolic activity of normal glandular tissue according to the patients' menstrual cycles.

Results

The mean SUVmax and SUVmean values differed significantly according to BPE grade (p<0001), with the lowest values occurring in the minimal group and the highest values occurring in the marked group. Spearman's correlation coefficients revealed moderate correlations between BPE grade and SUVmax (r=0.472, p<0.001) and BPE and SUVmean (r=0.498, p<0.001). The mean SUVmax and SUVmean values differed significantly according to the patients' menstrual cycles, with the highest values in the 3rd week and the lowest value in the 2nd week. Of 29 patients with low metabolic parenchyma (high BPE but low SUVmean values), 17 (58.6%) were in the 4th week of their menstrual cycle.

Conclusion

The metabolic activity of normal breast parenchyma, which is highest in the 3rd week and lowest in the 2nd week of the menstrual cycle, correlates moderately with BPE on MRI. Metabolic activity tends to be lower than blood flow and vessel permeability in the 4th week of the menstrual cycle.

Comparison between qualitative and quantitative assessment of background parenchymal enhancement on breast MRI

BACKGROUND

Potential clinical implications of the level of background parenchymal enhancement (BPE) on breast MRI are increasing. Currently, BPE is typically evaluated subjectively. Tests of concordance between subjective BPE assessment and computer-assisted quantified BPE have not been reported.

PURPOSE OR HYPOTHESIS

To compare subjective radiologist assessment of BPE with objective quantified parenchymal enhancement (QPE).

STUDY TYPE

Cross-sectional observational study.

POPULATION

Between 7/24/2015 and 11/27/2015, 104 sequential patients (ages 23 - 81 years, mean 49 years) without breast cancer underwent breast MRI and were included in this study.

FIELD STRENGTH/SEQUENCE

3T; fat suppressed axial T2, axial T1, and axial fat suppressed T1 before and after intravenous contrast.

ASSESSMENT

Four breast imagers graded BPE at 90 and 180 s after contrast injection on a 4-point scale (a-d). Fibroglandular tissue masks were generated using a phantom-validated segmentation algorithm, and were co-registered to pre- and postcontrast fat suppressed images to define the region of interest. QPE was calculated.

STATISTICAL TESTS

Receiver operating characteristic (ROC) analyses and kappa coefficients (k) were used to compare subjective BPE with QPE.

RESULTS

ROC analyses indicated that subjective BPE at 90 s was best predicted by quantified QPE ≤20.2 = a, 20.3-25.2 = b, 25.3-50.0 = c, >50.0 = d, and at 180 s by quantified QPE ≤ 32.2 = a, 32.3-38.3 = b, 38.4-74.5 = c, >74.5 = d. Agreement between subjective BPE and QPE was slight to fair at 90 s (k = 0.20-0.36) and 180 s (k = 0.19-0.28). At higher levels of QPE, agreement between subjective BPE and QPE significantly decreased for all four radiologists at 90 s (P ≤ 0.004) and for three of four radiologists at 180 s (P ≤ 0.004).

DATA CONCLUSION

Radiologists were less consistent with QPE as QPE increased.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1685-1691.

Background parenchymal enhancement: is it just an innocent effect of estrogen on the breast?

PURPOSE

We aimed to retrospectively analyze whether background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) correlates with menarche, menopause, reproductive period, menstrual cycle, gravidity-parity, family history of breast cancer, and the Breast Imaging-Reporting and Data System (BI-RADS) category of the patient.

METHODS

The study included 126 pre- and 78 postmenopausal women who underwent breast MRI in our institute between 2011 and 2016. Patients had filled a questionnaire form before the MRI. Two radiologists blinded to patient history graded the BPEs and the results were compared and analyzed.

RESULTS

The BPE was correlated with patient age and the day of menstrual cycle (P < 0.01 for both). No correlation was found with menarche age, menopause age, total number of reproductive years, and family history of breast cancer. In the moderate BPE group, only 1 out of 35 patients and in the marked BPE group only 1 out of 13 patients were postmenopausal and had BI-RADS scores of 4 and 5, respectively.

CONCLUSION

Increased symmetrical BPE is mainly due to current hormonal status in the premenopausal women. High-grade BPE, whether symmetrical or not, is rarely seen in postmenopausal women; hence, these patients should be further investigated or closely followed up.

Ductal Carcinoma in Situ: Quantitative Preoperative Breast MR Imaging Features Associated with Recurrence after Treatment

Purpose To investigate whether specific imaging features on breast magnetic resonance (MR) images are associated with ductal carcinoma in situ (DCIS) recurrence risk after definitive treatment. Materials and Methods Patients with DCIS who underwent preoperative dynamic contrast material-enhanced (DCE) MR imaging between 2004 and 2014 with ipsilateral recurrence more than 6 months after definitive surgical treatment were retrospectively identified. For each patient, a control subject with DCIS that did not recur was identified and matched on the basis of clinical, histopathologic, and treatment features known to affect recurrence risk. On DCE MR images, lesion characteristics (longest diameter, functional tumor volume [FTV], peak percentage enhancement [PE], peak signal enhancement ratio [SER], and washout fraction) and normal tissue features (background parenchymal enhancement [BPE] volume, mean BPE) were quantitatively measured. MR imaging features were compared between patients and control subjects by using the Wilcoxon signed-rank test, with adjustment for multiple comparisons. Results Of 415 subjects with DCIS who underwent preoperative MR imaging, 14 experienced recurrence and 11 had an identifiable matching control subject (final cohort, 11 patients and 11 control subjects). Median time to recurrence was 14 months, and median follow-up for control subjects was 102 months. When compared with matched control subjects, patients with DCIS recurrence exhibited significantly greater FTV (median, 9.3 cm³ vs 1.3 cm³, P = .01), lesion peak SER (median, 1.7 vs 1.2; P = .03), and mean BPE (median, 58.3% vs 41.1%; P = .02). Conclusion Quantitative lesion and normal breast tissue characteristics at preoperative MR imaging in women with newly diagnosed DCIS show promise for association with breast cancer recurrence after treatment. ^© RSNA, 2017.