Could parenchymal enhancement on contrast-enhanced spectral mammography (CESM) represent a new breast cancer risk factor? Correlation with known radiology risk factors

Evaluation of a ductal carcinoma in situ component accompanying HER2-positive invasive breast cancer on contrast-enhanced mammography

OBJECTIVES

A DCIS component can be present accompanying HER2+ invasive breast cancer (IBC) in approximately 57 % of patients. Until now, no contrast-enhanced mammography (CEM) studies have investigated the detection of a DCIS component, which is important for surgical decision-making. This study aimed to investigate imaging findings of a DCIS component in HER2+ IBC on CEM.

METHODS

Women with HER2+ IBC with a DCIS component that underwent CEM between 2013-2021 were included. Two independent radiologists retrospectively reassessed CEM exams, and a breast pathologist reassessed histopathology specimen. The percentage and extent of suspicious calcifications and non-mass enhancement (NME) on CEM, and interobserver agreement between radiologists was determined. In the primary surgery group, the detection rate of DCIS outside of the invasive tumor was determined, and maximum diameter of imaging findings was compared to histopathology.

RESULTS

Sixty-two patients were included. CEM showed suspicious calcifications (27.4 %), NME (16.1 %), both (27.4 %) or no findings (29.0 %), related to DCIS. In the primary surgery group (n = 45), CEM detected 27 of 35 DCIS components present outside of the invasive tumor (77.1 %). NME was a better predictor for DCIS diameter (ICC = 0.65) compared to suspicious calcifications (ICC = 0.43). Inter-observer agreement on detection of imaging findings was better for suspicious calcifications (κ = 0.81) compared to NME (κ = 0.47), while reliability between size measurements was comparable (ICC = 0.89 versus ICC = 0.80, respectively).

CONCLUSION

CEM was able to detect 77.1% of DCIS present outside of the invasive tumor. NME is the most accurate predictor of DCIS diameter, but requires improvements regarding inter-observer agreement.

Factors Influencing Background Parenchymal Enhancement in Breast Contrast-Enhanced Mammography: A Retrospective Study

Objective

To evaluate the association between background parenchymal enhancement (BPE) level and extent on contrast-enhanced mammography (CEM) with age, menopausal status, breast density, and menstrual cycle phase in women. Additionally, to characterize the dynamic changes in BPE during CEM.

Methods

This retrospective study included 103 women who underwent CEM at a single institution between September 2019 and November 2021 for screening or diagnostic purposes. Menopausal status and menstrual cycle phase were recorded for all patients. BPE on subtracted CEM images was assessed quantitatively (region of interest [ROI] analysis of pixel values) and qualitatively (subjective classification). Statistical analysis was performed to determine the relationship between BPE (level and extent) and age, menopausal status, breast density, and menstrual cycle phase. Dynamic changes in BPE level over time were also analyzed.

Results

Both BPE level and extent were negatively correlated with age (P=0.004, r=-0.280; P=0.001, r=-0.318). Postmenopausal women exhibited lower BPE level and extent compared to premenopausal women (P=0.003, Z=-2.958; P=0.042, 2=4.123). No significant association was observed between BPE and breast density or menstrual cycle phase (P>0.05). BPE level increased significantly from 3 to 9 minutes post-contrast injection (P<0.001, t=-10.7).

Conclusion

BPE in CEM is significantly associated with age and menopausal status. Further research is needed to clarify the relationship between BPE and breast density and menstrual cycle phase. BPE demonstrates a dynamic increase in level over time, this relates to post-contrast injection, rather than to the age of the woman.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

CLINICAL RELEVANCE STATEMENT

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

KEY POINTS

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

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

INTRODUCTION

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

BPE on contrast-enhanced mammography: relationship with breast density, age and menopausal status

PURPOSE

This retrospective study aimed to evaluate the relationship between BPE on CEM and breast density, age and menopausal status.

MATERIAL AND METHODS

Our analysis included all women eligible for CEM as a second-level examination in the diagnostic phase in a 12-month period. CEM were performed on a dedicated low-dose digital mammography unit after the injection of 1.5 ml/kg body weight Iohexol 350 mgI/ml. Both breast composition and BPE were assessed independently by two breast radiologists according to the CEM supplement to the 2013 ACR BI-RADS Mammography. A two-stage ordered probit regression model was fitted to evaluate the relationship between BPE and the other factors considered.

RESULTS

49 patients were included (median age = 55 years, 28.6% premenopausal and 71.4% postmenopausal). Breast composition was classified as ACR BI-RADS a in 4.1%, ACR BI-RADS b in 36.7%, ACR BI-RADS c in 46.9%, and ACR BI-RADS d in 12.2% of cases, by both Readers. A BPE 1 category was assigned in 53.1-55.1% of patients (by Reader 1 and 2, respectively), BPE 2 in 22.4%, BPE 3 in 18.4-12.2%, and BPE 4 in 6.1-10.2%. Higher breast density was strongly associated with higher levels of BPE, while BPE was not directly associated with age, both in fertile and postmenopausal patients. No significant differences were observed between the two Readers.

CONCLUSION

Increased BPE is associated with a well-established breast cancer risk factor as high breast density, while it was not directly dependent on the other non-modifiable factors considered.

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

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

Contrast-Enhanced Mammography: A Literature Review of Clinical Uses for Cancer Diagnosis and Surgical Oncology

Contrast-enhanced mammography (CEM) uses intermittent dual-energy (low- and high-energy) exposures to produce low-energy mammograms and recombine enhanced images after the administration of iodized contrast medium, which provides more detailed information to detect breast cancers by using the features of morphology and abnormal uptake. In this article, we reviewed the literature to clarify the clinical applications of CEM, including (1) the fundamentals of CEM: the technique, radiation exposure, and image interpretation; (2) its clinical uses for cancer diagnosis, including problem-solving, palpable mass, suspicious microcalcification, architecture distortion, screening, and CEM-guided biopsy; and (3) the concerns of surgical oncology in pre-operative and neoadjuvant chemotherapy assessments. CEM undoubtedly plays an important role in clinical practice.

Factors Influencing Background Parenchymal Enhancement in Contrast-Enhanced Mammography Images

Background: The aim of this study is to evaluate the correlation between background parenchymal enhancement (BPE) and various patient-related and technical factors in recombined contrast-enhanced spectral mammography (CESM) images. Material and Methods: We assessed CESM images from 62 female patients who underwent CESM between May 2017 and October 2019, focusing on factors influencing BPE. A total of 235 images, all acquired using the same mammography machine, were analyzed. A region of interest (ROI) with a standard size of 0.75 to 1 cm2 was used to evaluate the minimal, maximal, and average pixel intensity enhancement. Additionally, the images were qualitatively assessed on a scale from 1 (minimal BPE) to 4 (marked BPE). We examined correlations with body mass index (BMI), age, hematocrit, hemoglobin levels, cardiovascular conditions, and the amount of pressure applied during the examination. Results: Our study identified a significant correlation between the amount of pressure applied during the examination and the BPE (Spearman's ρ = 0.546). Additionally, a significant but weak correlation was observed between BPE and BMI (Spearman's ρ = 0.421). No significant associations were found between BPE and menopausal status, cardiovascular preconditions, hematocrit, hemoglobin levels, breast density, or age. Conclusions: Patient-related and procedural factors significantly influence BPE in CESM images. Specifically, increased applied pressure and BMI are associated with higher BPE.

Background parenchymal enhancement on contrast-enhanced mammography: associations with breast density and patient's characteristics

PURPOSE

To evaluate if background parenchymal enhancement (BPE) on contrast-enhanced mammography (CEM), graded according to the 2022 CEM-dedicated Breast Imaging Reporting and Data System (BI-RADS) lexicon, is associated with breast density, menopausal status, and age.

METHODS

This bicentric retrospective analysis included CEM examinations performed for the work-up of suspicious mammographic findings. Three readers independently and blindly evaluated BPE on recombined CEM images and breast density on low-energy CEM images. Inter-reader reliability was estimated using Fleiss κ. Multivariable binary logistic regression was performed, dichotomising breast density and BPE as low (a/b BI-RADS categories, minimal/mild BPE) and high (c/d BI-RADS categories, moderate/marked BPE).

RESULTS

A total of 200 women (median age 56.8 years, interquartile range 50.5-65.6, 140/200 in menopause) were included. Breast density was classified as a in 27/200 patients (13.5%), as b in 110/200 (55.0%), as c in 52/200 (26.0%), and as d in 11/200 (5.5%), with moderate inter-reader reliability (κ = 0.536; 95% confidence interval [CI] 0.482-0.590). BPE was minimal in 95/200 patients (47.5%), mild in 64/200 (32.0%), moderate in 25/200 (12.5%), marked in 16/200 (8.0%), with substantial inter-reader reliability (κ = 0.634; 95% CI 0.581-0.686). At multivariable logistic regression, premenopausal status and breast density were significant positive predictors of high BPE, with adjusted odds ratios of 6.120 (95% CI 1.847-20.281, p = 0.003) and 2.416 (95% CI 1.095-5.332, p = 0.029) respectively.

CONCLUSION

BPE on CEM is associated with well-established breast cancer risk factors, being higher in women with higher breast density and premenopausal status.

Deep-learning model for background parenchymal enhancement classification in contrast-enhanced mammography

Background.Breast background parenchymal enhancement (BPE) is correlated with the risk of breast cancer. BPE level is currently assessed by radiologists in contrast-enhanced mammography (CEM) using 4 classes: minimal, mild, moderate and marked, as described inbreast imaging reporting and data system(BI-RADS). However, BPE classification remains subject to intra- and inter-reader variability. Fully automated methods to assess BPE level have already been developed in breast contrast-enhanced MRI (CE-MRI) and have been shown to provide accurate and repeatable BPE level classification. However, to our knowledge, no BPE level classification tool is available in the literature for CEM.Materials and methods.A BPE level classification tool based on deep learning has been trained and optimized on 7012 CEM image pairs (low-energy and recombined images) and evaluated on a dataset of 1013 image pairs. The impact of image resolution, backbone architecture and loss function were analyzed, as well as the influence of lesion presence and type on BPE assessment. The evaluation of the model performance was conducted using different metrics including 4-class balanced accuracy and mean absolute error. The results of the optimized model for a binary classification: minimal/mild versus moderate/marked, were also investigated.Results.The optimized model achieved a 4-class balanced accuracy of 71.5% (95% CI: 71.2-71.9) with 98.8% of classification errors between adjacent classes. For binary classification, the accuracy reached 93.0%. A slight decrease in model accuracy is observed in the presence of lesions, but it is not statistically significant, suggesting that our model is robust to the presence of lesions in the image for a classification task. Visual assessment also confirms that the model is more affected by non-mass enhancements than by mass-like enhancements.Conclusion.The proposed BPE classification tool for CEM achieves similar results than what is published in the literature for CE-MRI.

Comparison of the effectiveness of contrast-enhanced mammography in detecting malignant lesions in patients with extremely dense breasts compared to the all-densities population

Purpose

To assess the effectiveness of contrast-enhanced mammography (CEM) recombinant images in detecting malignant lesions in patients with extremely dense breasts compared to the all-densities population.

Material and methods

792 patients with 808 breast lesions, in whom the final decision on core-needle biopsy was made based on CEM, and who received the result of histopathological examination, were qualified for a single-centre, retrospective study. Patient electronic records and imaging examinations were reviewed to establish demographics, clinical and imaging findings, and histopathology results. The CEM images were reassessed and assigned to the appropriate American College of Radiology (ACR) density categories.

Results

Extremely dense breasts were present in 86 (10.9%) patients. Histopathological examination confirmed the presence of malignant lesions in 52.6% of cases in the entire group of patients and 43% in the group of extremely dense breasts. CEM incorrectly classified the lesion as false negative in 16/425 (3.8%) cases for the whole group, and in 1/37 (2.7%) cases for extremely dense breasts. The sensitivity of CEM for the group of all patients was 96.2%, specificity - 60%, positive predictive values (PPV) - 72.8%, and negative predictive values (NPV) - 93.5%. In the group of patients with extremely dense breasts, the sensitivity of the method was 97.3%, specificity - 59.2%, PPV - 64.3%, and NPV - 96.7%.

Conclusions

CEM is characterised by high sensitivity and NPV in detecting malignant lesions regardless of the type of breast density. In patients with extremely dense breasts, CEM could serve as a complementary or additional examination in the absence or low availability of MRI.

Contrast-enhanced Mammography Artifacts and Pitfalls: Tips and Tricks to Avoid Misinterpretation

Contrast-enhanced mammography (CEM) involves addition of intravenous iodinated contrast material at digital mammography, thus increasing the ability to detect breast cancer owing to tumor contrast enhancement. After image acquisition, interpretation includes careful assessment of the technique, artifacts, and pitfalls and reporting with a standard lexicon category and appropriate follow-up recommendations. Artifacts and pitfalls that may cause image misinterpretation should be detected and distinguished from pathologic conditions. Different artifacts apparent on CEM images are usually caused during image acquisition and include CEM-specific and contrast agent-related artifacts, apart from the typical digital mammography artifacts. The pitfalls are related to technical and diagnostic difficulties. One disadvantage of CEM that MRI does not have is a technical factor related to a mammography technique that consists of blind spots that may not be included in the imaging field of mammography views, including the axilla, medial region of the breast, or areas close to the breast wall. Normal breast tissue enhancement called background parenchymal enhancement is also present at CEM and may affect interpretation performance. Diagnostic pitfalls are caused by minimally enhancing lesions, such as invasive lobular carcinomas and mucinous carcinomas, which are difficult to detect with CEM, resulting in false-negative findings. Benign lesions can show enhancement at CEM and represent false-positive lesions that should also be recognized. The authors discuss image interpretation of CEM studies and focus on the artifacts and pitfalls that may be encountered. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Interpreting contrast imaging to plan breast surgery

BACKGROUND

Contrast enhanced mammography (CEM) and magnetic resonance imaging (MRI) are more accurate than conventional imaging (CI) for breast cancer staging. How adding CEM and MRI to CI might change the surgical plan is understudied.

METHODS

Surgical plans (breast conserving surgery (BCS), wider BCS, BCS with diagnostic excision (>1BCS), mastectomy) were devised by mock-MDT (radiologist, surgeon and pathology reports) according to disease extent on CI, CI + CEM and CI + MRI. Differences in the mock-MDT's surgical plans following the addition of CEM or MRI were investigated. Using pre-defined criteria, the appropriateness of the modified plans was assessed by comparing estimated disease extent on imaging with final pathology. Surgery performed was recorded from patient records.

RESULTS

Contrast imaging modified mock-MDT plans for 20 of 61(32.8%) breasts. The addition of CEM changed the plan in 16/20 (80%) and MRI in 17/20 breasts (85%). Identical changes were proposed by both CEM and MRI in 13/20 (65%) breasts. The modified surgical plan based on CI + CEM was possibly appropriate for 6/16 (37.5%), and CI + MRI in 9/17, (52.9%) breasts. The surgery performed was concordant with the mock-MDT plan for all 10 patients where the plans could be compared (BCS 1, >1 BCS 2 and mastectomy 7).

CONCLUSION

Adding CEM or MRI to CI changed mock-MDT plans in up to one third of women, but not all were appropriate. Changing surgical plans following addition of contrast imaging to CI without biopsy confirmation could lead to over or under-treatment.

Association of Breast Cancer Odds with Background Parenchymal Enhancement Quantified Using a Fully Automated Method at MRI: The IMAGINE Study

Background Background parenchymal enhancement (BPE) at breast MRI has been associated with increased breast cancer risk in several independent studies. However, variability of subjective BPE assessments have precluded its use in clinical practice. Purpose To examine the association between fully objective measures of BPE at MRI and odds of breast cancer. Materials and Methods This prospective case-control study included patients who underwent a bilateral breast MRI examination and were receiving care at one of three centers in the United States from November 2010 to July 2017. Breast volume, fibroglandular tissue (FGT) volume, and BPE were quantified using fully automated software. Fat volume was defined as breast volume minus FGT volume. BPE extent was defined as the proportion of FGT voxels with enhancement of 20% or more. Spearman rank correlation between quantitative BPE extent and Breast Imaging Reporting and Data System (BI-RADS) BPE categories assigned by an experienced board-certified breast radiologist was estimated. With use of multivariable logistic regression, breast cancer case-control status was regressed on tertiles (low, moderate, and high) of BPE, FGT volume, and fat volume, with adjustment for covariates. Results In total, 536 case participants with breast cancer (median age, 48 years [IQR, 43-55 years]) and 940 cancer-free controls (median age, 46 years [IQR, 38-55 years]) were included. BPE extent was positively associated with BI-RADS BPE (rs = 0.54; P < .001). Compared with low BPE extent (range, 2.9%-34.2%), high BPE extent (range, 50.7%-97.3%) was associated with increased odds of breast cancer (odds ratio [OR], 1.74 [95% CI: 1.23, 2.46]; P for trend = .002) in a multivariable model also including FGT volume (OR, 1.39 [95% CI: 0.97, 1.98]) and fat volume (OR, 1.46 [95% CI: 1.04, 2.06]). The association of high BPE extent with increased odds of breast cancer was similar for premenopausal and postmenopausal women (ORs, 1.75 and 1.83, respectively; interaction P = .73). Conclusion Objectively measured BPE at breast MRI is associated with increased breast cancer odds for both premenopausal and postmenopausal women. Clinical trial registration no. NCT02301767 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bokacheva in this issue.

Qualitative assessments of density and background parenchymal enhancement on contrast-enhanced spectral mammography associated with breast cancer risk in high-risk women

OBJECTIVE

To investigate the correlation between the risk of breast cancer for high-risk females and the density and background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM).

METHODS

Females at high-risk, without breast cancer history and received CESM from July 2016 to December 2017 were retrospectively enrolled. The longest follow-up time was 4.5 years, and patients who developed breast cancer with maximized follow-up time were classified as cancer cohort, while females who did not develop breast cancer were categorized as control cohort. These two cohorts were one-to-one matched in age, family and/or genetic history of breast cancer, menopausal status and BRCA status. The density and BPE at CESM imaging were assessed. Conditional logistic regression was applied to evaluate the relationship between imaging features and breast cancer risk.

RESULTS

During the follow-up interval, 90 women at high-risk without history of breast cancer were newly diagnosed. Compared with minimal BPE, increasing BPE levels were associated with the risk of breast cancer among high-risk females in a time interval of 4.5 years (mild: odds ratio [OR]=3.2, p = 0.001; moderate: OR = 4.0, p = 0.002; marked: OR = 11.2, p < 0.001). In addition, females with mild, moderate or marked BPE were four times more likely to be diagnosed with breast cancer than females with minimal BPE in a time interval of 4.5 years (OR = 4.0, p < 0.001).

CONCLUSION

Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk females.

ADVANCES IN KNOWLEDGE

• Qualitative CESM BPE assessment may be useful in the prediction of breast cancer risk among high-risk women during the follow-up period of 4.5 years. • The significance of breast density as an independent risk factor is not fully established for high-risk women during the follow-up period of 4.5 years.

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

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

Accuracy and precision of contrast enhanced mammography versus MRI for predicting breast cancer size: how "good" are they really?

OBJECTIVE

To evaluate and compare the accuracy and precision of contrast-enhanced mammography (CEM) vs MRI to predict the size of biopsy-proven invasive breast cancer.

METHODS

Prospective study, 59 women with invasive breast cancer on needle biopsy underwent CEM and breast MRI. Two breast radiologists read each patient's study, with access limited to one modality. CEM lesion size was measured using low-energy and recombined images and on MRI, the first post-contrast series. Extent of abnormality per quadrant was measured for multifocal lesions. Reference standards were size of largest invasive malignant lesion, invasive (PathInvasive) and whole (PathTotal). Pre-defined clinical concordance ±10 mm.

RESULTS

Mean patient age 56 years, 42 (71%) asymptomatic. Lesions were invasive ductal carcinoma 40 (68%) with ductal carcinoma in situ (31/40) in 78%, multifocal in 12 (20%). Median lesion size was 17 mm (invasive) and 27 mm (total), range (5-125 mm). Lin's concordance correlation coefficients for PathTotal 0.75 (95% CI 0.6, 0.84) and 0.71 (95% CI 0.56, 0.82) for MRI and contrast-enhanced spectral mammography (CESM) respectively. Mean difference for total size, 3% underestimated and 4% overestimated, and for invasive 41% and 50% overestimate on MRI and CESM respectively. LOAs for PathTotal varied from 60% under to a 2.4 or almost threefold over estimation. MRI was concordant with PathTotal in 36 (64%) cases compared with 32 (57%) for CESM. Both modalities concordant in 26 (46%) cases respectively.

CONCLUSION

Neither CEM nor MRI have sufficient accuracy to direct changes in planned treatment without needle biopsy confirmation.

ADVANCES IN KNOWLEDGE

Despite small mean differences in lesion size estimates using CEM or MRI, the 95% limits of agreement do not meet clinically acceptable levels.

Contrast-enhanced mammography (CEM) versus MRI for breast cancer staging: detection of additional malignant lesions not seen on conventional imaging

BACKGROUND

Contrast-enhanced mammography (CEM) is more available than MRI for breast cancer staging but may not be as sensitive in assessing disease extent. We compared CEM and MRI in this setting.

METHODS

Fifty-nine women with invasive breast cancer underwent preoperative CEM and MRI. Independent pairs of radiologists read CEM studies (after reviewing a 9-case set prior to study commencement) and MRI studies (with between 5 and 25 years of experience in breast imaging). Additional lesions were assigned National Breast Cancer Centre (NBCC) scores. Positive lesions (graded NBCC ≥ 3) likely to influence surgical management underwent ultrasound and/or needle biopsy. True-positive lesions were positive on imaging and pathology (invasive or in situ). False-positive lesions were positive on imaging but negative on pathology (high-risk or benign) or follow-up. False-negative lesions were negative on imaging (NBCC < 3 or not identified) but positive on pathology.

RESULTS

The 59 women had 68 biopsy-proven malignant lesions detected on mammography/ultrasound, of which MRI demonstrated 66 (97%) and CEM 67 (99%) (p = 1.000). Forty-one additional lesions were detected in 29 patients: six of 41 (15%) on CEM only, 23/41 (56%) on MRI only, 12/41 (29%) on both; CEM detected 1/6 and MRI 6/6 malignant additional lesions (p = 0.063), with a positive predictive value (PPV) of 1/13 (8%) and 6/26 (23%) (p = 0.276).

CONCLUSIONS

While MRI and CEM were both highly sensitive for lesions detected at mammography/ultrasound, CEM may not be as sensitive as MRI in detecting additional otherwise occult foci of malignancy.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry: ACTRN 12613000684729.

Contrast enhanced mammography: focus on frequently encountered benign and malignant diagnoses

Contrast-enhanced mammography (CEM) is becoming a widely adopted modality in breast imaging over the past few decades and exponentially so over the last few years, with strong evidence of high diagnostic performance in cancer detection. Evidence is also growing indicating comparative performance of CEM to MRI in sensitivity with fewer false positive rates. As application of CEM ranges from potential use in screening dense breast populations to staging of known breast malignancy, increased familiarity with the modality and its implementation, and disease processes encountered becomes of great clinical significance. This review emphasizes expected normal findings on CEM followed by a focus on examples of the commonly encountered benign and malignant pathologies on CEM.

Contrast-enhanced mammography in breast cancer screening

Contrast-enhanced mammography (CEM) is a promising vascular-based breast imaging technique with high diagnostic performance in detecting breast cancer. Dual-energy acquisition using low and high energy x-ray spectra following intravenous iodinated contrast injection provides both anatomic and functional information in the same examination. The low-energy images are equivalent to standard digital mammography and the post-processed recombined images depict enhancement analogous to contrast-enhanced breast magnetic resonance imaging (MRI). Thus, CEM has the potential to detect abnormal morphologic features as well as neovascularity associated with breast cancer. Since its emergence in 2011, CEM has consistently demonstrated superior performance compared with standard mammography and mammography plus ultrasound, particularly in women with dense breasts, with high sensitivity approaching that of MRI, supporting its use as a cost-effective diagnostic and screening tool. CEM has been primarily used in the diagnostic setting to evaluate patients with screening abnormalities or with symptomatic breasts, to perform preoperative staging of newly diagnosed breast cancer, and to evaluate response to neoadjuvant chemotherapy. More recently, CEM has been performed to screen women who have an intermediate to high lifetime risk of developing breast cancer. In addition to its high diagnostic performance, CEM is less expensive and more accessible than MRI and potentially better tolerated by patients. Minor drawbacks to CEM include a slightly increased radiation dose compared with standard mammography and a low risk for contrast allergy reaction. The aim of this study is to review the background, current literature, and future applications of CEM in breast cancer screening.

How Dual-Energy Contrast-Enhanced Spectral Mammography Can Provide Useful Clinical Information About Prognostic Factors in Breast Cancer Patients: A Systematic Review of Literature

Introduction

In the past decade, a new technique derived from full-field digital mammography has been developed, named contrast-enhanced spectral mammography (CESM). The aim of this study was to define the association between CESM findings and usual prognostic factors, such as estrogen receptors, progesterone receptors, HER2, and Ki67, in order to offer an updated overview of the state of the art for the early differential diagnosis of breast cancer and following personalized treatments.

Materials and Methods

According to the PRISMA guidelines, two electronic databases (PubMed and Scopus) were investigated, using the following keywords: breast cancer AND (CESM OR contrast enhanced spectral mammography OR contrast enhanced dual energy mammography) AND (receptors OR prognostic factors OR HER2 OR progesterone OR estrogen OR Ki67). The search was concluded in August 2021. No restriction was applied to publication dates.

Results

We obtained 28 articles from the research in PubMed and 114 articles from Scopus. After the removal of six replicas that were counted only once, out of 136 articles, 37 articles were reviews. Eight articles alone have tackled the relation between CESM imaging and ER, PR, HER2, and Ki67. When comparing radiological characterization of the lesions obtained by either CESM or contrast-enhanced MRI, they have a similar association with the proliferation of tumoral cells, as expressed by Ki-67. In CESM-enhanced lesions, the expression was found to be 100% for ER and 77.4% for PR, while moderate or high HER2 positivity was found in lesions with non-mass enhancement and with mass closely associated with a non-mass enhancement component. Conversely, the non-enhancing breast cancer lesions were not associated with any prognostic factor, such as ER, PR, HER2, and Ki67, which may be associated with the probability of showing enhancement. Radiomics on CESM images has the potential for non-invasive characterization of potentially heterogeneous tumors with different hormone receptor status.

Conclusions

CESM enhancement is associated with the proliferation of tumoral cells, as well as to the expression of estrogen and progesterone receptors. As CESM is a relatively young imaging technique, a few related works were found; this may be due to the “off-label” modality. In the next few years, the role of CESM in breast cancer diagnostics will be more thoroughly investigated.

Identifying factors that may influence the classification performance of radiomics models using contrast-enhanced mammography (CEM) images

Background

Radiomics plays an important role in the field of oncology. Few studies have focused on the identification of factors that may influence the classification performance of radiomics models. The goal of this study was to use contrast-enhanced mammography (CEM) images to identify factors that may potentially influence the performance of radiomics models in diagnosing breast lesions.

Methods

A total of 157 women with 161 breast lesions were included. Least absolute shrinkage and selection operator (LASSO) regression and the random forest (RF) algorithm were employed to construct radiomics models. The classification result for each lesion was obtained by using 100 rounds of five-fold cross-validation. The image features interpreted by the radiologists were used in the exploratory factor analyses. Univariate and multivariate analyses were performed to determine the association between the image features and misclassification. Additional exploratory analyses were performed to examine the findings.

Results

Among the lesions misclassified by both LASSO and RF ≥ 20% of the iterations in the cross-validation and those misclassified by both algorithms ≤5% of the iterations, univariate analysis showed that larger lesion size and the presence of rim artifacts and/or ripple artifacts were associated with more misclassifications among benign lesions, and smaller lesion size was associated with more misclassifications among malignant lesions (all p <  0.050). Multivariate analysis showed that smaller lesion size (odds ratio [OR] = 0.699, p = 0.002) and the presence of air trapping artifacts (OR = 35.568, p = 0.025) were factors that may lead to misclassification among malignant lesions. Additional exploratory analyses showed that benign lesions with rim artifacts and small malignant lesions (< 20 mm) with air trapping artifacts were misclassified by approximately 50% more in rate compared with benign and malignant lesions without these factors.

Conclusions

Lesion size and artifacts in CEM images may affect the diagnostic performance of radiomics models. The classification results for lesions presenting with certain factors may be less reliable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00460-8.

Diagnostic Accuracy of Contrast-Enhanced, Spectral Mammography (CESM) and 3T Magnetic Resonance Compared to Full-Field Digital Mammography plus Ultrasound in Breast Lesions: Results of a (Pilot) Open-Label, Single-Centre Prospective Study

Introduction: To assess the diagnostic accuracy of CESM and 3T MRI compared to full-field digital mammography (FFDM), plus US, in the evaluation of advanced breast lesions. Materials and Methods: Consenting women with suspicious findings underwent FFDM, US, CESM and 3T MRI. Breast lesions were histologically assessed, with histology being the gold standard. Two experienced breast radiologists, blinded to cancer status, read the images. Diagnostic accuracy of (1) CESM as an adjunct to FFDM and US, and (2) 3T MRI as an adjunct to CESM compared to FFDM and US, was assessed. Measures of accuracy were sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV). Results: There were 118 patients included along with 142 histologically characterized lesions. K agreement values were 0.69, 0.68, 0.63 and 0.56 for concordance between the gold standard and FFDM, FFDM + US, CESM and MRI, respectively (p < 0.001, for all). K concordance for CESM was 0.81 with FFDM + US and 0.73 with MRI (p value < 0.001 for all). Conclusions: CESM may represent a valuable alternative and/or an integrating technique to MRI in the evaluation of breast cancer patients.

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

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

Contrast-Enhanced Mammography: Technique, Indications, and Review of Current Literature

Purpose of Review

To provide an update on contrast-enhanced mammography (CEM) regarding current technique and interpretation, the performance of this modality versus conventional breast imaging modalities (mammography, ultrasound, and MRI), existing clinical applications, potential challenges, and pitfalls.

Recent Findings

Multiple studies have shown that the low-energy, non-contrast-enhanced images obtained when performing CEM are non-inferior to full-field digital mammography with the added benefit of recombined post-contrast images, which have been shown to provide comparable information compared to MRI without sacrificing sensitivity and negative predictive values. While CEMs' usefulness for further diagnostic characterization of indeterminate breast findings is apparent, additional studies have provided strong evidence of potential roles in screening intermediate to high-risk populations, evaluation of disease extent, and monitoring response to therapy, particularly in patients in whom MRI is either unavailable or contraindicated. Others have shown that some patients prefer CEM over MRI given the ease of performance and patient comfort. Additionally, some health systems may find significantly reduced costs compared to MRI. Currently, CEM is hindered by the limited availability of CEM-guided tissue sampling and issues of intravenous contrast administration. However, commercially available CEM-guided biopsy systems are on the horizon, and small changes in practice workflow can be quickly adopted. As of now, MRI remains a mainstay of high-risk screening, evaluation of the extent of disease, and monitoring response to therapy, but smaller studies have suggested that CEM may be equivalent to MRI for these indications, and larger confirmatory studies are needed.

Summary

CEM is an emerging problem-solving breast imaging modality that provides complementary information to conventional imaging modalities and may potentially be used in place of MRI for specific indications and/or patient populations.

Diagnostic Performance of Contrast-enhanced Mammography: Comparison With MRI and Mammography

OBJECTIVE

To compare the diagnostic performance of contrast-enhanced mammography (CEM) with MRI and mammography (MG) based on histopathological results.

METHODS

In this IRB-approved study, written informed consent was obtained from all patients. Images from 40 patients (62 lesions) with suspicious findings on US between March 2018 and August 2018 were evaluated. Sensitivity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of CEM, MRI, and MG were evaluated and compared within a 95% confidence interval. Maximum dimensions of lesions were measured and correlations of results were evaluated with Spearman's Rho test.

RESULTS

In the histopathological analysis, 66% (41/62) of lesions were malignant and 34% (21/62) of lesions were benign. Contrast-enhanced mammography, MRI, and MG had sensitivities of 100% (41/41), 100% (41/41), and 80% (33/41), respectively. The sensitivity of CEM and MRI was significantly better than that of MG (P = 0.03). The NPVs of CEM (100%, 7/7) and MRI (100%, 14/14) were statistically higher than the NPV of MG (60%, 12/20) (P = 0.03). The false-positive rates for CEM, MRI, and MG were 33% (7/21), 66% (14/21), and 42% (9/21), respectively. Contrast-enhanced mammography had a significantly lower false-positive rate than MRI (P < 0.001). Mammography had the highest false-negative rate, missing 19% (8/41) of malignant lesions.

CONCLUSION

Contrast-enhanced mammography has similar performance characteristics to MRI and improved performance characteristics relative to MG. In particular, CEM and MRI have similar sensitivity and NPVs and both are superior in each of these metrics to MG.

Artifacts in contrast-enhanced mammography: are there differences between vendors?

PURPOSE

Contrast-Enhanced Mammography (CEM) produces a dual-energy subtracted (DES) image that demonstrates iodine uptake (neovascularity) in breast tissue. We aim to review a range of artifacts on DES images produced using equipment from two different vendors and compare their incidence and subjective severity.

METHODS

We retrospectively reviewed CEM studies performed between September 2013 and March 2017 using GE Senographe Essential (n = 100) and Hologic Selenia Dimensions (n = 100) equipment. Artifacts were categorized and graded in severity by a subspecialist breast radiologist and one of two medical imaging technologists in consensus. The incidence of artifacts between vendors was compared by calculating the relative risk, and the severity gradings were compared using a Wilcoxon rank-sum test.

RESULTS

Elephant rind, corrugations and the black line on chest wall artifact were seen exclusively in Hologic images. Artifacts such as cloudy fat, negative rim around lesion and white line on pectoral muscle were seen in significantly more Hologic images (p < 0.05) whilst halo, ripple, skin line enhancement, black line on pectoral muscle, bright pectorals, chest wall high-lighting and air gap were seen in significantly more GE images (p < 0.05). The severity gradings for cloudy fat had a significantly higher mean rank in Hologic images (p < 0.001) whilst halo and ripple artifacts had a significantly higher mean rank in GE images (p < 0.001 and p = 0.028 respectively).

CONCLUSION

The type, incidence and subjective severity of CEM-specific artifacts differ between vendors. Further research is needed, but differences in algorithms used to produce the DE image are postulated to be a significant contributor.

Contrast-enhanced mammography: past, present, and future

Contrast-enhanced mammography (CEM) combines conventional mammography with iodinated contrast material to improve cancer detection. CEM has comparable performance to breast MRI without the added cost or time of conventional MRI protocols. Thus, this technique may be useful for indications previously reserved for MRI, such as problem-solving, determining disease extent in patients with newly diagnosed cancer, monitoring response to neoadjuvant therapy, evaluating the posttreatment breast for residual or recurrent disease, and potentially screening in women at intermediate- or high-risk for breast cancer. This article will provide a comprehensive overview on the past, present, and future of CEM, including its evolving role in the diagnostic and screening settings.

Background parenchymal enhancement on contrast-enhanced spectral mammography does not represent an influencing factor for breast cancer: A preliminary study

To compare the relationship between background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM), mammographic breast density (MBD), age, in the group with benign vs malignant breast lesions.Four hundred thirty three non-high-risk patients from January 2018 to May 2019 were retrospectively analyzed. Patients were assigned into 4 groups: premenopausal benign lesions, premenopausal malignant lesions, postmenopausal benign lesions, and postmenopausal malignant lesions. The differences in CESM BPE and MBD between premenopausal benign lesions and premenopausal malignant lesions, between postmenopausal benign lesions and postmenopausal malignant lesions, between premenopausal and postmenopausal benign lesions, and between premenopausal and postmenopausal malignant lesions were evaluated. Pearson Chi-Squared test was used to analyze the differences between the above groups. Spearman rank correlation analysis was used to evaluate the correlations between BPE, MBD, and age. Multiple logistic regression was used to analyze the influencing factors of breast cancer. P < .05 was considered statistically significant.There was no significant difference in CESM BPE or MBD of benign and malignant lesions regardless of premenopausal or postmenopausal status, but there was a significant difference in CESM BPE and MBD of premenopausal and postmenopausal patients regardless of the presence of benign or malignant lesions. The intensity of CESM BPE was positively correlated with MBD, and the intensity of CESM BPE and MBD were negatively correlated with age. Multiple logistic regression analysis showed that age was an influencing factor for breast cancer in both premenopausal and postmenopausal patients.For non-high-risk women, CESM BPE and MBD were not correlated with benign or malignant breast lesions, and age was an influencing factor for breast cancer.

Background Parenchymal Enhancement at Contrast-Enhanced Spectral Mammography (CESM) as a Breast Cancer Risk Factor

RATIONALE AND OBJECTIVES

To assess the extent of background parenchymal enhancement (BPE) at contrast-enhanced spectral mammography (CESM), association between clinical factors and BPE, and between BPE extent and breast cancer.

MATERIALS AND METHODS

This study included 516 women who underwent CESM imaging for screening and diagnostic purposes between 2012 and 2015 in a single center. BPE at CESM images was retrospectively, independently and blindly graded by six experienced radiologists using the following scale: minimal, mild, moderate, or marked. Agreement between readers was estimated using Kendall's W coefficient of concordance. Associations between clinical factors and BPE, and between BPE and breast cancer were examined using generalized estimating equations. Association between BPE and breast cancer was assessed for the whole study group, and for the screening population separately.

RESULTS

Most women underwent CESM for breast cancer screening (424/516, 82.2%). Mean age was 53 years, the majority had dense breasts (50.4-94%, depending on the reviewer), and minimal to mild BPE (75.8-89.9%). A total of 53/516 women had breast cancer. Overall concordance (W) values between the readers were 0.611 for breast density and 0.789 on BPE. Increased breast density and younger age were positive predictors for increased BPE (odds ratio [OR] 4.07, 95% confidence interval [CI] 2.32-7.14, p < 0.001; OR 2.88, 95% CI 1.87-4.42, p < 0.001, respectively). Breast radiation therapy was a negative predictor for BPE (OR 0.13, 95% CI 0.06-0.31, p < 0.001). Women with increased BPE had increased odds for breast cancer (OR 2.24, 95% CI 1.23-4.09, p = 0.008). This result was consistent when screening cases were analyzed separately (OR 6.27, 95% CI 2.38-16.53, p < 0.001).

CONCLUSION

BPE at CESM was associated with breast density. Women with increased BPE had increased odds for breast cancer, independently of other potential risk factors.

Factors Associated With Background Parenchymal Enhancement on Contrast-Enhanced Mammography

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

Background Parenchymal Enhancement on Contrast-Enhanced Spectral Mammography: Influence of Age, Breast Density, Menstruation Status, and Menstrual Cycle Timing

To evaluate the relationship of the extent and quantitative intensity of background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM) with age, breast density, menstruation status, and menstrual cycle timing. This retrospective study included women who underwent CESM from July 2017 to March 2019 and who had menstruation status records. BPE category assessment was performed subjectively. BPE intensity was quantitatively measured using regions-of-interest. 208 subjects were included (150 were regular menstrual cycle and 58 were postmenopausal). The breast density was classified as category B in 11 subjects, category C in 231 subjects, and category D in 23 subjects. Subjects based on menstrual cycle timing, 24 at days 1-7, 55 at days 8-14, 48 at days 15-21, and 23 at days 22-28. Both quantitative and categorical analyses show a weak negative correlation between BPE and age in all subjects, but there was no significant correlation in premenopausal patients. Both the BPE pixel intensity value and BPE category was significantly lower in postmenopausal patients than in premenopausal patients, and there was no significant difference in breast density according to BPE. The minimum and maximum pixel values of BPE on days 8-14 of the menstrual cycle was significantly lower than those on days 15-21. There was no correlation between BPE level and menstrual cycle timing. Breast density with category D was more likely to have a lower BPE level than category C. We show here that BPE level is affected by menstruation status and menstrual cycle timing. We suggest that CESM should not be performed on days 15-21 of the menstrual cycle, but on days 8-14.

Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review

We reviewed technical parameters, acquisition protocols and adverse reactions (ARs) for contrast-enhanced spectral mammography (CESM). A systematic search in databases, including MEDLINE/EMBASE, was performed to extract publication year, country of origin, study design; patients; mammography unit/vendor, radiation dose, low-/high-energy tube voltage; contrast molecule, concentration and dose; injection modality, ARs and acquisition delay; order of views; examination time. Of 120 retrieved articles, 84 were included from 22 countries (September 2003-January 2019), totalling 14012 patients. Design was prospective in 44/84 studies (52%); in 70/84 articles (83%), a General Electric unit with factory-set kVp was used. Per-view average glandular dose, reported in 12/84 studies (14%), ranged 0.43-2.65 mGy. Contrast type/concentration was reported in 79/84 studies (94%), with Iohexol 350 mgI/mL mostly used (25/79, 32%), dose and flow rate in 72/84 (86%), with 1.5 mL/kg dose at 3 mL/s in 62/72 studies (86%). Injection was described in 69/84 articles (82%), automated in 59/69 (85%), manual in 10/69 (15%) and flush in 35/84 (42%), with 10-30 mL dose in 19/35 (54%). An examination time < 10 min was reported in 65/84 studies (77%), 120 s acquisition delay in 65/84 (77%) and order of views in 42/84 (50%) studies, beginning with the craniocaudal view of the non-suspected breast in 7/42 (17%). Thirty ARs were reported by 14/84 (17%) studies (26 mild, 3 moderate, 1 severe non-fatal) with a pooled rate of 0.82% (fixed-effect model). Only half of CESM studies were prospective; factory-set kVp, contrast 1.5 mL/kg at 3 mL/s and 120 s acquisition delay were mostly used; only 1 severe AR was reported. CESM protocol standardisation is advisable.

Up-regulated lncRNA GAS5 promotes chemosensitivity and apoptosis of triple-negative breast cancer cells

Up to accomplishment of this study, the role of long non-coding RNAs (lncRNAs) in breast cancer has been investigated in several researches. Nevertheless, its association with the chemosensitivity of cancer was little known. Therefore, this study is focused on lncRNA GAS5 and its influence in the chemosensitivity of triple-negative breast cancer (TNBC). Expression of GAS5 in TNBC tissues and cells was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and its methylation was evaluated using methylation-specific polymerase chain reaction (MSP). Moreover, in order to define the contributory role of GAS5 in TNBC, GAS5 expression, proliferation, and apoptosis of TNBC cells were detected by a series of experiment. Finally, the effects of GAS5 in vivo were investigated by measuring tumor formation in nude mice. GAS5 was poorly expressed in TNBC tissues and cells, which could regulate the progression of TNBC. The methylation of CpG island in the promoter region of GAS5 in MDA-MB-231 and MDA-MB-468 cells was decreased, while GAS5 expression in cells was increased. Overexpressed GAS5 reduced the inhibitory concentration (IC50) value and the cell proliferation of TNBC, and promoted their apoptosis, so as to delay the progression of TNBC. Our study provides evidence that up-regulated GAS5 suppressed the progression of TNBC and promoted chemosensitivity and apoptosis of TNBC cells. Thus, GAS5 may be a potential candidate for the treatment of TNBC.

Fully Automated Support System for Diagnosis of Breast Cancer in Contrast-Enhanced Spectral Mammography Images

Contrast-Enhanced Spectral Mammography (CESM) is a novelty instrumentation for diagnosing of breast cancer, but it can still be considered operator dependent. In this paper, we proposed a fully automatic system as a diagnostic support tool for the clinicians. For each Region Of Interest (ROI), a features set was extracted from low-energy and recombined images by using different techniques. A Random Forest classifier was trained on a selected subset of significant features by a sequential feature selection algorithm. The proposed Computer-Automated Diagnosis system is tested on 48 ROIs extracted from 53 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) from the breast cancer screening phase between March 2017 and June 2018. The present method resulted highly performing in the prediction of benign/malignant ROIs with median values of sensitivity and specificity of 87.5% and 91.7%, respectively. The performance was high compared to the state-of-the-art, even with a moderate/marked level of parenchymal background. Our classification model outperformed the human reader, by increasing the specificity over 8%. Therefore, our system could represent a valid support tool for radiologists for interpreting CESM images, both reducing the false positive rate and limiting biopsies and surgeries.