Contrast-enhanced Mammography versus MR Imaging of the Breast

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

Lesion attention guided neural network for contrast-enhanced mammography-based biomarker status prediction in breast cancer

BACKGROUND AND OBJECTIVE

Accurate identification of molecular biomarker statuses is crucial in cancer diagnosis, treatment, and prognosis. Studies have demonstrated that medical images could be utilized for non-invasive prediction of biomarker statues. The biomarker status-associated features extracted from medical images are essential in developing medical image-based non-invasive prediction models. Contrast-enhanced mammography (CEM) is a promising imaging technique for breast cancer diagnosis. This study aims to develop a neural network-based method to extract biomarker-related image features from CEM images and evaluate the potential of CEM in non-invasive biomarker status prediction.

METHODS

An end-to-end learning convolutional neural network with the whole breast images as inputs was proposed to extract CEM features for biomarker status prediction in breast cancer. The network focused on lesion regions and flexibly extracted image features from lesion and peri‑tumor regions by employing supervised learning with a smooth L1-based consistency constraint. An image-level weakly supervised segmentation network based on Vision Transformer with cross attention to contrast images of breasts with lesions against the contralateral breast images was developed for automatic lesion segmentation. Finally, prediction models were developed following further selection of significant features and the implementation of random forest-based classification. Results were reported using the area under the curve (AUC), accuracy, sensitivity, and specificity.

RESULTS

A dataset from 1203 breast cancer patients was utilized to develop and evaluate the proposed method. Compared to the method without lesion attention and with only lesion regions as inputs, the proposed method performed better at biomarker status prediction. Specifically, it achieved an AUC of 0.71 (95 % confidence interval [CI]: 0.65, 0.77) for Ki-67 and 0.73 (95 % CI: 0.65, 0.80) for human epidermal growth factor receptor 2 (HER2).

CONCLUSIONS

A lesion attention-guided neural network was proposed in this work to extract CEM image features for biomarker status prediction in breast cancer. The promising results demonstrated the potential of CEM in non-invasively predicting the biomarker statuses in breast cancer.

Breast masses with rim enhancement on contrast-enhanced mammography: morphological and enhancement features for diagnosis and differentiation of benign and malignant

OBJECTIVES

To investigate the imaging characteristics and clinicopathological features of rim enhancement of breast masses demonstrated on contrast-enhanced mammography (CEM).

METHODS

67 cases of breast lesions confirmed by pathology and showing rim enhancement on CEM examinations were analyzed. The lesions were divided into benign and malignant groups, and the morphological and enhanced features were described. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated separately for each morphology descriptor to evaluate the diagnostic ability of each indicator.

RESULTS

There were 35 (52.2%) malignant and 32 (47.8%) benign lesions. There are significant differences in the morphological and enhanced features between benign and malignant lesions. 29/35 (82.9%) malignant lesions exhibited irregular shapes, and 31/35 (88.6%) showed indistinct margins. 28/35 (80%) malignant lesions displayed strong enhancement on CEM, while 12/32 (37.5%) benign lesions exhibited weak enhancement (P = 0.001). Malignant lesions showed a higher incidence of unsmooth inner walls than benign lesions (28/35 vs 7/32; P <.001). Lesion margins showed high sensitivity of 88.57% and NPV of 81.8%. The presence of suspicious calcifications had the highest specificity of 100% and PPV of 100%. The diagnostic sensitivity, specificity, PPV, and NPV of the combined parameters were 97.14%, 93.15%, 94.44%, and 96.77%, respectively.

CONCLUSIONS

The assessment of morphological and enhanced features of breast lesions exhibiting rim enhancement on CEM can improve the differentiation between benign and malignant breast lesions.

ADVANCES IN KNOWLEDGE

This article provides a reference for the differential diagnosis of ring enhanced lesions on CEM.

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer

RATIONALE AND OBJECTIVES

To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer.

MATERIALS AND METHODS

In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio. Deep learning models, based on the pre-trained ResNet34 model and initially fine-tuned for identifying breast cancer, were trained using low-energy and subtracted CESM images. The predicted results served as deep learning features for the deep learning-based model. Clinical-pathological features, including age, progesterone receptor (PR) status, estrogen receptor (ER) status, Ki67 expression levels, and neutrophil-to-lymphocyte ratio, were used for the clinical model. All these features contributed to the nomogram. Feature selection was performed through univariate analysis. Logistic regression models were developed and chosen using a stepwise selection method. The deep learning-based and clinical models, along with the nomogram, were evaluated using precision-recall curves, receiver operating characteristic (ROC) curves, specificity, recall, accuracy, negative predictive value, positive predictive value (PPV), balanced accuracy, F1-score, and decision curve analysis (DCA).

RESULTS

The nomogram demonstrated considerable predictive ability, with higher area under the ROC curve (0.95, P < 0.05), accuracy (0.94), specificity (0.98), PPV (0.89), and precision (0.89) compared to the deep learning-based and clinical models. In DCA, the nomogram showed substantial clinical value in assisting breast cancer treatment decisions, exhibiting a higher net benefit than the other models.

CONCLUSION

The nomogram, integrating CESM deep learning with clinical-pathological features, proved valuable for predicting NAC response in patients with ER-positive/HER2-negative breast cancer. Nomogram outperformed deep learning-based and clinical models.

The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis

Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.

The Role of Contrast-Enhanced Mammography After Cryoablation of Breast Cancer

Image-guided cryoablation is an emerging therapeutic technique for the treatment of breast cancer and is a treatment strategy that is an effective alternate to surgery in select patients. Tumor features impacting the efficacy of cryoablation include size, location in relation to skin, and histology (e.g., extent of intraductal component), underscoring the importance of imaging for staging and workup in this patient population. Contrast-enhanced mammography (CEM) utilization is increasing in both the screening and diagnostic settings and may be useful for follow-up imaging after breast cancer cryoablation, given its high sensitivity for cancer detection and its advantages in terms of PPV, time, cost, eligibility, and accessibility compared with contrast-enhanced MRI. This Clinical Perspective describes the novel use of CEM after breast cancer cryoablation, highlighting the advantages and disadvantages of CEM compared with alternate imaging modalities, expected benign postablation CEM findings, and CEM findings suggestive of residual or recurrent tumor.

Contrast-enhanced breast imaging: Current status and future challenges

BACKGROUND

Contrast-enhanced breast MRI and recently also contrast-enhanced mammography (CEM) are available for breast imaging. The aim of the current overview is to explore existing evidence and ongoing challenges of contrast-enhanced breast imaging.

METHODS

This narrative provides an introduction to the contrast-enhanced breast imaging modalities breast MRI and CEM. Underlying principle, techniques and BI-RADS reporting of both techniques are described and compared, and the following indications and ongoing challenges are discussed: problem-solving, high-risk screening, supplemental screening in women with extremely dense breast tissue, breast implants, neoadjuvant systemic therapy (NST) response monitoring, MRI-guided and CEM- guided biopsy.

RESULTS

Technique and reporting for breast MRI are standardised, for the newer CEM standardisation is in progress. Similarly, compared to other modalities, breast MRI is well established as superior for problem-solving, screening women at high risk, screening women with extremely dense breast tissue or with implants; and for monitoring response to NST. Furthermore, MRI-guided biopsy is a reliable technique with low long-term false negative rates. For CEM, data is as yet either absent or limited, but existing results in these settings are promising.

CONCLUSION

Contrast-enhanced breast imaging achieves highest diagnostic performance and should be considered essential. Of the two contrast-enhanced modalities, evidence of breast MRI superiority is ample, and preliminary results on CEM are promising, yet CEM warrants further study.

Is contrast-enhanced mammography (CEM) an alternative to MRI in assessing the response to primary systemic therapy of breast cancer?

PURPOSE

To evaluate the accuracy of contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) in the assessing radiological response to primary systemic therapy (PST).

METHOD

Prospective study between February 2021 and October 2022. Women with breast cancer and indication of PST were enrolled. CEM and MRI were performed before and after PST, and the findings, including size and radiological response pattern, were compared with the size of the residual lesion measured in surgical specimens and its Miller-Payne classification (considered the gold standard). Two of four independent radiologists, with 2 years of CEM experience and 10 years of MRI experience, reviewed the images while being blinded to the results of the other technique. The agreement between measurements was evaluated using the Pearson correlation coefficient (r) and Lin's coefficient.

RESULTS

Forty-eight women with breast cancer who required PST were enrolled in the study, with a mean age of 57.21 ± 10.14 years. A total of thirty-three participants (68.75 %) completed the study. The correlation between CEM and MRI measurements was high before PST (r: 0.97), and local staging was identical for 45 out of 48 patients. MRI demonstrated better accuracy in predicting residual tumor size than CEM, with Lin's coefficient 0.91 and 0.73, respectively. However, no significant differences were observed in predicting response to therapy. Both methods tended to overestimate the size and degree of response in our study, with mean overestimations of 2.87 mm in CEM and 0.51 mm in MRI.

CONCLUSION

CEM was found to be as accurate as MRI in predicting response to PST, indicating its potential as an alternative imaging technique, but further research is necessary.

Head-to-head comparison of contrast-enhanced mammography and contrast-enhanced MRI for assessing pathological complete response to neoadjuvant therapy in patients with breast cancer: a meta-analysis

OBJECTIVE

Breast cancer patients receiving neoadjuvant therapy (NAT) are in need of a more patient-friendly imaging modality such as contrast-enhanced mammography (CEM) for monitoring therapy response. The purpose of this study was to conduct a meta-analysis to compare the diagnostic performances of CEM and contrast-enhanced magnetic resonance imaging (CE-MRI) for assessing pathological complete response (pCR) in these patients.

METHODS

The PubMed, Embase, and Cochrane Library databases were searched through March 2023 to identify studies reporting a head-to-head comparison of CEM and CE-MRI in detecting pCR in breast cancer patients receiving NAT. Pooled diagnostic performance was calculated using a bivariate random-effects model, and an AUC was derived for each test from hierarchic summary ROC analysis.

RESULTS

Six studies with 328 patients were included. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were 93% (95% CI 84-97%), 68% (95% CI 60-76%), and 29.29 (95% CI 11.41-75.18) for CEM versus 84% (95% CI 62-95%), 80% (95% CI 71-87%), and 21.39 (95% CI 5.94-77.13) for CE-MRI. The AUC was 0.85 (95% CI 0.82-0.88) for CEM and 0.85 (95% CI 0.82-0.88) for CE-MRI.

CONCLUSION

This meta-analysis of head-to-head comparison studies showed that CEM provides an equivalent diagnostic accuracy to CE-MRI in identification of pCR in breast cancer patients receiving NAT. The results support the increasing use of CEM in this setting and would encourage future studies to validate CEM as a suitable replacement for MRI.

Investigation of test methods for QC in dual-energy based contrast-enhanced digital mammography systems: I. Iodine signal testing

The technique of dual-energy contrast enhanced mammography (CEM) visualizes iodine uptake in cancerous breast lesions following an intravenous injection of a contrast medium. The CEM image is generated by recombining two images acquired in rapid succession: a low energy image, with a mean energy below the iodine K-edge, and a higher energy image. The first part of this study examines the use of both commercially available and custom made phantoms to investigate iodine imaging under different imaging conditions, with the focus on quality control (QC) testing. Four CEM equipped systems were included in the study, with units from Fujifilm, GE Healthcare, Hologic and Siemens-Healthineers. The CEM parameters assessed in part I were: (1) image signal as a function of iodine concentration, measured in breast tissue simulating backgrounds of varying thickness and adipose/glandular compositions; (2) normal breast texture cancellation in homogeneous and structured backgrounds; (3) visibility of iodinated structures. For all four systems, a linear response to iodine concentration was found but the degree to which this was independent of background composition differed between the systems. Good cancellation of the glandular tissue inserts was found on all the units. Visibility scores of iodinated targets were similar between the four systems. Specialized phantoms are needed to fully evaluate important CEM performance markers, such as system response to iodine concentration and the ability of the system to cancel background texture. An extensive evaluation of the iodine signal imaging performance is recommended at the Commissioning stage for a new CEM device.

Intra- and Peritumoral Radiomics of Contrast-Enhanced Mammography Predicts Axillary Lymph Node Metastasis in Patients With Breast Cancer: A Multicenter Study

RATIONALE AND OBJECTIVES

This multicenter study aimed to explore the feasibility of radiomics based on intra- and peritumoral regions on preoperative breast cancer contrast-enhanced mammography (CEM) to predict axillary lymph node (ALN) metastasis.

MATERIALS AND METHODS

A total of 809 patients with preoperative breast cancer CEM images from two centers were retrospectively recruited. Least absolute shrinkage and selection operator (LASSO) regression was used to select radiomics features extracted from CEM images in regions of the tumor and peritumoral area of five and ten mm as well as construct radiomics signature. A nomogram, including the optimal radiomics signature and clinicopathological factors, was then constructed. Nomogram performance was evaluated using AUC and compared with breast radiologists directly.

RESULTS

In the internal testing set, AUCs of peritumoral signatures decreased when the peritumoral area increased and signaturetumor + 10mm demonstrated the best performance with an AUC of 0.712. The nomogram incorporating signaturetumor + 10mm, tumor diameter, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and CEM-reported lymph node status yielded maximum AUCs of 0.753 and 0.732 in internal and external testing sets, respectively. Moreover, the nomogram outperformed radiologists and improved diagnostic performance of radiologists.

CONCLUSION

The nomogram based on CEM intra- and peritumoral regions may provide a noninvasive auxiliary tool to guide treatment strategy of ALN metastasis in breast cancer.

Predicting the response to neoadjuvant chemotherapy. Can the addition of tomosynthesis improve the accuracy of contrast-enhanced spectral mammography? A comparison with breast MRI

OBJECTIVES

Image monitoring is essential to monitor response to neoadjuvant chemotherapy (NACT). Whilst breast MRI is the gold-standard technique, evidence suggests contrast-enhanced spectral mammography (CESM) is comparable. We investigate whether the addition of digital breast tomosynthesis (DBT) to CESM increases the accuracy of response prediction.

METHODS

Women receiving NACT for breast cancer were included. Imaging with CESM+DBT and MRI was performed post-NACT. Imaging appearance was compared with pathological specimens. Accuracy for predicting pathological complete response (pCR) and concordance with size of residual disease was calculated.

RESULTS

Sixteen cancers in 14 patients were included, 10 demonstrated pCR. Greatest accuracy for predicting pCR was with CESM enhancement (accuracy: 81.3%, sensitivity: 100%, specificity: 57.1%), followed by MRI (accuracy: 62.5%, sensitivity: 44.4%, specificity: 85.7%). Concordance with invasive tumour size was greater for CESM enhancement than MRI, concordance-coefficients 0.70 vs 0.66 respectively. MRI demonstrated greatest concordance with whole tumour size followed by CESM+microcalcification, concordance coefficients 0.86 vs 0.69. DBT did not improve accuracy for prediction of pCR or residual disease size. CESM+DBT underestimated size of residual disease, MRI overestimated but no significant differences were seen (p>0.05).

CONCLUSIONS

CESM is similar to MRI for predicting residual disease post-NACT. Size of enhancement alone demonstrates best concordance with invasive disease. Inclusion of residual microcalcification improves concordance with ductal carcinoma in situ. The addition of DBT to CESM does not improve accuracy.

ADVANCES IN KNOWLEDGE

The addition ofDBT to CESM does not improve NACT response prediction.CESM enhancement has greatest accuracy for residual invasive disease, CESM+calcification has greater accuracy for residual in situ disease.

ACR Appropriateness Criteria® Monitoring Response to Neoadjuvant Systemic Therapy for Breast Cancer: 2022 Update

Imaging plays a vital role in managing patients undergoing neoadjuvant chemotherapy, as treatment decisions rely heavily on accurate assessment of response to therapy. This document provides evidence-based guidelines for imaging breast cancer before, during, and after initiation of neoadjuvant chemotherapy. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Contrast-enhanced mammography in the assessment of residual disease after neoadjuvant treatment

PURPOSE

To investigate the utility of contrast-enhanced mammography (CEM) as an alternative to breast MRI for the evaluation of residual disease after neoadjuvant treatment (NAT).

METHODS

This prospective study enrolled consecutive women undergoing NAT for breast cancer from July 2017-July 2019. Breast MRI and CEM exams performed after completion of NAT were read independently by two breast radiologists. Residual disease and lesion size on MRI and CEM recombined (RI) and low-energy images (LEI) were compared. Histopathology was considered the reference standard. Statistical analysis was performed using McNemar's and Leisenring's tests. Multiple comparison adjustment was made using Bonferroni procedure. Lesion sizes were correlated using Kendall's tau coefficient.

RESULTS

There were 110 participants with 115 breast cancers. Residual disease (invasive cancer or ductal carcinoma in situ) was detected in 83/115 (72%) lesions on pathology, 71/115 (62%) on MRI, 55/115 (48%) on CEM RI, and 75/115 (65%) on CEM LEI. When using multiple comparison adjustment, no significant differences were detected between MRI combined with CEM LEI and CEM RI combined with CEM LEI, in terms of accuracy (MRI: 77%, CEM: 72%; p ≥ 0.99), sensitivity (MRI: 88%, CEM: 81%; p ≥ 0.99), specificity (MRI: 47%, CEM: 50%; p ≥ 0.99), PPV (MRI: 81%, CEM: 81%; p ≥ 0.99), or NPV (MRI: 60%, CEM: 50%; p ≥ 0.99). Size correlation between pathology and both MRI combined with CEM LEI and CEM RI combined with CEM LEI was moderate: τ = 0. 36 vs 0.33 (p ≥ 0.99).

CONCLUSION

Contrast-enhanced mammography is an acceptable alternative to breast MRI for the detection of residual disease after neoadjuvant treatment.

Invasive Lobular Carcinoma: A Review of Imaging Modalities with Special Focus on Pathology Concordance

Invasive lobular cancer (ILC) is the second most common type of breast cancer. It is characterized by a unique growth pattern making it difficult to detect on conventional breast imaging. ILC can be multicentric, multifocal, and bilateral, with a high likelihood of incomplete excision after breast-conserving surgery. We reviewed the conventional as well as newly emerging imaging modalities for detecting and determining the extent of ILC- and compared the main advantages of MRI vs. contrast-enhanced mammogram (CEM). Our review of the literature finds that MRI and CEM clearly surpass conventional breast imaging in terms of sensitivity, specificity, ipsilateral and contralateral cancer detection, concordance, and estimation of tumor size for ILC. Both MRI and CEM have each been shown to enhance surgical outcomes in patients with newly diagnosed ILC that had one of these imaging modalities added to their preoperative workup.

Deformable registration with intensity correction for CESM monitoring response to Neoadjuvant Chemotherapy

This paper proposes a robust longitudinal registration method for Contrast Enhanced Spectral Mammography in monitoring neoadjuvant chemotherapy. Because breast texture intensity changes with the treatment, a non-rigid registration procedure with local intensity compensations is developed. The approach allows registering the low energy images of the exams acquired before and after the chemotherapy. The measured motion is then applied to the corresponding recombined images. The difference of registered images, called residual, makes vanishing the breast texture that did not changed between the two exams. Consequently, this registered residual allows identifying local density and iodine changes, especially in the lesion area. The method is validated with a synthetic NAC case where ground truths are available. Then the procedure is applied to 51 patients with 208 CESM image pairs acquired before and after the chemotherapy treatment. The proposed registration converged in all 208 cases. The intensity-compensated registration approach is evaluated with different mathematical metrics and through the repositioning of clinical landmarks (RMSE: 5.9 mm) and outperforms state-of-the-art registration techniques.

Multimodality Imaging Review of HER2-positive Breast Cancer and Response to Neoadjuvant Chemotherapy

Human epidermal growth factor receptor 2 (HER2/neu or ErbB2)-positive breast cancers comprise 15%-20% of all breast cancers. The most common manifestation of HER2-positive breast cancer at mammography or US is an irregular mass with spiculated margins that often contains calcifications; at MRI, HER2-positive breast cancer may appear as a mass or as nonmass enhancement. HER2-positive breast cancers are often of intermediate to high nuclear grade at histopathologic analysis, with increased risk of local recurrence and metastases and poorer overall prognosis. However, treatment with targeted monoclonal antibody therapies such as trastuzumab and pertuzumab provides better local-regional control and leads to improved survival outcome. With neoadjuvant treatments, including monoclonal antibodies, taxanes, and anthracyclines, women are now potentially able to undergo breast conservation therapy and sentinel lymph node biopsy versus mastectomy and axillary lymph node dissection. Thus, the radiologist's role in assessing the extent of local-regional disease and response to neoadjuvant treatment at imaging is important to inform surgical planning and adjuvant treatment. However, assessment of treatment response remains difficult, with the potential for different imaging modalities to result in underestimation or overestimation of disease to varying degrees when compared with surgical pathologic analysis. In particular, the presence of calcifications at mammography is especially difficult to correlate with the results of pathologic analysis after chemotherapy. Breast MRI findings remain the best predictor of pathologic response. The authors review the initial manifestations of HER2-positive tumors, the varied responses to neoadjuvant chemotherapy, and the challenges in assessing residual cancer burden through a multimodality imaging review with pathologic correlation. ^© RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.

Feasibility of contrast-enhanced mammography in women with breast implants

Contrast-enhanced mammography (CEM) may provide an alternative to magnetic resonance imaging as a diagnostic exam in women with known or suspected breast cancer or as a screening exam in women at increased risk of breast cancer. Women with breast augmentation, either for oncologic or cosmetic reasons, may fall into this increased risk population and need safe and effective screening and diagnostic imaging tools. Here, we present our clinical practice data in order to demonstrate the feasibility of CEM in women with breast implants. An institutional review board-approved, Health Insurance Portability and Accountability Act-compliant, retrospective review of our tertiary cancer center's database yielded 104 women with breast implants who underwent 198 CEM exams from November 2014 to March 2020. All 198/198 (100%) exams were successfully completed in 104 women. Exam indications included: 174/198 (88%) screening due to increased risk, 10/198 (5%) to evaluate a palpable abnormality, 9/198 (<5%) to evaluate disease extent following neoadjuvant chemotherapy for a known breast malignancy, and 5/198 (<3%) for a 6-month follow-up. 97/104 (93%) women had dense breasts. Routine and implant-displaced low-energy views were obtained with contrast-enhanced images obtained on displaced views for all patients. 197/198 (99.5%) exams yielded no complications. In one exam, the patient experienced mild vasovagal symptoms following the administration of contrast. In conclusion, it is feasible to utilize CEM in both diagnostic and screening capacities in women with breast implants.

Assessment and Response to Neoadjuvant Treatments in Breast Cancer: Current Practice, Response Monitoring, Future Approaches and Perspectives

Neoadjuvant treatments (NAT) for breast cancer (BC) consist in the administration of chemotherapy-more rarely endocrine therapy-before surgery. Firstly, it was introduced 50 years ago to downsize locally advanced (inoperable) BCs. NAT are now widespread and so effective to be used also at the early stage of the disease. NAT are heterogeneous in terms of therapeutic patterns, class of used drugs, dosage, and duration. The poly-chemotherapy regimen and administration schedule are established by a multi-disciplinary team, according to the stage of disease, the tumor subtype and the age, the physical status, and the drug sensitivity of BC patients. Consequently, an accurate monitoring of treatment response can provide significant clinical advantages, such as the treatment de-escalation in case of early recognition of complete response or, on the contrary, the switch to an alternative treatment path in case of early detection of resistance to the ongoing therapy. Future is going toward increasingly personalized therapies and the prediction of individual response to treatment is the key to practice customized care pathways, preserving oncological safety and effectiveness. To gain such goal, the development of an accurate monitoring system, reproducible and reliable alone or as part of more complex diagnostic algorithms, will be promising.

Patient perspectives on repeated contrast-enhanced mammography and magnetic resonance during neoadjuvant chemotherapy of breast cancer

BACKGROUND

The burden perceived by the patient of repeated imaging required for neoadjuvant chemotherapy (NAC) monitoring warrants attention due to the increased use of NAC and imaging.

PURPOSE

To evaluate and compare the experienced burden associated with repeated contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) during NAC for breast cancer from the patient perspective.

MATERIAL AND METHODS

Approval from the ethics committee and written informed consent were obtained. In this prospective study, CEM and MRI were performed on 38 patients with breast cancer before, during, and after NAC in a tertiary cancer center. The experienced burden was evaluated with a self-reported questionnaire addressing duration, comfort, anxiety, positioning, and intravenous contrast administration, each measured on a 5-point Likert scale. The participants were asked their preference between CEM or MRI. Statistical comparisons were performed and P<0.05 was considered significant.

RESULTS

Most participants (n = 29, 76%) preferred CEM over MRI (P = 0.0008). CEM was associated with a significantly shorter duration (P < 0.001), greater overall comfort (P < 0.01), more comfortable positioning (P = 0.01), and lower anxiety (P = 0.03). Intravenous contrast administration perception revealed no significant difference. Only 4 (10%) participants preferred MRI over CEM, due to the absence of breast compression.

CONCLUSION

In the hypothetical scenario of equal diagnostic accuracy, most participants preferred CEM and compared CEM favorably to MRI in all investigated features at repeated imaging required for NAC response assessment. Our results indicate that repeated examinations with CEM is well tolerated and constitutes a patient-friendly alternative for NAC imaging monitoring in breast cancer.

Contrast-Enhanced Mammography Versus MRI in the Evaluation of Neoadjuvant Therapy Response in Patients With Breast Cancer: A Prospective Study

BACKGROUND. Contrast-enhanced mammography (CEM) is rapidly expanding as a credible alternative to MRI in various clinical settings. OBJECTIVE. The purpose of this study was to compare CEM and MRI for neoadjuvant therapy (NAT) response assessment in patients with breast cancer. METHODS. This prospective study included 51 patients (mean age, 46 ± 11 [SD] years) with biopsy-proven breast cancer who were candidates for NAT from May 2015 to April 2018. Patients underwent both CEM and MRI before, during, and after NAT (pre-NAT, mid-NAT, and post-NAT, respectively). Post-NAT CEM included a 6-minute delayed acquisition. One breast radiologist with experience in CEM reviewed CEM examinations; one breast radiologist with experience in MRI reviewed MRI examinations. The radiologists assessed for the presence of an enhancing lesion; if an enhancing lesion was detected, its size was measured. RECIST version 1.1 response assessment categories were derived. Pathologic complete response (pCR) was defined as absence of both invasive cancer and ductal carcinoma in situ (DCIS). RESULTS. Of 51 patients, 16 achieved pCR. CEM yielded systematically lower size measurements compared with MRI (mean difference, -0.2 mm for pre-NAT, -0.7 mm for mid-NAT, and -0.3 mm for post-NAT). All post-NAT imaging tests yielded systematically larger size measurements compared with pathology (mean difference, 0.8 mm for CEM, 1.2 mm for MRI, and 1.9 mm for delayed CEM). Of 12 patients with residual DCIS, an enhancing lesion was detected in seven on post-NAT CEM, eight on post-NAT MRI, and nine on post-NAT delayed CEM. Agreement of RECIST response categories between CEM and MRI, expressed as kappa coefficient, was 0.791 at mid-NAT and 0.871 at post-NAT. For detecting pCR by post-NAT imaging, sensitivity and specificity were 81% and 83% for CEM, 100% and 86% for MRI, and 81% and 89% for delayed CEM. Sensitivity was significantly higher for MRI than CEM (p = .001) and delayed CEM (p = .002); remaining comparisons were not significant (p > .05). CONCLUSION. After NAT for breast cancer, CEM and MRI yielded comparable assessments of lesion size (both slightly overestimated vs pathology) and RECIST categories and showed no significant difference in specificity for pCR. MRI had higher sensitivity for pCR. Delayed CEM acquisition may help detect residual DCIS. CLINICAL IMPACT. Although MRI remains the preferred test for NAT response monitoring, the findings support CEM as a useful alternative when MRI is contraindicated or not tolerated.

Applying artificial intelligence technology to assist with breast cancer diagnosis and prognosis prediction

Breast cancer remains the most diagnosed cancer in women. Advances in medical imaging modalities and technologies have greatly aided in the early detection of breast cancer and the decline of patient mortality rates. However, reading and interpreting breast images remains difficult due to the high heterogeneity of breast tumors and fibro-glandular tissue, which results in lower cancer detection sensitivity and specificity and large inter-reader variability. In order to help overcome these clinical challenges, researchers have made great efforts to develop computer-aided detection and/or diagnosis (CAD) schemes of breast images to provide radiologists with decision-making support tools. Recent rapid advances in high throughput data analysis methods and artificial intelligence (AI) technologies, particularly radiomics and deep learning techniques, have led to an exponential increase in the development of new AI-based models of breast images that cover a broad range of application topics. In this review paper, we focus on reviewing recent advances in better understanding the association between radiomics features and tumor microenvironment and the progress in developing new AI-based quantitative image feature analysis models in three realms of breast cancer: predicting breast cancer risk, the likelihood of tumor malignancy, and tumor response to treatment. The outlook and three major challenges of applying new AI-based models of breast images to clinical practice are also discussed. Through this review we conclude that although developing new AI-based models of breast images has achieved significant progress and promising results, several obstacles to applying these new AI-based models to clinical practice remain. Therefore, more research effort is needed in future studies.

Accuracy of Posttreatment Imaging for Evaluation of Residual in Breast Disease After Neoadjuvant Endocrine Therapy

BACKGROUND

Neoadjuvant endocrine therapy (NET) can help downstage certain breast cancers prior to surgical resection. This study measured the accuracy of conventional mammography (MMG), ultrasound (US), magnetic resonance imaging (MRI), and contrast-enhanced mammography (CEM) for assessing breast tumor size in response to NET.

PATIENTS AND METHODS

Patients who underwent surgery after NET from 2013 to 2021 were identified. The maximal dimension of residual tumor on imaging was compared with the maximal dimension on final pathology. Lin's concordance correlation coefficient (r_c) and Spearman's rank correlation coefficient (r) were used to assess agreement.

RESULTS

In total, 119 patients with invasive breast cancer underwent NET, posttreatment imaging, and surgery. Tumor size reported on posttreatment CEM correlated with size on final pathology to within 1 cm in n = 42 (58%) of patients, equivalent to the accuracy of MRI (n = 35, 58%). Size was accurately predicted by US in 54% and in 48% of MMG. Posttreatment imaging tumor size was moderately correlated with final tumor size on pathology CEM (r = 0.49; r_c = 0.38), MRI (r = 0.52; r_c = 0.45), and US (r = 0.41; r_c = 0.28). MMG was weakly correlated (r = 0.21; r_c = 0.16). Similar findings were shown in subgroup analysis; in those who received all four post-NET imaging, CEM and MRI again performed comparably, with r = 0.36 and 0.41, respectively, US (r = 0.43) and MMG (r = 0.28).

CONCLUSIONS

Compared with mammography and US, CEM and MRI had higher accuracy in estimating final tumor size for breast cancers treated with NET. Contrast-enhanced imaging is a helpful adjunct when response to preoperative therapy will impact clinical management.

Impact of contrast-enhanced mammography in surgical management of breast cancers for women with dense breasts: a dual-center, multi-disciplinary study in Asia

OBJECTIVE

To evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts.

METHODS

We conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.2) who underwent pre-surgical CEM imaging across two Asian institutions (Singapore and Taiwan). Majority (95.5%) of patients had dense breast tissue (BI-RADS category C or D). Surgical decision was recorded in a simulated blinded multi-disciplinary team setting on two separate scenarios: (i) pre-CEM setting with standard imaging, and clinical and histopathological results; and (ii) post-CEM setting with new imaging and corresponding histological findings from CEM. Alterations in surgical plan (if any) because of CEM imaging were recorded. Predictors CEM of patients who benefitted from surgical plan alterations were evaluated using logistic regression.

RESULTS

CEM resulted in altered surgical plans in 36 (18%) of 200 patients in this study. CEM discovered clinically significant larger tumor size or extent in 24 (12%) patients and additional tumors in 12 (6%) patients. CEM also detected additional benign/false-positive lesions in 13 (6.5%) of the 200 patients. Significant predictors of patients who benefitted from surgical alterations found on multivariate analysis were pre-CEM surgical decision for upfront breast conservation (OR, 7.7; 95% CI, 1.9-32.1; p = 0.005), architectural distortion on mammograms (OR, 7.6; 95% CI, 1.3-42.9; p = .022), and tumor size of ≥ 1.5 cm (OR, 1.5; 95% CI, 1.0-2.2; p = .034).

CONCLUSION

CEM is an effective imaging technique for pre-surgical planning for Asian breast cancer patients with dense breasts.

KEY POINTS

• CEM significantly altered surgical plans in 18% (nearly 1 in 5) of this Asian study cohort with dense breasts. • Significant patient and imaging predictors for surgical plan alteration include (i) patients considered for upfront breast-conserving surgery; (ii) architectural distortion lesions; and (iii) tumor size of ≥ 1.5 cm. • Additional false-positive/benign lesions detected through CEM were uncommon, affecting only 6.5% of the study cohort.

Preoperative evaluation of breast cancer: Contrast-enhanced mammography versus contrast-enhanced magnetic resonance imaging: A systematic review and meta-analysis

INTRODUCTION

Breast cancer is the most common cancer in women worldwide. It is responsible for about 23% of cancer in females in both developed and developing countries. This study aimed to compare the diagnostic performance of contrast-enhanced mammography (CEM) and contrast-enhanced magnetic resonance imaging (CEMRI) in preoperative evaluations of breast lesions.

METHODS

We searched for published literature in the English language in MEDLINE via PubMed and EMBASETM via Ovid, The Cochrane Library, and Trip database. For literature published in other languages, we searched national databases (Magiran and SID), KoreaMed, and LILACS. Metadisc1.4 software was used for statistical analysisRESULTS:A total of 1225 patients were included. The pooled sensitivity of CEM and CEMRI was 0.946 (95% CI, 0.931-0.958) and 0.935 (95% CI, 0.920-0.949), respectively. The pooled specificity of CEM and CEMRI was 0.783 (95% CI, 0.758-0.807) and 0.715 (95% CI, 0.688-0.741), respectively. The sensitivity of CEM was the most in the United States (97%) and the specificity of CEM was the most in Brazil (88%). MRI sensitivity was the most in USA and Egypt (99%) and China had the most MRI specificity (81%) in diagnosis of breast lesions.

CONCLUSION

Contrast-enhanced mammography, a combination of high energy image and low energy image, can well display breast lesions and has the diagnostic efficacy equivalent to MRI. Importantly, CEM imaging shows higher specificity, positive predictive value, and diagnostic conformance rate than MRI. Despite some drawbacks such as higher irradiation and iodine usage, CEM has such advantages as convenient and fast examination, strong applicability, and low costs; thus, it can be popularized as a useful tool in breast disease.

Contrast-enhanced digital breast tomosythesis and breast MRI to monitor response to neoadjuvant chemotherapy: patient tolerance and preference

OBJECTIVE

Contrast-enhanced digital breast tomosynthesis (CE-DBT) is a novel imaging technique, combining contrast-enhanced spectral mammography and tomosynthesis. This may offer an alternative imaging technique to breast MRI for monitoring of response to neoadjuvant chemotherapy. This paper addresses patient experience and preference regarding the two techniques.

METHODS

Conducted as part of a prospective pilot study; patients were asked to complete questionnaires pertaining to their experience of CE-DBT and MRI following pre-treatment and end-of-treatment imaging. Questionnaires consisted of eight questions answered on a categorical scale, two using a visual analogue scale (VAS), and a question to indicate preference of imaging technique. Statistical analysis was performed with Wilcoxon signed rank test and McNemar test for related samples using SPSS v. 25.

RESULTS

18 patients were enrolled in the pilot study. Matched CE-DBT and MRI questionnaires were completed after 22 patient episodes. Patient preference was indicated after 31 patient episodes. Overall, on 77% of occasions patients preferred CE-DBT with no difference between pre-treatment and end-of-treatment imaging. Overall experience (p = 0.008), non-breast pain (p = 0.046), anxiety measured using VAS (p = 0.003), and feeling of being put at ease by staff (p = 0.023) was better for CE-DBT. However, more breast pain was experienced during CE-DBT when measured on both VAS (p = 0.011) and categorical scale (p = 0.021).

CONCLUSION

Our paper suggests that patients prefer CE-DBT to MRI, adding further evidence in favour of contrast-enhanced mammographic techniques.

ADVANCES IN KNOWLEDGE

Contrast mammographic techniques offer an alternative, more accessible imaging technique to breast MRI. Whilst other studies have addressed patient experience of contrast-enhanced spectral mammography, this is the first study to directly explore patient preference for CE-DBT over MRI in the setting of neoadjuvant chemotherapy, finding that overall, patients preferred CE-DBT despite the relatively long breast compression.

Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.

Three-Dimensional H-Scan Ultrasound Imaging of Early Breast Cancer Response to Neoadjuvant Therapy in a Murine Model

OBJECTIVES

Three-dimensional (3D) H-scan is a new ultrasound (US) technique that images the relative size of acoustic scatterers. The goal of this research was to evaluate use of 3D H-scan US imaging for monitoring early breast cancer response to neoadjuvant therapy using a preclinical murine model of breast cancer.

MATERIALS AND METHODS

Preclinical studies were conducted using luciferase-positive breast cancer-bearing mice (n = 40). Anesthetized animals underwent US imaging at baseline before administration with an apoptosis-inducing drug or a saline control. Image data were acquired using a US scanner equipped with a volumetric transducer following either a shorter- or longer-term protocol. The later included bioluminescent imaging to quantify tumor cell viability. At termination, tumors were excised for ex vivo analysis.

RESULTS

In vivo results showed that 3D H-scan US imaging is considerably more sensitive to tumor changes after apoptosis-inducing drug therapy as compared with traditional B-scan US. Although there was no difference at baseline (P > 0.99), H-scan US results from treated tumors exhibited progressive decreases in image intensity (up to 62.2% by day 3) that had a significant linear correlation with cancer cell nuclear size (R2 > 0.51, P < 0.001). Results were validated by histological data and a secondary longitudinal study with survival as the primary end point.

DISCUSSION

Experimental results demonstrate that noninvasive 3D H-scan US imaging can detect an early breast tumor response to apoptosis-inducing drug therapy. Local in vivo H-scan US image intensity correlated with cancer cell nuclear size, which is one of the first observable changes of a cancer cell undergoing apoptosis and confirmed using histological techniques. Early imaging results seem to provide prognostic insight on longer-term tumor response. Overall, 3D H-scan US imaging is a promising technique that visualizes the entire tumor and detects breast cancer response at an early stage of therapy.

Single Center Evaluation of Comparative Breast Radiation dose of Contrast Enhanced Digital Mammography (CEDM), Digital Mammography (DM) and Digital Breast Tomosynthesis (DBT)

RATIONALE AND OBJECTIVES

The aim of this retrospective study is to compare the radiation dose received during CEDM, short and long protocol (CEDM SP and CEDM LP), with dose received during DM and DBT on patients with varying breast thickness, age and density.

MATERIALS AND METHODS

Between January 2019 and December 2019, patients having 6214 DM, 3662 DBT and 173 CEDM examinations in our department were analyzed. Protocol total single breast AGD has been evaluated for all clinical imaging protocols, extracting AGD values and exposure data from the dose DICOM Structured Report (SR) information stored in the hospital PACS system. Protocol AGD was calculated as the sum of single projection AGDs carried out in every exam for each clinical protocol. A total amount of 23,383 exams for each breast were analyzed. Protocol AGDs, stratified as a function of patient breast compression thickness, age, and breast density were assessed.

RESULTS

The total protocol AGD median values for each protocol are: 2.8 mGy for DM, 3.2 mGy for DBT, 6.0 mGy for DM+DBT, 4.5 mGy for CEDM SP, 7.4 mGy for CEDM SP_DBT (CEDM SP protocol with DBT), 8.4 mGy for CEDM LP and 11.6 mGy for CEDM LP_DBT (CEDM LP protocol with DBT). CEDM SP AGD median value is 59% higher than DM AGD median value and 40% lesser than DM+DBT AGD median; this last difference was statistically confirmed with a p-value <0.001. AGD value for each standard breast CEDM SP projection results to be below 3-mGy limit. AGD value for each standard breast CEDM SP projection results to be below 3 mGy, as required by international legislation. For dense breasts, the AGD median value is 4.2 mGy, with the first and third quartile of 3.3 mGy and 6.0 mGy respectively; for non-dense breasts, the AGD median value is 4.7 mGy, with first and third quartile of 3.5 mGy and 6.3 mGy respectively. The difference between the two groups was statistically tested and confirmed, with a p-value of 0.039.

CONCLUSION

CEDM SP results in higher radiation exposure compared with conventional DM and DBT but lower than the Combo mode. The dose administered during the CEDM SP is lower in patients with dense breasts regardless of their size. An interesting outcome, considering the ongoing studies on CEDM screening in patients with dense breasts.

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.

Current Status of Contrast Enhanced Mammography: A Comprehensive Review

OBJECTIVES

The purpose of this article is to provide a detailed and updated review of the physics, techniques, indications, limitations, reporting, implementation and management of contrast enhanced mammography.

BACKGROUND

Contrast enhanced mammography (CEM), is an emerging iodine-based modified dual energy mammography technique. In addition to having the same advantages as standard full-field digital mammography (FFDM), CEM provides information regarding tumor enhancement, relying on tumor angiogenesis, similar to dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). This article reviews current literature on CEM and highlights considerations that are critical to the successful use of this modality.

CONCLUSION

Multiple studies point to the advantage of using CEM in the diagnostic setting of breast imaging, which approaches that of DCE-MRI.

Contrast-Enhanced Spectral Mammography Assessment of Patients Treated with Neoadjuvant Chemotherapy for Breast Cancer

Background: Evaluating the tumor response to neoadjuvant chemotherapy is key to planning further therapy of breast cancer. Our study aimed to evaluate the effectiveness of low-energy and subtraction contrast-enhanced spectral mammography (CESM) images in the detection of complete response (CR) for neoadjuvant chemotherapy (NAC) in breast cancer. Methods: A total of 63 female patients were qualified for our retrospective analysis. Low-energy and subtraction CESM images just before the beginning of NAC and as a follow-up examination 2 weeks before the end of chemotherapy were compared with one another and assessed for compliance with the postoperative histopathological examination (HP). The response to preoperative chemotherapy was evaluated based on the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumors). Results: Low-energy images tend to overestimate residual lesions (6.28 mm) and subtraction images tend to underestimate them (2.75 mm). The sensitivity of low-energy images in forecasting CR amounted to 33.33%, while the specificity was 92.86%. In the case of subtraction CESM, the sensitivity amounted to 85.71% and the specificity to 71.42%. Conclusions: CESM is characterized by high sensitivity in the assessment of CR after NAC. The use of only morphological assessment is insufficient. CESM correlates well with the size of residual lesions on histopathological examination but tends to underestimate the dimensions.

Contrast-Enhanced Mammography for Newly Diagnosed Breast Cancer in Women With Breast Augmentation: Preliminary Findings

In 17 women with newly diagnosed breast cancer who underwent contrast-enhanced mammography (CEM) and MRI, both modalities were found to be concordant for the index cancer. In six of the 17 women, CEM showed an additional lesion that was confirmed by MRI. Of these six additional lesions, three were multifocal, one was multicentric, and two were contralateral; two of the six were malignant. MRI did not identify any additional cancers that were not identified on CEM. CEM may have a role in women with breast augmentation and either a contraindication or limited access to MRI.

Assessment and Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Imaging Modalities and Future Perspectives

Neoadjuvant chemotherapy (NAC) is becoming the standard of care for locally advanced breast cancer, aiming to reduce tumor size before surgery. Unfortunately, less than 30% of patients generally achieve a pathological complete response and approximately 5% of patients show disease progression while receiving NAC. Accurate assessment of the response to NAC is crucial for subsequent surgical planning. Furthermore, early prediction of tumor response could avoid patients being overtreated with useless chemotherapy sections, which are not free from side effects and psychological implications. In this review, we first analyze and compare the accuracy of conventional and advanced imaging techniques as well as discuss the application of artificial intelligence tools in the assessment of tumor response after NAC. Thereafter, the role of advanced imaging techniques, such as MRI, nuclear medicine, and new hybrid PET/MRI imaging in the prediction of the response to NAC is described in the second part of the review. Finally, future perspectives in NAC response prediction, represented by AI applications, are discussed.

Contrast-enhanced Mammography: How Does It Work?

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

Contrast-enhanced Mammography: State of the Art

Contrast-enhanced mammography (CEM) has emerged as a viable alternative to contrast-enhanced breast MRI, and it may increase access to vascular imaging while reducing examination cost. Intravenous iodinated contrast materials are used in CEM to enhance the visualization of tumor neovascularity. After injection, imaging is performed with dual-energy digital mammography, which helps provide a low-energy image and a recombined or iodine image that depict enhancing lesions in the breast. CEM has been demonstrated to help improve accuracy compared with digital mammography and US in women with abnormal screening mammographic findings or symptoms of breast cancer. It has also been demonstrated to approach the accuracy of breast MRI in preoperative staging of patients with breast cancer and in monitoring response after neoadjuvant chemotherapy. There are early encouraging results from trials evaluating CEM in the screening of women who are at an increased risk of breast cancer. Although CEM is a promising tool, it slightly increases radiation dose and carries a small risk of adverse reactions to contrast materials. This review details the CEM technique, diagnostic and screening uses, and future applications, including artificial intelligence and radiomics.

Quantitative analysis of contrast enhanced spectral mammography grey value for early prediction of pathological response of breast cancer to neoadjuvant chemotherapy

A quantitative analysis of contrast-enhanced spectral mammography (CESM) enhancement was conducted for the early prediction of the pathological response after neoadjuvant chemotherapy (NAC). Retrospective analysis of the data of 111 patients was conducted, and all of them underwent NAC in our hospital and surgical resection after the end of all cycles from January 2018 to May 2019. They were divided into pathological complete response (PCR) and non-PCR groups. We determined whether a statistical difference in the percentage of CESM grey value reduction (ΔCGV) was present in the PCR and non-PCR groups and whether a statistical difference was observed in the diagnostic efficiency of craniocaudal (CC) and mediolateral oblique (MLO) view subtraction images. Independent sample t-test was used to compare different groups, the receiver operating characteristic (ROC) curve was used to compare the diagnostic efficacy of CC and MLO for pathological response after NAC, and the Delong test was used to compare the area under the ROC curve (AUC). Statistical significance was considered at P < 0.05. A statistical difference was observed in the ΔCGV in the PCR and non-PCR groups. No statistical difference was observed in the AUCs of CC and MLO view subtraction images. The ΔCGV can be used as a quantitative index to predict PCR early, and no statistical difference was observed in the diagnostic efficacy of CC and MLO view subtraction images.

Accuracy and Reproducibility of Contrast-Enhanced Mammography in the Assessment of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients with Calcifications in the Tumor Bed

This study aimed to evaluate contrast-enhanced mammography (CEM) accuracy and reproducibility in the detection and measurement of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients with calcifications, using surgical specimen pathology as the reference. Pre- and post-NAC CEM images of 36 consecutive BC patients receiving NAC in 2012–2020, with calcifications in the tumor bed at diagnosis, were retrospectively reviewed by two radiologists; described were absence/presence and size of residual disease based on contrast enhancement (CE) only and CE plus calcifications. Twenty-eight patients (77.8%) had invasive and 5 (13.9%) in situ-only residual disease at surgical specimen pathology. Considering CE plus calcifications instead of CE only, CEM sensitivity for invasive residual tumor increased from 85.7% (95% CI = 67.3–96%) to 96.4% (95% CI = 81.7–99.9%) and specificity decreased from 5/8 (62.5%; 95% CI = 24.5–91.5%) to 1/8 (14.3%; 95% CI = 0.4–57.9%). For in situ-only residual disease, false negatives decreased from 3 to 0 and false positives increased from 1 to 2. CEM pathology concordance in residual disease measurement increased (R squared from 0.38 to 0.45); inter-reader concordance decreased (R squared from 0.79 to 0.66). Considering CE plus calcifications to evaluate NAC response in BC patients increases sensitivity in detection and accuracy in measurement of residual disease but increases false positives.

Contrast mammography in clinical practice: Current uses and potential diagnostic dilemmas

OBJECTIVE

This article will discuss the indications for Contrast Enhanced Spectral Mammography (CESM) with a focus on imaging interpretation including diagnostic dilemmas and pitfalls which may be encountered in practice.

CONCLUSION

Understanding potential diagnostic dilemmas and pitfalls of CESM allows for enhanced interpretation. The clinical utilization of Contrast Enhanced Spectral Mammography (CESM) has increased significantly over the last few years. CESM demonstrates comparable sensitivity and accuracy to magnetic resonance imaging (MRI) for the evaluation of breast cancer but is less time consuming and less expensive. Because of this, CESM is now being used in lieu of MRI for many diagnostic indicators including the evaluation of abnormal mammographic findings, extent of disease, and response to neoadjuvant therapy. Additionally, ongoing research into the role of CESM in asymptomatic screening for breast cancer is evolving. As this technique becomes more popular, focusing on appropriate technique and interpretation is important. This article reviews the current and potential roles of CESM. It provides examples of CESM utilized for diagnostic indications while highlighting diagnostic dilemmas, pitfalls, and artifacts that may be encountered when interpreting CESM images.

Architecture distortion score (ADS) in malignancy risk stratification of architecture distortion on contrast-enhanced digital mammography

OBJECTIVE

To develop a risk predictor model in evaluation of tomosynthesis-detected architectural distortion (AD) based on characteristics of contrast-enhanced digital mammography (CEDM).

METHODS

Ninety-four AD lesions on CEDM in combination with tomosynthesis were retrospectively reviewed from 92 consecutive women (mean age, 52.4 years ± 7.9) with abnormal diagnostic or screening mammography. CEDM results were correlated with histology of ADs using cross-tabulation for statistical analysis. Predictors for risk of malignancy from CEDM characteristics (background parenchyma enhancement, degree of AD enhancement, enhancing morphology, size of enhancement, and enhancing spiculations) and patient's age were evaluated using logistic regression. We propose a sum score, termed AD score (ADS), for risk stratification and corresponding suggested BI-RADS category.

RESULTS

Thirty-three of ninety-four (35.1%) of detected AD lesions were malignant. The sensitivity, specificity, PPV, and NPV of CEDM in evaluation of malignant AD are 100%, 42.6%, 48.5%, and 100%, respectively. Absence of AD enhancement on CEDM is highly indicative of no underlying malignancy. On multivariate analysis, the predictors on CEDM with statistical significance are (1) marked intensity of AD enhancement (OR, 22.6; 95%CI 3.1, 166.6; p = .002); and (2) presence of enhancing spiculations (OR, 9.1; 95%CI 2.2, 36.5; p = .002). A prediction model whose scores (ADS) given by ranking of OR of all predictors with AUC of 0.934 and Brier score of 0.0956 was developed.

CONCLUSION

ADS-based lesion characterization on CEDM enables risk assessment of tomosynthesis-detected AD lesions.

KEY POINTS

• Architecture distortions presenting with marked enhancement intensity and presence of enhancing spiculations are highly associated with risk of malignancy. • Absence of architecture distortion enhancement in minimal or mild background parenchyma enhancement on CEDM indicates low risk of breast malignancy (NPV = 100%).

Contrast-Enhanced Mammography Implementation, Performance, and Use for Supplemental Breast Cancer Screening

Contrast-enhanced mammography (CEM) is an emerging breast imaging technology that provides recombined contrast-enhanced images of the breast in addition to low-energy images analogous to a 2-dimensional full-field digital mammogram. Because most breast imaging centers do not use CEM at this time, a detailed overview of CEM implementation and performance is presented. Thereafter, the potential use of CEM for supplemental screening is discussed in detail, given the importance of this topic for the future of the CEM community. Diagnostic performance, safety, and cost considerations of CEM for dense breast tissue supplemental screening are discussed.

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.

Which clinical, radiological, histological, and molecular parameters are associated with the absence of enhancement of known breast cancers with Contrast Enhanced Digital Mammography (CEDM)?

Background

CEDM has demonstrated a diagnostic performance similar to MRI and could have similar limitations in breast cancer (BC) detection.

Purpose

The aim of our study was to systematically analyze the characteristics of the lesions with the absence of enhancement with CEDMs, called false-negatives (FNs), in order to identify which clinical, radiological, histological and molecular parameters are associated with the absence of enhancement of known BCs with CEDMs, and which types of BC are most likely to cause FNs in CEDMs. We also tried to evaluate which parameters instead increased the probability of showing enhancement in the same context.

Materials and methods

Included in our study group were 348 women with 348 diagnosed BCs performing CEDM as preoperative staging. Two breast-imaging radiologists reviewed the CEDM exams. The absence of perceptible contrast enhancement at the index cancer site was indicative of an FN CEDM, whereas cases with appreciable enhancement were considered true positives (TPs). Dichotomic variables were analyzed with Fisher’s exact probability test or, when applicable, the chi-square test. Binary logistic regression was performed on variables shown to be significant by the univariate analysis in order to assess the relationship between predictors (independent variables) and TFNs (outcome).

Results

Enhancement was observed in 317 (91.1%) of the 348 BCs. From the 31 (8.9%) lesions which were FNs, we excluded 12 (38.7%) which showed an artifact generated by the post biopsy hematoma and 6 (19.4%) which were outside the CEDM field of vision. We thus obtained 13 (41.9%) BCs considered “True False Negatives” (TFNs), i.e. BCs which showed no enhancement despite being within the CEDM field of vision and failed to show post biopsy hematoma artifacts. We found that the TFNs frequently have a unifocal disease extension, diameter <10 mm, a lower number of luminal B HER2-subtypes, a higher number of DCIS, and an index lesion with microcalcifications.

Conclusions

The parameters we found to be associated with no enhancement of known BCs with CEDMs were: unifocal disease extension, DCIS histotype, lesion dimensions <10 mm, and index lesion with microcalcifications. The characteristics that instead increase the probability of showing enhancement were US mass, Luminal B HER2 negative molecular subtype, the presence of an invasive ductal component, and lesion dimensions ≥10 mm.

•

The variables associated with an increased risk of no enhancement were unifocal disease extension, non-classifiable molecular subtype, DCIS histotype, lesion dimensions <10 mm, index lesion represented by microcalcifications.

•

A greater probability of showing enhancement entailed the presence of an invasive ductal component, index lesion represented by ultrasound mass, Luminal B HER2 negative molecular subtype, lesion dimensions ≥10 mm, multifocal disease extension.

The diagnostic performance of CESM and CE-MRI in evaluating the pathological response to neoadjuvant therapy in breast cancer: a systematic review and meta-analysis

OBJECTIVES

Neoadjuvant chemotherapy (NAC) is an important method for breast cancer treatment. By monitoring its pathological response, the selection of clinical treatment strategies can be guided. In this study, the meta-analysis was used to compare the accuracy of contrast-enhanced MRI (CE-MRI) and contrast-enhanced spectral mammography (CESM) in detecting the pathological response of NAC.

METHODS

Literatures associated to CE-MRI and CESM in the evaluation of pathological response of NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool was used to assess the quality of studies. Pooled sensitivity, specificity, and the area under the SROC curve were calculated to evaluate the diagnostic accuracy of CE-MRI and CESM in monitoring the pathological response of NAC.

RESULTS

There were 24 studies involved, 18 of which only underwent CE-MRI examination, three of which only underwent CESM examination, and three of which underwent both CE-MRI and CESM examination. The pooled sensitivity and specificity of CE-MRI were 0.77 (95%CI, 0.67-0.84) and 0.82 (95%CI, 0.73-0.89), respectively. The pooled sensitivity and specificity of CESM were 0.83 (95%CI, 0.66-0.93) and 0.82 (95%CI, 0.68-0.91), respectively. The AUCs of SROC curve for CE-MRI and CESM were 0.86 and 0.89, respectively.

CONCLUSIONS

Compared to CE-MRI, CESM has equal specificity, greater sensitivity and excellent performance, which may have a brighter prospect in evaluating the pathological response of breast cancer to NAC.

ADVANCES IN KNOWLEDGE

CESM showed equal specificity, greater sensitivity, and excellent performance than CE-MRI.

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

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

Contrast-Enhanced Mammography: A Scientific Review

In this paper we provide an overview of contrast-enhanced mammography (CEM) and a review of the published literature in order to provide a picture of the current state of the evidence on the performance of CEM. Clinical research was fairly sparse following the demonstration of the technique in research subjects about 18 years ago, but the number of publications rapidly increased following commercialization 9 years ago, and even more so in the last 5 years. Initial studies compared CEM with mammography, and clearly showed that CEM could detect cancers not visible on mammography. More recent studies have primarily focused on comparing the performance of CEM with contrast-enhanced magnetic resonance imaging (MRI) in selected cohorts. These studies have almost uniformly shown CEM and MRI to have similar sensitivities, with sensitivity and accuracy showing more variability from study to study. With increasing clinical use, a large number of retrospective reviews of CEM have appeared, showing utility of CEM in the diagnostic clinical setting. Most recently, a small number of papers have been published looking at CEM for high-risk and dense breast screening, two potentially large applications of the technique, showing it to outperform mammography in both populations. CEM has clearly been shown to have clinical utility, but more prospective studies, including screening studies, are needed to further evaluate its performance, especially in comparison with MRI.