Diagnostic performance of dual-energy contrast-enhanced subtracted mammography in dense breasts compared to mammography alone: interobserver blind-reading analysis

Contrast-enhanced mammography improves patient access to functional breast imaging

Imaging research pathways focus increasingly on the development of individualised approaches to breast cancer detection, diagnosis and management. Detection of breast cancer with X-ray mammography may fail in some cancer subtypes with limited changes in morphology/tissue density and in women with dense breasts. International organisations offer recommendations for contrast-enhanced breast imaging, as it provides superior sensitivity for screening, local staging and assessment of neoadjuvant treatment response, when compared with standard X-ray mammography (including tomosynthesis) and breast ultrasound. Arguably, the evidence base is stronger for contrast-enhanced MRI (CE-MRI). Unfortunately, patient access to breast MRI in rural and remote areas is limited by practical limitations and equipment licensing restrictions. Moreover, breast MRI is an expensive test, likely to be out of reach for many women. Contrast-enhanced mammography (CEM) offers an attractive alternative to improve patient access to functional breast imaging. It is a new type of digital, dual energy X-ray mammography that can be performed on most modern units, following a relatively inexpensive hard- and software upgrade. In this paper, we review the rapidly accumulating evidence that CEM can provide similar diagnostic accuracy to CE-MRI, though at a significantly lower cost and offering greater comfort to the patient. The adoption of CEM can help meet the anticipated increased demand for CE-MRI.

Diagnostic Accuracy of Screening Contrast-enhanced Mammography for Women with Extremely Dense Breasts at Increased Risk of Breast Cancer

Background Mammogram interpretation is challenging in female patients with extremely dense breasts (Breast Imaging Reporting and Data System [BI-RADS] category D), who have a higher breast cancer risk. Contrast-enhanced mammography (CEM) has recently emerged as a potential alternative; however, data regarding CEM utility in this subpopulation are limited. Purpose To evaluate the diagnostic performance of CEM for breast cancer screening in female patients with extremely dense breasts. Materials and Methods This retrospective single-institution study included consecutive CEM examinations in asymptomatic female patients with extremely dense breasts performed from December 2012 to March 2022. From CEM examinations, low-energy (LE) images were the equivalent of a two-dimensional full-field digital mammogram. Recombined images highlighting areas of contrast enhancement were constructed using a postprocessing algorithm. The sensitivity and specificity of LE images and CEM images (ie, including both LE and recombined images) were calculated and compared using the McNemar test. Results This study included 1299 screening CEM examinations (609 female patients; mean age, 50 years ± 9 [SD]). Sixteen screen-detected cancers were diagnosed, and two interval cancers occured. Five cancers were depicted at LE imaging and an additional 11 cancers were depicted at CEM (incremental cancer detection rate, 8.7 cancers per 1000 examinations). CEM sensitivity was 88.9% (16 of 18; 95% CI: 65.3, 98.6), which was higher than the LE examination sensitivity of 27.8% (five of 18; 95% CI: 9.7, 53.5) (P = .003). However, there was decreased CEM specificity (88.9%; 1108 of 1246; 95% CI: 87.0, 90.6) compared with LE imaging (specificity, 96.2%; 1199 of 1246; 95% CI: 95.0, 97.2) (P < .001). Compared with specificity at baseline, CEM specificity at follow-up improved to 90.7% (705 of 777; 95% CI: 88.5, 92.7; P = .01). Conclusion Compared with LE imaging, CEM showed higher sensitivity but lower specificity in female patients with extremely dense breasts, although specificity improved at follow-up. © RSNA, 2024 See also the editorial by Lobbes in this issue.

Contrast-enhanced mammography versus conventional imaging in women recalled from breast cancer screening (RACER trial): a multicentre, open-label, randomised controlled clinical trial

Background

Women recalled from breast cancer screening receive post-screening work-up in the hospital with conventional breast imaging. The RACER trial aimed to study whether contrast-enhanced mammography (CEM) as primary imaging instead of conventional imaging resulted in more accurate and efficient diagnostic work-up in recalled women.

Methods

In this randomised, controlled trial (registered under NL6413/NTR6589) participants were allocated using deterministic minimisation to CEM or conventional imaging as a primary work-up tool in two general and two academic hospitals. Predefined patients' factors were reason for recall, BI-RADS score, and study centre. Primary outcomes were sensitivity and specificity. Secondary outcomes were the proportion of women needing supplemental examinations, and number of days until diagnosis.

Findings

Between April, 2018, and September, 2021, 529 patients recalled from the Dutch screening program were randomised, 265 to conventional imaging and 264 to CEM. Three patients in the control arm had to be excluded from analysis due to a protocol breach. After the entire work-up, sensitivity was 98.0% (95% CI; 92.2-99.7%) in the intervention arm and 97.7% (91.8-99.6%) in the control arm (p = 1.0), and specificity was 75.6% (72.5-76.6%) and 75.4% (72.5-76.4%, p = 1.0), respectively. Based on only primary full-field digital mammography/digital breast tomosynthesis or CEM, final diagnosis was reached in 27.7% (73/264) in the intervention arm and 1.1% (3/262) in the control arm. The frequency of supplemental imaging was significantly higher in the control arm (p < 0.0001). Median time needed to reach final diagnosis was comparable: 1 day (control arm: IQR 0-4; intervention arm: IQR 0-3). Thirteen malignant occult lesions were detected using CEM, versus three using conventional imaging. No serious adverse events occurred.

Interpretation

Diagnostic accuracy of CEM in the work-up of recalled women is comparable with conventional imaging. However, work-up with CEM as primary imaging is a more efficient pathway.

Funding

ZonMw (grant number 843001801) and GE Healthcare.

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.

Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software

OBJECTIVES

To evaluate the improvement of mammography interpretation for novice and experienced radiologists assisted by two commercial AI software.

METHODS

We compared the performance of two AI software (AI-1 and AI-2) in two experienced and two novice readers for 200 mammographic examinations (80 cancer cases). Two reading sessions were conducted within 4 weeks. The readers rated the likelihood of malignancy (range, 1-7) and the percentage probability of malignancy (range, 0-100%), with and without AI assistance. Differences in AUROC, sensitivity, and specificity were analyzed.

RESULTS

Mean AUROC increased in both novice (0.86 to 0.90 with AI-1 [p = 0.005]; 0.91 with AI-2 [p < 0.001]) and experienced readers (0.87 to 0.92 with AI-1 [p < 0.001]; 0.90 with AI-2 [p = 0.004]). Sensitivities increased from 81.3 to 88.8% with AI-1 (p = 0.027) and to 91.3% with AI-2 (p = 0.005) in novice readers, and from 81.9 to 90.6% with AI-1 (p = 0.001) and to 87.5% with AI-2 (p = 0.016) in experienced readers. Specificity did not decrease significantly in both novice (p > 0.999, both) and experienced readers (p > 0.999 with AI-1 and 0.282 with AI-2). There was no significant difference in the performance change depending on the type of AI software (p > 0.999).

CONCLUSION

Commercial AI software improved the diagnostic performance of both novice and experienced readers. The type of AI software used did not significantly impact performance changes. Further validation with a larger number of cases and readers is needed.

CLINICAL RELEVANCE STATEMENT

Commercial AI software effectively aided mammography interpretation irrespective of the experience level of human readers.

KEY POINTS

• Mammography interpretation remains challenging and is subject to a wide range of interobserver variability. • In this multi-reader study, two commercial AI software improved the sensitivity of mammography interpretation by both novice and experienced readers. The type of AI software used did not significantly impact performance changes. • Commercial AI software may effectively support mammography interpretation irrespective of the experience level of human readers.

Assessing the malignancy of suspicious breast microcalcifications: the role of contrast enhanced mammography

PURPOSE

To assess the role of contrast-enhanced mammography (CEM) in predicting the malignancy of breast calcifications.

MATERIAL AND METHODS

We retrospectively evaluated patients with suspicious calcifications (BIRADS 4) who underwent CEM and stereotactic vacuum-assisted biopsy (VAB) at our institution. We assessed the sensitivity (SE), specificity (SP), positive predictive value (PPV) and negative predictive value (NPV) of CEM in predicting malignancy of microcalcifications with a 95% confidence interval; we performed an overall analysis and a subgroup analysis stratified into group A-low risk (BIRADS 4a) and group B-medium/high risk (BIRADS 4b-4c). We then evaluated the correlation between enhancement and tumour proliferation index (Ki-67) for all malignant lesions.

RESULTS

Data from 182 patients with 184 lesions were collected. Overall the SE of CEM in predicting the malignancy of microcalcifications was 0.70, SP was 0.85, the PPV was 0.82, the NPV was 0.76 and AUC was 0.78. SE in group A was 0.89, SP was 0.89, PPV was 0.57, NPV was 0.98 and AUC was 0.75. SE in group B was 0.68, SP was 0.80, PPV was 0.87, NPV was 0.57 and AUC was 0.75. Among malignant microcalcifications that showed enhancement (N = 52), 61.5% had Ki-67 ≥ 20% and 38.5% had low Ki-67 values. Among the lesions that did not show enhancement (N = 22), 90.9% had Ki-67 < 20% and 9.1% showed high Ki-67 values 20%.

CONCLUSIONS

The absence of enhancement can be used as an indicative parameter for the absence of disease in cases of low-suspicious microcalcifications, but not in intermediate-high suspicious ones for which biopsy remains mandatory and can be used to distinguish indolent lesions from more aggressive neoplasms, with consequent reduction of overdiagnosis and overtreatment.

Patient Experience of Women With Dense Breasts Undergoing Screening Contrast-Enhanced Mammography

OBJECTIVE

We investigated patient experience with screening contrast-enhanced mammography (CEM) to determine whether a general population of women with dense breasts would accept CEM in a screening setting.

METHODS

In this institutional review board-approved prospective study, patients with heterogeneous and extremely dense breasts on their mammogram were invited to undergo screening CEM and complete pre-CEM and post-CEM surveys. On the pre-CEM survey, patients were asked about their attitudes regarding supplemental screening in general. On the post-CEM survey, patients were asked about their experience undergoing screening CEM, including causes and severity of any discomfort and whether they would consider undergoing screening CEM again in the future or recommend it to a friend.

RESULTS

One hundred sixty-three women were surveyed before and after screening CEM. Most patients, 97.5% (159/163), reported minimal or no unpleasantness associated with undergoing screening CEM. In addition, 91.4% (149/163) said they would probably or very likely undergo screening CEM in the future if it cost the same as a traditional screening mammogram, and 95.1% (155/163) said they would probably or very likely recommend screening CEM to a friend. Patients in this study, who were all willing to undergo CEM, more frequently reported a family history of breast cancer than a comparison cohort of women with dense breasts (58.2% vs 47.1%, P = .027).

CONCLUSION

Patients from a general population of women with dense breasts reported a positive experience undergoing screening CEM, suggesting screening CEM might be well received by this patient population, particularly if the cost was comparable with traditional screening mammography.

Role of contrast-enhanced mammography in the preoperative detection of ductal carcinoma in situ of the breasts: a comparison with low-energy image and magnetic resonance imaging

OBJECTIVES

To compare contrast-enhanced mammography (CEM) with low-energy image (LEI) alone and with magnetic resonance imaging (MRI) in the preoperative diagnosis of ductal carcinoma in situ (DCIS).

METHODS

In this single-center retrospective study, we reviewed 98 pure DCIS lesions in 96 patients who underwent CEM and MRI within 2 weeks preoperatively. The diagnostic performances of each imaging modality, lesion morphology, and extent were evaluated.

RESULTS

The sensitivity of CEM to DCIS was similar to that of MRI (92.9% vs. 93.9%, p = 0.77) and was significantly higher than that of LEI alone (76.5%, p = 0.002). The sensitivity of CEM to calcified DCIS (92.4%) was not significantly different from LEI alone (92.4%) and from MRI (93.9%, p = 1.00). However, CEM contributed to the simultaneous comparison of calcifications with enhancements. CEM had considerably higher sensitivity compared with LEI alone (93.8% vs. 43.8%, p < 0.001) and performed similarly to MRI (93.8%, p = 1.00) for noncalcified DCIS. All DCIS lesions were enhanced in MRI, whereas 94.9% (93/98) were enhanced in CEM. Non-mass enhancement was the most common presentation (CEM 63.4% and MRI 66.3%). The difference between the lesion size on each imaging modality and the histopathological size was smallest in MRI, followed by CEM, and largest in LEI.

CONCLUSION

CEM was more sensitive than LEI alone and comparable to MRI in DCIS diagnosis. The enhanced morphology of DCIS in CEM was consistent with that in MRI. CEM was superior to LEI alone in size measurement of DCIS.

CLINICAL RELEVANCE STATEMENT

This study investigated the value of CEM in the diagnosis and evaluation of DCIS, aiming to offer a reference for the selection of examination methods for DCIS and contribute to the early diagnosis and precise treatment of DCIS.

KEY POINTS

• DCIS is an important indication for breast surgery. Early and accurate diagnosis is crucial for DCIS treatment and prognosis. • CEM overcomes the deficiency of mammography in noncalcified DCIS diagnosis, exhibiting similar sensitivity to MRI; and CEM contributes to the comparison of calcification and enhancement of calcified DCIS, thereby outperforming MRI. • CEM is superior to LEI alone and slightly inferior to MRI in the size evaluation of DCIS.

Contrast-Enhanced Mammography for Women with Palpable Breast Abnormalities

RATIONALE AND OBJECTIVES

To examine the role of contrast-enhanced mammography (CEM) in the work-up of palpable breast abnormalities.

MATERIALS AND METHODS

In this single-center combination prospective-retrospective study, women with palpable breast abnormalities underwent CEM evaluation prospectively, comprising the acquisition of low energy (LE) images and recombined images (RI) which depict enhancement, followed by targeted ultrasound (US). Two independent readers retrospectively reviewed the imaging and assigned BI-RADS assessment based on LE alone, LE plus US, RI with LE plus US (CEM plus US), and RI alone. Pathology results or 1-year follow-up imaging served as the reference standard.

RESULTS

237 women with 262 palpable abnormalities were included (mean age, 51 years). Of the 262 palpable abnormalities, 116/262 (44%) had no imaging correlate and 242/262 (92%) were benign. RI alone had better specificity compared to LE plus US (Reader 1, 94% versus 89% (p = 0.009); Reader 2, 93% versus 88% (p = 0.03)), better positive predictive value (Reader 1, 52% versus 42% (p = 0.04); Reader 2, 53% versus 42% (p = 0.04)), and better accuracy (Reader 1, 93% versus 89% (p = 0.05); Reader 2, 93% versus 90% (p = 0.06)). CEM plus US was not significantly different in performance metrics versus LE plus US.

CONCLUSION

RI had better specificity compared to LE in combination with US. There was no difference in performance between CEM plus US and LE plus US, likely reflecting the weight US carries in radiologist decision-making. However, the results indicate that the absence of enhancement on RI in the setting of palpable lesions may help avoid benign biopsies.

Diagnostic performance of contrast-enhanced mammography for suspicious findings in dense breasts: A systematic review and meta-analysis

PURPOSE

Contrast-enhanced spectral imaging (CEM) is a new mammography technique, but its diagnostic value in dense breasts is still inconclusive. We did a systematic review and meta-analysis of studies evaluating the diagnostic performance of CEM for suspicious findings in dense breasts.

MATERIALS AND METHODS

The PubMed, Embase, and Cochrane Library databases were searched systematically until August 6, 2023. Prospective and retrospective studies were included to evaluate the diagnostic performance of CEM for suspicious findings in dense breasts. The QUADAS-2 tool was used to evaluate the quality and risk of bias of the included studies. STATA V.16.0 and Review Manager V.5.3 were used to meta-analyze the included studies.

RESULTS

A total of 10 studies (827 patients, 958 lesions) were included. These 10 studies reported the diagnostic performance of CEM for the workup of suspicious lesions in patients with dense breasts. The summary sensitivity and summary specificity were 0.95 (95% CI, 0.92-0.97) and 0.81 (95% CI, 0.70-0.89), respectively. Enhanced lesions, circumscribed margins, and malignancy were statistically correlated. The relative malignancy OR value of the enhanced lesions was 28.11 (95% CI, 6.84-115.48). The relative malignancy OR value of circumscribed margins was 0.17 (95% CI, 0.07-0.45).

CONCLUSION

CEM has high diagnostic performance in the workup of suspicious findings in dense breasts, and when lesions are enhanced and have irregular margins, they are often malignant.

Breast Cancer Detection Using a Low-Dose Positron Emission Digital Mammography System

Purpose To investigate the feasibility of low-dose positron emission mammography (PEM) concurrently to MRI to identify breast cancer and determine its local extent. Materials and Methods In this research ethics board-approved prospective study, participants newly diagnosed with breast cancer with concurrent breast MRI acquisitions were assigned independently of breast density, tumor size, and histopathologic cancer subtype to undergo low-dose PEM with up to 185 MBq of fluorine 18-labeled fluorodeoxyglucose (18F-FDG). Two breast radiologists, unaware of the cancer location, reviewed PEM images taken 1 and 4 hours following 18F-FDG injection. Findings were correlated with histopathologic results. Detection accuracy and participant details were examined using logistic regression and summary statistics, and a comparative analysis assessed the efficacy of PEM and MRI additional lesions detection (ClinicalTrials.gov: NCT03520218). Results Twenty-five female participants (median age, 52 years; range, 32-85 years) comprised the cohort. Twenty-four of 25 (96%) cancers (19 invasive cancers and five in situ diseases) were identified with PEM from 100 sets of bilateral images, showcasing comparable performance even after 3 hours of radiotracer uptake. The median invasive cancer size was 31 mm (range, 10-120). Three additional in situ grade 2 lesions were missed at PEM. While not significant, PEM detected fewer false-positive additional lesions compared with MRI (one of six [16%] vs eight of 13 [62%]; P = .14). Conclusion This study suggests the feasibility of a low-dose PEM system in helping to detect invasive breast cancer. Though large-scale clinical trials are essential to confirm these preliminary results, this study underscores the potential of this low-dose PEM system as a promising imaging tool in breast cancer diagnosis. ClinicalTrials.gov registration no. NCT03520218 Keywords: Positron Emission Digital Mammography, Invasive Breast Cancer, Oncology, MRI Supplemental material is available for this article. © RSNA, 2024 See also commentary by Barreto and Rapelyea in this issue.

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.

Breast cancer diagnosis from contrast-enhanced mammography using multi-feature fusion neural network

OBJECTIVES

To develop an end-to-end deep neural network for the classification of contrast-enhanced mammography (CEM) images to facilitate breast cancer diagnosis in the clinic.

METHODS

In this retrospective mono-centric study, patients who underwent CEM examinations from January 2019 to August 2021 were enrolled. A multi-feature fusion network combining low-energy (LE) and dual-energy subtracted (DES) images and dual view, as well as bilateral information, was trained and tested using a large CEM dataset with a diversity of breast tumors for breast lesion classification. Its generalization performance was further evaluated on two external datasets. Results were reported using AUC, accuracy, sensitivity, and specificity.

RESULTS

A total of 2496 patients (mean age, 53 years ± 12 (standard deviation)) were included and divided into a training set (1718), a validation set (255), and a testing set (523). The proposed CEM-based multi-feature fusion network achieved the best diagnosis performance with an AUC of 0.96 (95% confidence interval (CI): 0.95, 0.97), compared with the no-fusion model, the left-right fusion model, and the multi-feature fusion network with only LE image inputs. Our models reached an AUC of 0.90 (95% CI: 0.85, 0.94) on a full-field digital mammograph (FFDM) external dataset (86 patients), and an AUC of 0.92 (95% CI: 0.89, 0.95) on a CEM external dataset (193 patients).

CONCLUSION

The developed multi-feature fusion neural network achieved high performance in CEM image classification and was able to facilitate CEM-based breast cancer diagnosis.

CLINICAL RELEVANCE STATEMENT

Compared with low-energy images, CEM images have greater sensitivity and similar specificity in malignant breast lesion detection. The multi-feature fusion neural network is a promising computer-aided diagnostic tool for the clinical diagnosis of breast cancer.

KEY POINTS

• Deep convolutional neural networks have the potential to facilitate contrast-enhanced mammography-based breast cancer diagnosis. • The multi-feature fusion neural network reaches high accuracies in the classification of contrast-enhanced mammography images. • The developed model is a promising diagnostic tool to facilitate clinical breast cancer diagnosis.

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.

Screening in Women With BRCA Mutations Revisited

Patients with BRCA1 or BRCA2 gene mutations are at high risk for the development of breast cancer. This article reviews the current evidence for breast cancer screening of patients with BRCA1 or BRCA2 pathogenic gene mutations if they have not undergone prophylactic mastectomy. It will review the current evidence-based imaging recommendations for different modalities and ages of screening initiation in screening this patient population at high risk. Special considerations in transgender BRCA1 and BRCA2 mutation carriers are also discussed.

Breast Imaging Physics in Mammography (Part II)

One of the most frequently detected neoplasms in women in Italy is breast cancer, for which high-sensitivity diagnostic techniques are essential for early diagnosis in order to minimize mortality rates. As addressed in Part I of this work, we have seen how conditions such as high glandular density or limitations related to mammographic sensitivity have driven the optimization of technology and the use of increasingly advanced and specific diagnostic methodologies. While the first part focused on analyzing the use of a mammography machine from a physical and dosimetric perspective, in this paper, we will examine other techniques commonly used in breast imaging: contrast-enhanced mammography, digital breast tomosynthesis, radio imaging, and include some notes on image processing. We will also explore the differences between these various techniques to provide a comprehensive overview of breast lesion detection techniques. We will examine the strengths and weaknesses of different diagnostic modalities and observe how, with the implementation of improvements over time, increasingly effective diagnoses can be achieved.

Short-term follow-up of contrast-enhanced mammography lesions after negative breast MRI in women with elevated breast cancer risk

PURPOSE

To determine the outcome of enhancing lesions detected on contrast-enhanced mammography (CEM) that had no correlate on magnetic resonance imaging (MRI) and underwent short-term follow-up CEM.

METHODS

In this retrospective single-center study, we identified patients with elevated breast cancer risk who had a CEM between 2014 and 2021 showing indeterminate enhancement on recombined images (BI-RADS 0, 3, 4) that had no correlate on subsequent MRI (performed within one month), and therefore underwent short-term follow-up CEM (performed within eight months). Medical records and imaging studies were reviewed to collect data on patient and lesion characteristics, and outcomes. Cancer incidence with 95% confidence interval (CI) was calculated.

RESULTS

This study included 71 women (median age 49 years) with 81 enhancing CEM lesions who underwent short-term follow-up CEM (median 6.2 months) after MRI reported no correlate. Of 81 lesions (median size = 0.7 cm), 73 (90%) were non-mass enhancement and 8 (10%) were enhancing masses. No sonographic correlate was identified for 75 lesions that had a same-day targeted ultrasound. Two cancers (2.5%, 95% CI 0.3-8.6) were diagnosed during the short-term follow-up period, one at 6-months (invasive ductal carcinoma) and one at 12-months (ductal carcinoma in situ). The remaining 79 lesions were benign at 6-month follow-up CEM and at one-year mammographic follow-up.

CONCLUSIONS

Follow-up CEM of MRI-occult lesions is prudent and may be reasonable to perform at one-year given the low incidence of cancer detected at six-months (one of 81) in our small study sample.

A cohort study of mammography-guided vacuum-assisted breast biopsy in patients with compressed thin breasts (≦ 3 cm)

OBJECTIVES

In the women with compressed thin thickness (≦ 3 cm), mammographic guiding vacuum-assist breast biopsy (MG-VABB) is a technical challenge. We herein report their performance of MG-VABB on suspicious microcalcification by modern mammography.

METHODS

We retrospectively reviewed the consecutive MG-VABB in our hospital from February 2019 to January 2021. All the patients received biopsy because of suspicious microcalcifications discovered by mammography and had at least one-year post-biopsy follow-up.

RESULTS

We reviewed 745 consecutive patients revealing 195 with compressed thin breasts ≦ 3 cm (mean age: 50.12 ± 7.0; breast thickness: 24.99 mm range 11.6-30 mm). Of the 191 patients received biopsy, the microcalcification retrieval rate was 97.9%. Using the half-open notch biopsy or horizontal needle approach, the biopsies were technically achieved in 30.4% and 9.4% of patients respectively. Regarding to the gold standard of surgicohistology, the cancer sensitivities was 88.46% and the atypia upgrade rate was 16.67%. There was no statistical difference of the procedure time between stereotactic guided and tomosynthesis guided.

CONCLUSIONS

The modern MG-VABB has technically improve the performance of biopsy to the patients with compressed thin breasts (≦ 3 cm), revealing approximate results to those breasts > 3 cm. The diagnosis helps the management of suspicious microcalcifications discovered by mammography.

Breast Cancer Screening for Women at Higher-Than-Average Risk: Updated Recommendations From the ACR

Early detection decreases breast cancer death. The ACR recommends annual screening beginning at age 40 for women of average risk and earlier and/or more intensive screening for women at higher-than-average risk. For most women at higher-than-average risk, the supplemental screening method of choice is breast MRI. Women with genetics-based increased risk, those with a calculated lifetime risk of 20% or more, and those exposed to chest radiation at young ages are recommended to undergo MRI surveillance starting at ages 25 to 30 and annual mammography (with a variable starting age between 25 and 40, depending on the type of risk). Mutation carriers can delay mammographic screening until age 40 if annual screening breast MRI is performed as recommended. Women diagnosed with breast cancer before age 50 or with personal histories of breast cancer and dense breasts should undergo annual supplemental breast MRI. Others with personal histories, and those with atypia at biopsy, should strongly consider MRI screening, especially if other risk factors are present. For women with dense breasts who desire supplemental screening, breast MRI is recommended. For those who qualify for but cannot undergo breast MRI, contrast-enhanced mammography or ultrasound could be considered. All women should undergo risk assessment by age 25, especially Black women and women of Ashkenazi Jewish heritage, so that those at higher-than-average risk can be identified and appropriate screening initiated.

Novel Technologies in Breast Imaging: A Scoping Review

Breast cancer is one of the leading causes of death in the United States and can cause considerable suffering for not only the patient but their families as well. The current mainstay of screening is mammography, although this screening modality has its drawbacks. Multiple technologies have been recently explored in hopes of increasing breast cancer detection rates and decreasing false positive rates. Overall, improving breast cancer screening techniques has the potential to decrease cost, patient anxiety, and the use of unnecessary procedures. This review discusses multiple modalities including digital breast tomosynthesis, contrast-enhanced dual-energy digital mammography (CE DE DM), MRI with diffusion-weighted sequences and proton magnetic resonance spectroscopy. This paper was written with the objective of synthesizing information across several databases to provide clinicians with a more accessible tool to understand the underlying concepts behind these imaging modalities, as well as present reviewed data which highlights the benefits and drawbacks of these breast cancer-detecting techniques.

Diagnostic Performance of Contrast-Enhanced Digital Mammography versus Conventional Imaging in Women with Dense Breasts

The aim of this prospective study was to compare the diagnostic performance of contrast-enhanced mammography (CEM) versus digital mammography (DM) combined with breast ultrasound (BUS) in women with dense breasts. Between March 2021 and February 2022, patients eligible for CEM with the breast composition category ACR BI-RADS c-d at DM and an abnormal finding (BI-RADS 3-4-5) at DM and/or BUS were considered. During CEM, a nonionic iodinated contrast agent (Iohexol 350 mg I/mL, 1.5 mL/kg) was power-injected intravenously. Images were evaluated independently by two breast radiologists. Findings classified as BI-RADS 1-3 were considered benign, while BI-RADS 4-5 were considered malignant. In case of discrepancies, the higher category was considered for DM+BUS. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated, using histology/≥12-month follow-up as gold standards. In total, 51 patients with 65 breast lesions were included. 59 (90.7%) abnormal findings were detected at DM+BUS, and 65 (100%) at CEM. The inter-reader agreement was excellent (Cohen's k = 0.87 for DM+BUS and 0.97 for CEM). CEM showed a 93.5% sensitivity (vs. 90.3% for DM+BUS), a 79.4-82.4% specificity (vs. 32.4-35.5% for DM+BUS) (McNemar p = 0.006), a 80.6-82.9% PPV (vs. 54.9-56.0% for DM+BUS), a 93.1-93.3% NPV (vs. 78.6-80.0% for DM+BUS), and a 86.1-87.7% accuracy (vs. 60.0-61.5% for DM+BUS). The AUC was higher for CEM than for DM+BUS (0.865 vs. 0.613 for Reader 1, and 0.880 vs. 0.628, for Reader 2) (p < 0.001). In conclusion, CEM had a better diagnostic performance than DM and BUS alone and combined together in patients with dense breasts.

A pictorial guide to artifacts on contrast mammography: How to avoid pitfalls and improve interpretation

Contrast-enhanced mammography (CEM) is an increasingly accepted emerging imaging modality that demonstrates a similar sensitivity to MRI but has the advantage of being less time consuming and inexpensive. The use of CEM continues to expand as it is recognized and utilized as a valuable tool for diagnostic and potentially screening examinations. As with any radiologic examination, artifacts occur and knowledge of these is important for adequate image interpretation. The purpose of this paper is to provide a pictorial review the common artifacts encountered on CEM examinations and identify causes and potential resolutions.

Preoperative staging by multimodal imaging in newly diagnosed breast cancer: Diagnostic performance of contrast-enhanced spectral mammography compared to conventional mammography, ultrasound, and MRI

PURPOSE

To compare contrast-enhanced spectral mammography (CESM) with mammography (Mx), ultrasound (US), and magnetic resonance imaging (MRI) regarding breast cancer detection rate and preoperative local staging.

MATERIAL AND METHODS

This prospective observational, single-centre study included 128 female patients (mean age 55.8 ± 11.5 years) with a newly diagnosed malignant breast tumour during routine US and Mx were prospectively enrolled. CESM and MRI examinations were performed within the study. Analysis included interreader agreement, tumour type and grade distribution, detection rates (DR), imaging morphology, contrast-enhancement and was performed by two independent readers blinded to patient history and histopathological diagnosis. Assessment of local disease extent was compared between modalities via Bland-Altman plots.

RESULTS

One-hundred-and-ten tumours were classified as NST (85.9%), 4 as ILC (3.1%) and 10 as DCIS (7.8%). DR was highest for MRI (128/128, 100.0%), followed by US (124/128, 96.9%) and CESM (123/128, 96.1%) and lowest for conventional Mx (106/128, 82.8%) (p = 0.0002). Higher breast density did not negatively affect DR of US, CESM or MRI. Local tumour extent measurements based on CESM (Bland-Altman bias 6.6, standard deviation 30.2) showed comparable estimation results to MRI, surpassing Mx (23.4/43.7) and US (35.4/40.5). Even though detection of multifocality and multicentricity was highest for CESM and MRI (p < 0.0001), second-look rates, i.e., targeted US examinations after MRI or CESM, were significantly lower for CESM (10.2% of cases) compared to MRI (16.2%) with a significantly higher true positive rate for CESM (72.0%) vs. MRI (42.5%).

CONCLUSION

CESM is a viable alternative to MRI for lesion detection and local staging in newly diagnosed malignant breast cancer and provides higher specificity in regard to second-look examinations.

Contrast-enhanced Mammography-guided Biopsy: Initial Trial and Experience

OBJECTIVE

Evaluate lesion visibility and radiologist confidence during contrast-enhanced mammography (CEM)-guided biopsy.

METHODS

Women with BI-RADS ≥4A enhancing breast lesions were prospectively recruited for 9-g vacuum-assisted CEM-guided biopsy. Breast density, background parenchymal enhancement (BPE), lesion characteristics (enhancement and conspicuity), radiologist confidence (scale 1-5), and acquisition times were collected. Signal intensities in specimens were analyzed. Patient surveys were collected.

RESULTS

A cohort of 28 women aged 40-81 years (average 57) had 28 enhancing lesions (7/28, 25% malignant). Breast tissue was scattered (10/28, 36%) or heterogeneously dense (18/28, 64%) with minimal (12/28, 43%), mild (7/28, 25%), or moderate (9/28, 32%) BPE on CEM. Twelve non-mass enhancements, 11 masses, 3 architectural distortions, and 2 calcification groups demonstrated weak (12/28, 43%), moderate (14/28, 50%), or strong (2/28, 7%) enhancement. Specimen radiography demonstrated lesion enhancement in 27/28 (96%). Radiologists reported complete lesion removal on specimen radiography in 8/28 (29%). Average time from contrast injection to specimen radiography was 18 minutes (SD = 5) and, to post-procedure mammogram (PPM), 34 minutes (SD = 10). Contrast-enhanced mammography PPM was performed in 27/28 cases; 13/19 (68%) of incompletely removed lesions on specimen radiography showed residual enhancement; 6/19 (32%) did not. Across all time points, average confidence was 2.2 (SD = 1.2). Signal intensities of enhancing lesions were similar to iodine. Patients had an overall positive assessment.

CONCLUSION

Lesion enhancement persisted through PPM and was visible on low energy specimen radiography, with an average "confident" score. Contrast-enhanced mammography-guided breast biopsy is easily implemented clinically. Its availability will encourage adoption of CEM.

Predicting Malignancy of Breast Imaging Findings Using Quantitative Analysis of Contrast-Enhanced Mammography (CEM)

We sought to develop new quantitative approaches to characterize the spatial distribution of mammographic density and contrast enhancement of suspicious contrast-enhanced mammography (CEM) findings to improve malignant vs. benign classifications of breast lesions. We retrospectively analyzed all breast lesions that underwent CEM imaging and tissue sampling at our institution from 2014–2020 in this IRB-approved study. A penalized linear discriminant analysis was used to classify lesions based on the averaged histograms of radial distributions of mammographic density and contrast enhancement. T-tests were used to compare the classification accuracies of density, contrast, and concatenated density and contrast histograms. Logistic regression and AUC-ROC analyses were used to assess if adding demographic and clinical data improved the model accuracy. A total of 159 suspicious findings were evaluated. Density histograms were more accurate in classifying lesions as malignant or benign than a random classifier (62.37% vs. 48%; p < 0.001), but the concatenated density and contrast histograms demonstrated a higher accuracy (71.25%; p < 0.001) than the density histograms alone. Including the demographic and clinical data in our models led to a higher AUC-ROC than concatenated density and contrast images (0.81 vs. 0.70; p < 0.001). In the classification of invasive vs. non-invasive malignancy, the concatenated density and contrast histograms demonstrated no significant improvement in accuracy over the density histograms alone (77.63% vs. 78.59%; p = 0.504). Our findings suggest that quantitative differences in the radial distribution of mammographic density could be used to discriminate malignant from benign breast findings; however, classification accuracy was significantly improved with the addition of contrast-enhanced imaging data from CEM. Adding patient demographic and clinical information further improved the classification accuracy.

Supplemental Breast Cancer Screening in Women with Dense Breasts and Negative Mammography: A Systematic Review and Meta-Analysis

Background The best supplemental breast cancer screening modality in women at average risk or intermediate risk for breast cancer with dense breast and negative mammogram remains to be determined. Purpose To conduct systematic review and meta-analysis comparing clinical outcomes of the most common available supplemental screening modalities in women at average risk or intermediate risk for breast cancer in patients with dense breasts and mammography with negative findings. Materials and Methods A comprehensive search was conducted until March 12, 2020, in Medline, Epub Ahead of Print and In-Process and Other Non-Indexed Citations; Embase Classic and Embase; Cochrane Central Register of Controlled Trials; and Cochrane Database of Systematic Reviews, for Randomized Controlled Trials and Prospective Observational Studies. Incremental cancer detection rate (CDR); positive predictive value of recall (PPV1); positive predictive value of biopsies performed (PPV3); and interval CDRs of supplemental imaging modalities, digital breast tomosynthesis, handheld US, automated breast US, and MRI in non-high-risk patients with dense breasts and mammography negative for cancer were reviewed. Data metrics and risk of bias were assessed. Random-effects meta-analysis and two-sided metaregression analyses comparing each imaging modality metrics were performed (PROSPERO; CRD42018080402). Results Twenty-two studies reporting 261 233 screened patients were included. Of 132 166 screened patients with dense breast and mammography negative for cancer who met inclusion criteria, a total of 541 cancers missed at mammography were detected with these supplemental modalities. Metaregression models showed that MRI was superior to other supplemental modalities in CDR (incremental CDR, 1.52 per 1000 screenings; 95% CI: 0.74, 2.33; P < .001), including invasive CDR (invasive CDR, 1.31 per 1000 screenings; 95% CI: 0.57, 2.06; P < .001), and in situ disease (rate of ductal carcinoma in situ, 1.91 per 1000 screenings; 95% CI: 0.10, 3.72; P < .04). No differences in PPV1 and PPV3 were identified. The limited number of studies prevented assessment of interval cancer metrics. Excluding MRI, no statistically significant difference in any metrics were identified among the remaining imaging modalities. Conclusion The pooled data showed that MRI was the best supplemental imaging modality in women at average risk or intermediate risk for breast cancer with dense breasts and mammography negative for cancer. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Hooley and Butler in this issue.

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.

Breast Cancer Screening in Women With Dense Breasts: Current Status and Future Directions for Appropriate Risk Stratification and Imaging Utilization

Breast density continues to be a prevailing topic in the field of breast imaging, with continued complexities contributing to overall confusion and controversy among patients and the medical community. In this article, we explore the current status of breast cancer screening in women with dense breasts including breast density legislation. Risk-based approaches to supplemental screening may be more financially cost-effective. While all advanced imaging modalities detect additional primarily invasive, node-negative cancers, the degree to which this occurs can vary by density category. Future directions include expanding the use of density-inclusive risk models with appropriate risk stratification and imaging utilization. Further research is needed, however, to better understand how to optimize population-based screening programs with knowledge of patients' individualized risk, including breast density assessment, to improve the benefit-to-harm ratio of breast cancer screening.

Quantitative Analysis of Contrast-enhanced Mammography for Risk Stratification of Benign Versus Malignant Disease and Molecular Subtype

OBJECTIVE

To assess quantitative enhancement of benign, high-risk, and malignant lesions and differences in molecular subtype and grade of malignant lesions on contrast-enhanced mammography (CEM).

METHODS

This IRB-approved retrospective study included women who underwent CEM for diagnostic work-up of a breast lesion between 2014 and 2020. Inclusion criteria were women who had diagnostic work-up with CEM and had BI-RADS 1 or 2 with one year follow-up, BI-RADS 3 with tissue diagnosis or stability for 2 years, or BI-RADS 4 or 5 with tissue diagnosis. An enhancement ratio was calculated for all lesions. This was obtained by drawing a region of interest within the lesion and a second region of interest in the nonenhancing background tissue using a program developed with MATLAB. Descriptive statistics were evaluated using chi-squared tests, Fisher exact tests, and analysis of variance. A logistic regression model was used to predict cancer outcome using the enhancement ratio. Statistical significance was defined as P < 0.05.

RESULTS

There were 332 lesions in 210 women that met study criteria. Of the 332 lesions, 50.9% (169/332) were malignant, 5.7% (19/332) were high-risk, and 43.4% (144/332) were benign. Enhancement intensity of malignant lesions was higher than benign lesions. Odds ratio for quantitative enhancement of malignant lesions was 30.15 (P < 0.0001). Enhancement ratio above 1.49 had an 84.0% sensitivity and 84.0% specificity for malignancy. HER2-enriched breast cancers had significantly higher mean enhancement ratios (P = 0.0062).

CONCLUSION

Quantitative enhancement on CEM demonstrated that malignant breast lesions had higher mean enhancement intensity than benign lesions.

Contrast Media-Enhanced Breast Computed Tomography With a Photon-Counting Detector: Initial Experiences on In Vivo Image Quality and Correlation to Histology

OBJECTIVES

The aim of this study was to investigate the feasibility, the image quality, and the correlation with histology of dedicated spiral breast computed tomography (B-CT) equipped with a photon-counting detector in patients with suspicious breast lesions after application of iodinated contrast media.

MATERIALS AND METHODS

The local ethics committee approved this prospective study. Twelve women with suspicious breast lesions found in mammography or B-CT underwent contrast-enhanced spiral B-CT and supplementary ultrasound. For all lesions, biopsy-proven diagnosis and histological workup after surgical resection were obtained including the size of cancer/ductal carcinoma in situ, which were correlated to sizes measured in B-CT. Signal-to-noise ratio and contrast-to-noise ratio were evaluated for tumor, glandular tissue, and fatty tissue.

RESULTS

Of the 12 patients, 15 suspicious lesions were found, 14 were malignant, and 1 benign lesion corresponded to a chronic inflammation. All lesions showed strong contrast media uptake with a signal-to-noise ratio of 119.7 ± 52.5 with a contrast-to-noise ratio between glandular tissue and breast cancer lesion of 12.6 ± 5.9. The correlation of the size of invasive tumors measured in B-CT compared with histological size was significant and strong R = 0.77 ( P < 0.05), whereas the correlation with the size of the peritumoral ductal carcinoma in situ was not significant R = 0.80 ( P = 0.11).

CONCLUSIONS

Contrast-enhanced B-CT shows high contrast between breast cancer and surrounding glandular tissue; therefore, it is a promising technique for cancer detection and staging depicting both soft tissue lesions and microcalcifications, which might be a substantial advantage over breast MRI.

A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography

Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22−83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies.

Addressing Misinformation About the Canadian Breast Screening Guidelines

Screening mammography has been shown to reduce breast cancer mortality by 41% in screened women ages 40-69 years. There is misinformation about breast screening and the Canadian breast screening guidelines. This can decrease confidence in screening mammography and can lead to suboptimal recommendations. We review some of this misinformation to help radiologists and referring physicians navigate the varied international and provincial guidelines. We address the ages to start and stop breast screening. We explore how these recommendations may vary for specific populations such as patients who are at increased risk, transgender patients and minorities. We identify who would benefit from supplemental screening and review the available supplemental screening modalities including ultrasound, MRI, contrast-enhanced mammography and others. We describe emerging technologies including the potential use of artificial intelligence for breast screening. We provide background on why screening policies vary across the country between provinces and territories. This review is intended to help radiologists and referring physicians understand and navigate the varied international and provincial recommendations and guidelines and make the best recommendations for their patients.

A case report of breast cancer in silicone-injected breasts diagnosed by an emerging technique of contrast-enhanced mammography-guided biopsy

Background

Breast cancer in silicone-injected breasts is often obscured in conventional mammography and sonography. Contrast-enhanced magnetic resonance imaging (CE-MRI) is an optimal modality for cancer detection. This case report demonstrates the use of contrast-enhanced spectral mammography (CESM) and CESM-guided biopsy (CESM-Bx) to diagnose breast cancer in silicone-injected breasts. However, there is no relevant report in the literature.

Case Presentation

A 59-year-old woman who received a liquid silicone injection for breast augmentation 30 years ago was transferred to our hospital for a CE-MRI-guided biopsy due to a suspicion of cancer in her right breast. The CE-MRI showed a 3.1-cm irregular enhanced mass and a 1.1-cm circumscribe mass in the upper outer quadrant of the right breast. Unfortunately, the CE-MRI-guided biopsy had to wait for 1 month due to a busy schedule. The CESM revealed two masses that were consistent with CE-MRI findings. CESM-Bx was performed, and the patient was diagnosed with invasive lobular carcinoma with an irregular mass and fibroadenoma of the circumscribed mass. The patient underwent substantial surgery.

Conclusions

CESM-Bx is a simple emerging technique that can be used feasibly to obtain tissue proof on the concerned enhanced lesion on CESM. In such cases of silicone-injected breasts, the CESM-Bx can be used as an alternative to MRI-guided biopsy for cancer diagnosis.

The Impact of Dense Breasts on the Stage of Breast Cancer at Diagnosis: A Review and Options for Supplemental Screening

The purpose of breast cancer screening is to find cancers early to reduce mortality and to allow successful treatment with less aggressive therapy. Mammography is the gold standard for breast cancer screening. Its efficacy in reducing mortality from breast cancer was proven in randomized controlled trials (RCTs) conducted from the early 1960s to the mid 1990s. Panels that recommend breast cancer screening guidelines have traditionally relied on the old RCTs, which did not include considerations of breast density, race/ethnicity, current hormone therapy, and other risk factors. Women do not all benefit equally from mammography. Mortality reduction is significantly lower in women with dense breasts because normal dense tissue can mask cancers on mammograms. Moreover, women with dense breasts are known to be at increased risk. To provide equity, breast cancer screening guidelines should be created with the goal of maximizing mortality reduction and allowing less aggressive therapy, which may include decreasing the interval between screening mammograms and recommending consideration of supplemental screening for women with dense breasts. This review will address the issue of dense breasts and the impact on the stage of breast cancer at the time of diagnosis, and discuss options for supplemental screening.

Can Contrast-Enhanced Spectral Mammography (CESM) Reduce Benign Breast Biopsy?

Objectives

To evaluate the potential of contrast-enhanced spectral mammography (CESM) in reducing benign breast biopsy rate, thereby improving resource utilization. To explore its potential as a value-adding modality in the management of BI-RADS 4/5 lesions.

Materials and Methods

This was a prospective study conducted between July 2016 and September 2018. Patients with BI-RADS 4/5 lesions detected on conventional imaging (mammogram, digital breast tomosynthesis, and ultrasound) were enrolled for adjunct CESM. Histopathologic correlation was done for all lesions. Additional suspicious lesions detected on CESM were all identified on second-look ultrasound and subsequently biopsied. Images were evaluated independently by two radiologists trained in breast imaging using BI-RADS classification. Presence of enhancement on CESM, BI-RADS score, and histopathology of each lesion were analyzed and tested with the chi-square/fisher-exact test for statistical significance.

Results

The study included 105 lesions in 63 participants—1 man and 62 women, an average age of 53.7 ± 10.8 years. On CESM, 22 (20.9%) of the lesions did not show enhancement. All 22 lesions had been classified as BI-RADS 4A and were subsequently proven to be benign. Of the remaining 83 enhancing lesions, 54 (65.1%) were malignant and 29 (34.9%) were benign (p < 0.05). CESM detected 6 additional lesions which were not identified on initial conventional imaging. Four of these were proven malignant and were in a different quadrant than the primary lesion investigated.

Conclusion

There is evidence that the absence of enhancement in CESM strongly favors benignity. It may provide the reporting radiologist with greater confidence in imaging assessment, especially in BI-RADS 4A cases, where a proportion of them are in actuality BI-RADS 3. Greater accuracy of BI-RADS grading can reduce nearly half of benign biopsies and allow better resource allocation. CESM also increases the detection rate of potentially malignant lesions, thereby changing the treatment strategies.

Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours

Objective

To evaluate if a deep learning model can be used to characterise breast cancers on contrast-enhanced spectral mammography (CESM).

Methods

This retrospective mono-centric study included biopsy-proven invasive cancers with an enhancement on CESM. CESM images include low-energy images (LE) comparable to digital mammography and dual-energy subtracted images (DES) showing tumour angiogenesis. For each lesion, histologic type, tumour grade, estrogen receptor (ER) status, progesterone receptor (PR) status, HER-2 status, Ki-67 proliferation index, and the size of the invasive tumour were retrieved. The deep learning model used was a CheXNet-based model fine-tuned on CESM dataset. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated for the different models: images by images and then by majority voting combining all the incidences for one tumour.

Results

In total, 447 invasive breast cancers detected on CESM with pathological evidence, in 389 patients, which represented 2460 images analysed, were included. Concerning the ER, the deep learning model on the DES images had an AUC of 0.83 with the image-by-image analysis and of 0.85 for the majority voting. For the triple-negative analysis, a high AUC was observable for all models, in particularity for the model on LE images with an AUC of 0.90 for the image-by-image analysis and 0.91 for the majority voting. The AUC for the other histoprognostic factors was lower.

Conclusion

Deep learning analysis on CESM has the potential to determine histoprognostic tumours makers, notably estrogen receptor status, and triple-negative receptor status.

Key Points

• A deep learning model developed for chest radiography was adapted by fine-tuning to be used on contrast-enhanced spectral mammography.

• The adapted models allowed to determine for invasive breast cancers the status of estrogen receptors and triple-negative receptors.

• Such models applied to contrast-enhanced spectral mammography could provide rapid prognostic and predictive information.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08538-4.

Patient preferences regarding use of contrast-enhanced imaging for breast cancer screening

RATIONALE AND OBJECTIVES

Our purpose is to understand patient preferences towards contrast-enhanced imaging such as CEM or MRI for breast cancer screening.

METHODS AND MATERIALS

An anonymous survey was offered to all patients having screening mammography at a single academic institution from December 27 th 2019 to March 6 th 2020. Survey questions related to: (1) patients' background experiences (2) patients' concern for aspects of MRI and CEM measured using a 5-point Likert scale, and (3) financial considerations.

RESULTS

75% (1011/1349) patients completed the survey. 53.0% reported dense breasts and of those, 47.6% had additional screening. 49.6% had experienced a callback, 29.0% had a benign biopsy, and 13.7% had prior CEM/MRI. 34.7% were satisfied with mammography for screening. A majority were neutral or not concerned with radiation exposure, contrast allergy, IV line placement, claustrophobia, and false positive exams. 54.7% were willing to pay at least $250-500 for screening MRI. Those reporting dense breasts were less satisfied with mammography for screening (p<0.001) and willing to pay more for MRI (p<0.001). If patients had prior CEM/MRI, there was less concern for an allergic reaction (p<0.001), IV placement (p=0.025), and claustrophobia (p=0.006). There was less concern for false positives if they had a prior benign biopsy (p=0.029) or prior CEM/MRI (p=0.005) and less concern for IV placement if they had dense breasts (p=0.007) or a previous callback (p=0.013).

CONCLUSION

The screening population may accept CEM or MRI as a screening exam despite its risks and cost, especially patients with dense breasts and patients who have had prior CEM/MRI.

Contrast-enhanced Mammography: A Systematic Review and Meta-Analysis of Diagnostic Performance

Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ² = 0.3). At meta-regression, CEM interpretation with both low-energy and recombined images had higher sensitivity (95% vs 94%, P < .001) and specificity (81% vs 71%, P = .03) compared with recombined images alone. At subgroup analysis, CEM showed a 95% pooled sensitivity (95% CI: 92, 97) and a 78% pooled specificity (95% CI: 66, 87) from nine studies in patients with dense breasts, while in 10 studies on mammography-detected suspicious findings, CEM had a 92% pooled sensitivity (95% CI: 89, 94) and an 84% pooled specificity (95% CI: 73, 91). Conclusion Contrast-enhanced mammography demonstrated high performance in breast cancer detection, especially with joint interpretation of low-energy and recombined images. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bahl in this issue.

Contrast-enhanced mammography: what the radiologist needs to know

Contrast-enhanced mammography (CEM) is a combination of standard mammography and iodinated contrast material administration. During the last decade, CEM has found its place in breast imaging protocols: after i.v. administration of iodinated contrast material, low-energy and high-energy images are retrieved in one acquisition using a dual-energy technique, and a recombined image is constructed enabling visualisation of areas of contrast uptake. The increased incorporation of CEM into everyday clinical practice is reflected in the installation of dedicated equipment worldwide, the (commercial) availability of systems from different vendors, the number of CEM examinations performed, and the number of scientific articles published on the subject. It follows that ever more radiologists will be confronted with this technique, and thus be required to keep up to date with the latest developments in the field. Most importantly, radiologists must have sufficient knowledge on how to interpret CEM images and be acquainted with common artefacts and pitfalls. This comprehensive review provides a practical overview of CEM technique, including CEM-guided biopsy; reading, interpretation and structured reporting of CEM images, including the accompanying learning curve, CEM artefacts and interpretation pitfalls; indications for CEM; disadvantages of CEM; and future developments.

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.

ACR Appropriateness Criteria® Supplemental Breast Cancer Screening Based on Breast Density

Mammography remains the only validated screening tool for breast cancer, however, there are limitations to mammography. One of the limitations of mammography is the variable sensitivity based on breast density. Supplemental screening may be considered based on the patient's risk level and breast density. For average-risk women with nondense breasts, the sensitivity of digital breast tomosynthesis (DBT) screening is high; additional supplemental screening is not warranted in this population. For average-risk women with dense breasts, given the decreased sensitivity of mammography/DBT, this population may benefit from additional supplemental screening with contrast-enhanced mammography, screening ultrasound (US), breast MRI, or abbreviated breast MRI. In intermediate-risk women, there is emerging evidence suggesting that women in this population may benefit from breast MRI or abbreviated breast MRI. In intermediate-risk women with dense breasts, given the decreased sensitivity of mammography/DBT, this population may benefit from additional supplemental screening with contrast-enhancedmammography or screening US. There is strong evidence supporting screening high-risk women with breast MRI regardless of breast density. Contrast-enhanced mammography, whole breast screening US, or abbreviated breast MRI may be also considered. 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 include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

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 Mammographic Features of In Situ and Invasive Ductal Carcinoma Manifesting Microcalcifications Only: Help to Predict Underestimation?

BACKGROUND

The contrast-enhanced mammographic features of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) manifesting microcalcifications only on mammograms were evaluated to determine whether they could predict IDC underestimation.

METHODS

We reviewed patients who underwent mammography-guided biopsy on suspicious breast microcalcifications only and received contrast-enhanced spectral mammography (CESM) within 2 weeks before the biopsy. Those patients who were proven to have cancers (DCIS or IDC) by biopsy and subsequently had surgical treatment in our hospital were included for analysis. The presence or absence, size, morphology and texture of enhancement on contrast-enhanced spectral mammography were reviewed by consensus of two radiologists.

RESULTS

A total of 49 patients were included for analysis. Forty patients (81.6%) showed enhancement, including 18 (45%) DCIS and 22 (55%) IDC patients. All nine unenhanced cancers were pure DCIS. Pure DCIS showed 72.22% nonmass enhancement and 83.33% pure ground glass enhancement. IDC showed more mass (72.2% vs. 27.8%) and solid enhancements (83.33% vs. 16.67%). The cancer and texture of enhancement were significantly different between pure DCIS and IDC, with moderate diagnostic performance for the former (p-value < 0.01, AUC = 0.66, sensitivity = 93%, specificity = 39%) and the latter (p-value < 0.01, AUC = 0.74, sensitivity = 65%, specificity = 83%). Otherwise, pure DCIS showed a significant difference in enhanced texture compared with upgraded IDC and IDC (p = 0.0226 and 0.0018, respectively).

CONCLUSIONS

Nonmass and pure ground glass enhancements were closely related to pure DCIS, and cases showing mass and unpurified solid enhancements should be suspected as IDC. Unenhanced DCIS with microcalcifications only has a low DCIS upgrade rate. The CESM-enhanced features could feasibly predict IDC underestimation.

Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions

OBJECTIVE

To conduct perilesional region radiomics analysis of contrast-enhanced mammography (CEM) images to differentiate benign and malignant breast lesions.

METHODS AND MATERIALS

This retrospective study included patients who underwent CEM from November 2017 to February 2020. Lesion contours were manually delineated. Perilesional regions were automatically obtained. Seven regions of interest (ROIs) were obtained for each lesion, including the lesion ROI, annular perilesional ROIs (1 mm, 3 mm, 5 mm), and lesion + perilesional ROIs (1 mm, 3 mm, 5 mm). Overall, 4,098 radiomics features were extracted from each ROI. Datasets were divided into training and testing sets (1:1). Seven classification models using features from the seven ROIs were constructed using LASSO regression. Model performance was assessed by the AUC with 95% CI.

RESULTS

Overall, 190 women with 223 breast lesions (101 benign; 122 malignant) were enrolled. In the testing set, the annular perilesional ROI of 3-mm model showed the highest AUC of 0.930 (95% CI: 0.882-0.977), followed by the annular perilesional ROI of 1 mm model (AUC = 0.929; 95% CI: 0.881-0.978) and the lesion ROI model (AUC = 0.909; 95% CI: 0.857-0.961). A new model was generated by combining the predicted probabilities of the lesion ROI and annular perilesional ROI of 3-mm models, which achieved a higher AUC in the testing set (AUC = 0.940).

CONCLUSIONS

Annular perilesional radiomics analysis of CEM images is useful for diagnosing breast cancers. Adding annular perilesional information to the radiomics model built on the lesion information may improve the diagnostic performance.

KEY POINTS

• Radiomics analysis of the annular perilesional region of 3 mm in CEM images may provide valuable information for the differential diagnosis of benign and malignant breast lesions. • The radiomics information from the lesion region and the annular perilesional region may be complementary. Combining the predicted probabilities of the models constructed by the features from the two regions may improve the diagnostic performance of radiomics models.

Contrast-enhanced Mammography: A Guide to Setting Up a New Clinical Program

Contrast-enhanced mammography (CEM) is gaining rapid traction following the U.S. Food and Drug Administration approval for diagnostic indications. Contrast-enhanced mammography is an alternative form of mammography that uses a dual-energy technique for image acquisition after the intravenous administration of iodinated contrast material. The resulting exam includes a dual set of images, one that appears similar to a routine 2D mammogram and one that highlights areas of contrast uptake. Studies have shown improved sensitivity compared to mammography and similar performance to contrast-enhanced breast MRI. As radiology groups incorporate CEM into clinical practice they must first select the indications for which CEM will be used. Many practices initially use CEM as an MRI alternative or in cases recommended for biopsy. Practices should then define the CEM clinical workflow and patient selection to include ordering, scheduling, contrast safety screening, and managing imaging on the day of the exam. The main equipment requirements for performing CEM include CEM-capable mammography equipment, a power injector for contrast administration, and imaging-viewing capability. The main staffing requirements include personnel to place the intravenous line, perform the CEM exam, and interpret the CEM. To safely and appropriately perform CEM, staff must be trained in their respective roles and to manage potential contrast-related events. Lastly, informing referring colleagues and patients of CEM through marketing campaigns is helpful for successful implementation.

Adenoid Cystic Carcinoma of the Breast

BACKGROUND

Contrast-enhanced spectral mammogram (CESM) is a modern technique providing additional information to detect or diagnose breast cancers.

INTRODUCTION

We present a rare ACC of the breast on CESM.

METHODS

A 49-year-old woman with surgicopathological proved ACC was reported with tumor features on CESM, sonography and contrast-enhanced magnetic resonance imaging (CE-MRI).

RESULTS

Sonography revealed a 1.4 cm × 1.2 cm × 1 cm circumscribe round mass in the upper outer quadrant of the left breast that was diagnosed with fibroadenoma. The mammogram did not show any discernible mass, however, the recombined subtracted images displayed a circumscribe mass with thin rim enhancement and enhanced internal patches that were resembling CE-MRI. Finally, the mass was proved to ACC.

CONCLUSION

CESM facilitates the detection of isodense cancer and provides the enhanced features for differential diagnosis. Resembling CE-MRI, CESM displayed rim enhancement and internal enhanced patches as diagnostic clues for this case of ACC.

Contrast-enhanced spectral mammography without and with a delayed image for diagnosing malignancy among mass lesions in dense breast

Aim of the study

To analyse the diagnostic performance of contrast-enhanced spectral mammography (CESM) based on morphologic and enhancement patterns of mass lesions in dense breast using different protocols: CESM without delayed image and CESM with delayed image.

Material and methods

A total of 151 informed women with suspicious for malignancy mass lesions in dense breast were included in this study. All of them underwent CESM using 2 protocols. A total of 155 lesions were pathomorphologically verified. We analysed morphologic patterns on low-energy (LE) images and recombined images (RI) by defining the shape, margin, and dynamic patterns based on delayed images.

Results

The comparative analysis revealed that the shape and margins on RI were more significant than those on LE images. The dynamic indicators of CESM were found to be highly significant in dense breasts. The correlation between kinetic curve and histological results demonstrated that a persistent type of curve was common for benign lesions, accounting for 15/22 (68.1%); plateau and washout – for malignant lesions, accounting for 24/89 (26.9%) and 61/89 (68.5%), respectively. Delayed image leads to an increase of specificity up to 12.4%, which is statistically significant. The area under the curve (AUC) in CESM with delayed image is larger than that in CESM without delayed image (p < 0.01).

Conclusions

CESM is sensitive for the differential diagnosis of breast lesions. CESM with delayed image has higher specificity than CESM without delayed image. Delayed images with plateau and washout are typical for malignancy.

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.