Comparison of Contrast-Enhanced Mammography With Conventional Digital Mammography in Breast Cancer Screening: A Pilot Study

ACR Appropriateness Criteria® Female Breast Cancer Screening: 2023 Update

Early detection of breast cancer from regular screening substantially reduces breast cancer mortality and morbidity. Multiple different imaging modalities may be used to screen for breast cancer. Screening recommendations differ based on an individual's risk of developing breast cancer. Numerous factors contribute to breast cancer risk, which is frequently divided into three major categories: average, intermediate, and high risk. For patients assigned female at birth with native breast tissue, mammography and digital breast tomosynthesis are the recommended method for breast cancer screening in all risk categories. In addition to the recommendation of mammography and digital breast tomosynthesis in high-risk patients, screening with breast MRI is recommended. 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.

False-Positive and False-Negative Contrast-enhanced Mammograms: Pitfalls and Strategies to Improve Cancer Detection

Contrast-enhanced mammography (CEM) is a relatively new breast imaging modality that uses intravenous contrast material to increase detection of breast cancer. CEM combines the structural information of conventional mammography with the functional information of tumor neovascularity. Initial studies have demonstrated that CEM and MRI perform with similar accuracies, with CEM having a slightly higher specificity (fewer false positives), although larger studies are needed. There are various reasons for false positives and false negatives at CEM. False positives at CEM can be caused by benign lesions with vascularity, including benign tumors, infection or inflammation, benign lesions in the skin, and imaging artifacts. False negatives at CEM can be attributed to incomplete or inadequate visualization of lesions, marked background parenchymal enhancement (BPE) obscuring cancer, lack of lesion contrast enhancement due to technical issues or less-vascular cancers, artifacts, and errors of lesion perception or characterization. When possible, real-time interpretation of CEM studies is ideal. If additional views are necessary, they may be obtained while contrast material is still in the breast parenchyma. Until recently, a limitation of CEM was the lack of CEM-guided biopsy capability. However, in 2020, the U.S. Food and Drug Administration cleared two devices to support CEM-guided biopsy using a stereotactic biopsy technique. The authors review various causes of false-positive and false-negative contrast-enhanced mammograms and discuss strategies to reduce these diagnostic errors to improve cancer detection while mitigating unnecessary additional imaging and procedures. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Revisiting Screening in Women With a Family History of Breast Cancer

Women with a family history (FH) of breast cancer and without known genetic susceptibility represent a unique population whose lifetime probability of developing breast cancer varies widely depending on familial factors, breast density, and the risk assessment tool used. Recently updated guidelines from the American College of Radiology recommend supplemental annual screening with contrast-enhanced MRI or contrast-enhanced mammography for women with an FH who are high risk (≥20% lifetime risk) or have dense breasts. To date, most screening studies addressing outcomes in women with FH have largely included those also with confirmed or suspected gene mutations, in whom the lifetime risk is highest, with limited data for women at average to intermediate risk who are not known to be genetically susceptible and may not benefit as much from the same screening approaches. Further research focusing specifically on women with FH as the only breast cancer risk factor is warranted to refine risk assessment and optimize a multimodality personalized screening approach.

Comparison of Contrast-enhanced Mammography with MRI Utilizing an Enriched Reader Study: A Breast Cancer Study (CONTRRAST Trial)

Background Despite growing interest in using contrast-enhanced mammography (CEM) for breast cancer screening as an alternative to breast MRI, limited literature is available. Purpose To determine whether CEM is noninferior to breast MRI or abbreviated breast MRI (AB MRI) and superior to two-dimensional mammography in an asymptomatic population simulating those who would present for screening and then undergo diagnostic work-up. Materials and Methods This enriched reader study used CEM and MRI data prospectively collected from asymptomatic individuals at a single institution from December 2014 to March 2020. Case sets were obtained at screening, as part of work-up for a screening-detected finding, or before biopsy of a screening-detected abnormality. All images were anonymized and randomized, and all 12 radiologists interpreted them. For CEM interpretation, readers were first shown low-energy images as a surrogate for digital mammography and asked to give a forced Breast Imaging Reporting and Data System score for up to three abnormalities. The highest score was used as the case score. Readers then reviewed the full CEM examination and scored it similarly. After a minimum 1-month washout, the readers similarly interpreted AB MRI and full MRI examinations. Receiver operating characteristic analysis, powered to test CEM noninferiority to full MRI, was performed. Results The study included 132 case sets (14 negative, 74 benign, and 44 malignant; all female participants; mean age, 54 years ± 12 [SD]). The mean areas under the receiver operating characteristic curve (AUCs) for digital mammography, CEM, AB MRI, and full MRI were 0.79, 0.91, 0.89, and 0.91, respectively. CEM was superior to digital mammography (P < .001). No evidence of a difference in AUC was found between CEM and AB MRI and MRI. Conclusion In an asymptomatic study sample, CEM was noninferior to full MRI and AB MRI and was superior to digital mammography. Clinical trial registration no. NCT03482557 and NCT02275871 © RSNA, 2023 Supplemental material is available for this article.

Iopromide for Contrast-Enhanced Mammography: A Systemic Review and Meta-Analysis of Pertinent Literature

Background

Contrast-enhanced mammography (CEM) is an emerging breast imaging modality. Clinical data is scarce.

Objectives

To summarize clinical evidence on the use of iopromide in CEM for the detection or by systematically analyzing the available literature on efficacy and safety.

Design

Systematic review and meta-analysis.

Data sources and methods

Iopromide-specific publications reporting its use in CEM were identified by a systematic search within Bayer's Product Literature Information (PLI) database and by levering a recent review publication. The literature search in PLI was performed up to January 2023. The confirmatory-supporting review publication was based on a MEDLINE/EMBASE + full text search for publications issued between September 2003 and January 2019. Relevant literature was selected based on pre-defined criteria by 2 reviewers. The comparison of CEM vs traditional mammography (XRM) was performed on published results of sensitivity and specificity. Differences in diagnostic parameters were assessed within a meta-analysis.

Results

Literature search: A total of 31 studies were identified reporting data on 5194 patients. Thereof, 19 studies on efficacy and 3 studies on safety. Efficacy: in 11 studies comparing iopromide CEM vs XRM, sensitivity was up to 43% higher (range 1%-43%) for CEM. Differences in specificity were found to be in a range of -4% to 46% for CEM compared with XRM. The overall gain in sensitivity for CEM vs XRM was 7% (95% CI [4%, 11%]) with no statistically significant loss in specificity in any study assessed. In most studies, accuracy, positive predictive value, and negative predictive value were found to be in favor of CEM. In 2 studies comparing CEM with breast magnetic resonance imaging (bMRI), both imaging modalities performed either equally well or CEM tended to show better results with respect to sensitivity and specificity. Safety: eight cases of iopromide-related adverse drug reactions were reported in 1022 patients (0.8%).

Conclusions

Pertinent literature provides evidence for clinical utility of iopromide in CEM for the detection or confirmation of breast cancer. The overall gain in sensitivity for iopromide CEM vs XRM was 7% with no statistically significant loss in specificity.

Contextual Features and Information Bottleneck-Based Multi-Input Network for Breast Cancer Classification from Contrast-Enhanced Spectral Mammography

In computer-aided diagnosis methods for breast cancer, deep learning has been shown to be an effective method to distinguish whether lesions are present in tissues. However, traditional methods only classify masses as benign or malignant, according to their presence or absence, without considering the contextual features between them and their adjacent tissues. Furthermore, for contrast-enhanced spectral mammography, the existing studies have only performed feature extraction on a single image per breast. In this paper, we propose a multi-input deep learning network for automatic breast cancer classification. Specifically, we simultaneously input four images of each breast with different feature information into the network. Then, we processed the feature maps in both horizontal and vertical directions, preserving the pixel-level contextual information within the neighborhood of the tumor during the pooling operation. Furthermore, we designed a novel loss function according to the information bottleneck theory to optimize our multi-input network and ensure that the common information in the multiple input images could be fully utilized. Our experiments on 488 images (256 benign and 232 malignant images) from 122 patients show that the method's accuracy, precision, sensitivity, specificity, and f1-score values are 0.8806, 0.8803, 0.8810, 0.8801, and 0.8806, respectively. The qualitative, quantitative, and ablation experiment results show that our method significantly improves the accuracy of breast cancer classification and reduces the false positive rate of diagnosis. It can reduce misdiagnosis rates and unnecessary biopsies, helping doctors determine accurate clinical diagnoses of breast cancer from multiple CESM images.

Diagnostic performance of the Kaiser score in the evaluation of breast lesions on contrast-enhanced mammography

OBJECTIVES

We aimed to investigate whether the Kaiser score (KS) could improve the diagnostic performance of breast imaging reporting and data system (BI-RADS) in evaluating breast enhancing lesions on contrast-enhanced mammography (CEM).

METHODS

Three hundred fifty-nine patients with 375 lesions (231 malignant and 144 benign) were included in this retrospective study from April 2019 to December 2021.Two readers with different levels of experience in breast imaging were asked to give a BI-RADS assessment category according to the CEM BI-RADS and final score based on the KS. The diagnostic performance of all lesions, mass and non-mass enhancement (NME) were assessed by receiver operating characteristic (ROC) analysis, and the areas under the ROC curve (AUCs) were measured. The weighted kappa coefficients were calculated to investigate the interreader agreement.

RESULTS

The AUCs of the KS for all lesions were 0.915 (95 %CI: 0.884-0.947) and 0.876 (95 %CI: 0.838-0.914) for two readers. When mass and NME were evaluated separately, the AUCs of the KS for mass were higher than those for NME (p < 0.001). The AUCs of BI-RADS for all lesion diagnoses ranged between 0.821 (95 %CI: 0.778-0.864) and 0.842(95 %CI: 0.801-0.883) for two readers. The AUCs of the KS were higher than those of BI-RADS (p < 0.001, p = 0.016). There were no significant differences in the sensitivity between the KS (97.4 %) and BI-RADS (99.6 %) for all lesions (p = 0.130). The specificity of the KS was significantly higher than that of BI-RADS (p < 0.001). Compared with BI-RADS, the application of the KS could have potentially obviated 41.7 % to 47.9 % unnecessary biopsies in 144 benign lesions. Interreader agreement between the two readers of the KS was almost perfect (k = 0.883 [95 % CI: 0.842-0.924]).

CONCLUSION

The use of the KS provided a high diagnostic performance in distinguishing malignant and benign breast lesions on CEM and outperformed BI-RADS. The application of the KS can downgrade up to 47.9% of unnecessary biopsies of benign breast lesions.

Radiation Dose of Contrast-Enhanced Mammography: A Two-Center Prospective Comparison

The radiation dose associated with contrast-enhanced mammography (CEM) has been investigated only by single-center studies. In this retrospective study, we aimed to compare the radiation dose between two centers performing CEM within two prospective studies, using the same type of equipment. The CEM mean glandular dose (MGD) was computed for low energy (LE) and high energy (HE) images and their sum was calculated for each view. MGD and related parameters (entrance dose, breast thickness, compression, and density) were compared between the two centers using the Mann−Whitney test. Finally, per-patient MGD was calculated by pooling the two datasets and determining the contribution of LE and HE images. A total of 348 CEM examinations were analyzed (228 from Center 1 and 120 from Center 2). The median total MGD per view was 2.33 mGy (interquartile range 2.19−2.51 mGy) at Center 1 and 2.46 mGy (interquartile range 2.32−2.70 mGy) at Center 2, with a 0.15 mGy median difference (p < 0.001) equal to 6.2%. LE-images contributed between 64% and 77% to the total patient dose in CEM, with the remaining 23−36% being associated with HE images. The mean radiation dose for a two-view bilateral CEM exam was 4.90 mGy, about 30% higher than for digital mammography.

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: 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.

Breast imaging: Beyond the detection

Breast cancer is a heterogeneous disease nowadays, including different biological subtypes with a variety of possible treatments, which aim to achieve the best outcome in terms of response to therapy and overall survival. In recent years breast imaging has evolved considerably, and the ultimate goal is to predict these strong phenotypic differences noninvasively. Indeed, breast cancer multiparametric studies can highlight not only qualitative imaging parameters, as the presence/absence of a likely malignant finding, but also quantitative parameters, suggesting clinical-pathological features through the evaluation of imaging biomarkers. A further step has been the introduction of artificial intelligence and in particular radiogenomics, that investigates the relationship between breast cancer imaging characteristics and tumor molecular, genomic and proliferation features. In this review, we discuss the main techniques currently in use for breast imaging, their respective fields of use and their technological and diagnostic innovations.

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.

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.

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

RATIONALE AND OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

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.

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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.

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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.

Diagnostic accuracy of contrast-enhanced spectral mammography for breast lesions: A systematic review and meta-analysis

Breast cancer diagnosis and staging is based on mammography, ultrasound, and magnetic resonance imaging (MRI). Contrast enhanced spectral mammography (CESM) has gained momentum as an innovative and clinically useful method for breast assessment. CESM is based on abnormal enhancement of neoplastic tissue compared to surrounding breast tissue. We performed a systematic review of prospective trial to evaluate its diagnostic performance, following standard PRISMA-DTA. We used a bivariate random-effects regression approach to obtain summary estimates of both sensitivity and specificity of CESM. 8 studies published between 2003 and 2019 were included in the meta-analysis for a total of 945 lesions. The summary area under the curve obtained from all the study was 89% [95% CI 86%-91%], with a sensitivity of 85% [95% CI 73%-93%], and a specificity of 77% [95% CI 60%-88%]. With a pre-test probability of malignancy of 57% a positive finding at CESM gives a post-test probability of 83% while a negative finding a post-test probability of 20%. CESM shows a suboptimal sensitivity and specificity in the diagnosis of breast cancer in a selected population, and at present time, it could be considered only as a possible alternative test for breast lesions assessment when mammography and ultrasound are not conclusive or MRI is contraindicated or not available.

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.

Novel imaging approaches to screen for breast cancer: Recent advances and future prospects

AIM OF THE STUDY

Over the past 50 years, the application of mammography - an X-ray of the breast - to screen healthy women has been a successful strategy to reduce breast cancer mortality. The aim of this study was to review the literature on novel imaging approaches that have the potential to replace mammography.

METHODS

An online literature search was carried out using PubMed, Google Scholar, ScienceDirect and Google Patents. The search keywords included "breast cancer", "imaging" and "screening", with 51 journal articles and five United States patents being selected for review. Seventeen relevant online sources were also identified and referenced.

RESULTS

In addition to full-field digital mammography (FFDM), a further nine imaging modalities were identified for review. These included: digital breast tomosynthesis (DBT); breast computed tomography (BCT); automated breast ultrasound (ABUS); fusion of FFDM and ABUS; fusion of DBT and ABUS; magnetic resonance imaging (MRI); optical imaging; radio-wave imaging; and tactile sensor imaging. Important parameters were considered: diagnostic success (sensitivity and specificity), especially in dense breasts; time to acquire the images; and capital cost of the equipment.

CONCLUSIONS

DBT is rapidly replacing FFDM although it still misses invasive cancers in dense tissue. The fusion of ABUS, either with FFDM or DBT, will lead to sensitivity and specificity approaching 100%. The fusion of opto-acoustic imaging with ultrasound holds considerable promise for the future.