Contrast-enhanced spectral mammography versus MRI: Initial results in the detection of breast cancer and assessment of tumour size

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.

Breast cancer in dense breasts: comparative diagnostic merits of contrast-enhanced mammography and diffusion-weighted breast MRI

Background

The study was done to compare the value of contrast-enhanced mammography and diffusion-weighted breast MRI in dense breast screening and accurate detection of the breast cancer with correlation of the findings to the histopathological results.

The study included 32 female patients having suspicious breast lesions and underwent digital mammography then scheduled for CESM and MRI DW imaging technique. The imaging findings were correlated to the histopathological findings.

Results

The study was conducted on 40 breast lesions in 32 female patients having dense breasts; they were classified by the digital mammography into ACR C (59.4%) and ACR D (40.6%). By CESM, there were twenty three lesions (57.5%) as mass lesions and thirteen lesions (32.5%) as non-mass lesions. Four lesions (10%) showed no contrast enhancement. According to the lesion characteristics in diffusion-weighted imaging, the breast lesions were classified into thirty three lesions (82.5%) with restricted diffusion and seven lesions (17.5%) with non-restricted diffusion. The study showed a cutoff ADC value to detect the malignant lesions in the dense breasts ≤ 1.1 × 10-3 s/mm2 at b value of 1000 s/mm2 with a sensitivity of 96.77%, specificity of 66.67%, PPV of 96.77%, NPV of 55.55%, and an overall total accuracy of 92.5%.

On comparing the diagnostic accuracy of the CESM to that of the DW MRI, the sensitivity of DW MRI (96.77%) was higher than that of CESM (90.32%). The specificity of DW MRI (66.67%) was higher than that of CESM (33.33%). Total accuracy of DW MRI was higher than that of CESM; they were 90% and 77.5%, respectively. Also, PPV and NPV of DW MRI were 90.91 and 85.71% as compared with 82.35 and 50.00% in CESM, respectively. When comparing the sensitivity of CESM to DW MRI in the detection of multiple breast lesions, they were 88.8 and 100%, respectively.

Conclusion

CESM is a useful technique in identification of hidden lesions in mammographically dense breasts. DW MRI is a fast, unenhanced modality that can be used as a breast cancer screening modality. CESM and DWI demonstrated good overall diagnostic accuracy in dense breast patients; however, DW MRI has a higher diagnostic accuracy than CESM for the detection of malignant breast lesions and their multiplicity.

Added value of contrast-enhanced spectral mammography in symptomatic patients with dense breasts

Background

Breast cancer is the most common malignancy in females around the world representing 25.1% of all cancers.

The high prevalence and need for early treatment of breast malignancy highlight the importance of early and accurate diagnosis. In order to achieve this target, it is necessary to select the most appropriate modality for investigation.

Early detection of breast cancer by conventional mammography tends to reduce mortality; however, it has a low sensitivity and specificity in young females with dense breasts owing to reduced contrast between a possible tumor and the surrounding breast tissue with superimposition of the glandular tissue obscuring underlying lesions.

Our study included 25 patients with dense breasts presented with different breast symptoms, yet the breast lump was the most common complaint. The aim of our study is to evaluate the supplementary value of contrast-enhanced spectral mammography in the assessment of symptomatic patients with dense breasts.

Results

In our study, the enrolled subjects underwent both contrast-enhanced spectral mammography (CESM) and conventional full-field digital mammography (FFDM). CESM was shown to be better than FFDM in terms of sensitivity, positive predictive value, negative predictive value, and accuracy, measuring 100%, 77.8%, 100%, and 84%, compared to 56%, 75%, 46%, and 60%, respectively, yet both modalities showed low specificity, measuring 63.6% and 66.6% for CESM and FFDM, respectively.

The added value of CESM was assessed in terms of ability to detect and correctly characterize the lesions in correlation to histopathological results where CESM could detect 88% of the lesions included in our study and correctly characterized 84% of the lesions; on the other side, FFDM detected only 20% of the lesions and correctly characterized 60% of the lesions. CESM changed the treatment plan to a more extensive surgery +/− neoadjuvant chemotherapy in 57% out of fourteen cases diagnosed with breast cancer emphasizing the role of CESM in assessing the extent of the disease, multicentricity, and multifocality and consequently tailoring the most appropriate treatment plan suitable for each patient.

Conclusion

Contrast-enhanced spectral mammography is superior to full-field digital mammography in patients with dense breasts with a significant supplementary value in detection, characterization of lesions, and tailoring the appropriate treatment plan.

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.

Contrast-enhanced digital mammography and magnetic resonance imaging: reproducibility compared to pathologic anatomy

PURPOSE

To compare the reproducibility between contrast-enhanced digital mammography (CEDM) and magnetic resonance imaging (MRI) with the postsurgical pathologic examination. In addition, the applicability of the Breast Imaging-Reporting and Data System (BI-RADS) lexicon of MRI to CEDM was evaluated for mass lesions.

METHODS

A total of 62 patients with a histologically proven diagnosis of breast cancer were included in this study, for a total of 67 lesions. Fifty-nine patients underwent both methods. The reproducibility between MRI vs CEDM and the reference standard (postoperative pathology) was assessed by considering the lesion and breast size as pivotal variables. Reproducibility was evaluated by computing the concordance correlation coefficient (CCC). Bland-Altman plots were used to depict the observed pattern of agreement as well as to estimate the associated bias. Furthermore, the pattern of agreement between the investigated methods with regard to the breast lesion characterization (i.e. mass/nonmass; shape; margins; internal enhanced characteristics) was assessed by computing the Cohen kappa and its 95% confidence interval (CI).

RESULTS

The reproducibility between MRI and the reference standard and between CEDM and the reference standard showed substantial agreement, with a CCC value of 0.956 (95% CI, 0.931-0.972) and 0.950 (95% CI, 0.920-0.969), respectively. By looking at the Bland-Altman analysis, bias values of 2.344 and 1.875 mm were observed for MRI and CEDM vs reference evaluation, respectively. The agreement between MRI and CEDM is substantial with a CCC value of 0.969 (95% CI, 0.949-0.981). The Bland-Altman analysis showed bias values of -0.469 mm when comparing CEDM vs MRI. Following the Landis and Koch classification criteria, moderate agreement was observed between the two methods in describing BI-RADS descriptors of mass lesions.

CONCLUSION

CEDM is able to measure and describe tumor masses comparably to MRI and can be used for surgical planning.

The added value of an artificial intelligence system in assisting radiologists on indeterminate BI-RADS 0 mammograms

OBJECTIVES

To investigate the value of an artificial intelligence (AI) system in assisting radiologists to improve the assessment accuracy of BI-RADS 0 cases in mammograms.

METHODS

We included 34,654 consecutive digital mammography studies, collected between January 2011 and January 2019, among which, 1088 cases from 1010 unique patients with initial BI-RADS 0 assessment who were recalled during 2 years of follow-up were used in this study. Two mid-level radiologists retrospectively re-assessed these BI-RADS 0 cases with the assistance of an AI system developed by us previously. In addition, four entry-level radiologists were split into two groups to cross-read 80 cases with and without the AI. Diagnostic performance was evaluated using the follow-up diagnosis or biopsy results as the reference standard.

RESULTS

Of the 1088 cases, 626 were actually normal (BI-RADS 1 and no recall required). Assisted by the AI system, 351 (56%) and 362 (58%) normal cases were correctly identified by the two mid-level radiologists hence can be avoided for unnecessary follow-ups. However, they would have missed 12 (10 invasive cancers and 2 ductal carcinoma in situ cancers) and 6 (invasive cancers) malignant lesions respectively as a result. These missed lesions were not highly malignant tumors. The inter-rater reliability of entry-level radiologists increased from 0.20 to 0.30 (p < 0.005) by introducing the AI.

CONCLUSION

The AI system can effectively assist mid-level radiologists in reducing unnecessary follow-ups of mammographically indeterminate breast lesions and reducing the benign biopsy rate without missing highly malignant tumors.

KEY POINTS

• The artificial intelligence system could assist mid-level radiologists in effectively reducing unnecessary BI-RADS 0 mammogram recalls and the benign biopsy rate without missing highly malignant tumors. • The artificial intelligence system was capable of detecting low suspicion lesions from heterogeneously and extremely dense breasts that radiologists tended to miss. • The use of an artificial intelligence system may improve the inter-rater reliability and sensitivity, and reduce the reading time of entry-level radiologists in assessing potential lesions in BI-RADS 0 mammograms.

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Contrast enhanced mammography (CEM) versus magnetic resonance imaging (MRI) for staging of breast cancer: The pro CEM perspective

In women with newly diagnosed breast cancer, preoperative staging is required to assess disease extent, enabling us to decide on the most optimal treatment strategy. For locoregional staging, assessment of intramammary tumor extent and presence of axillary and perhaps also internal mammary lymph node metastases is required. Due to the similarity in the underlying principle, contrast-enhanced mammography is increasingly considered instead of breast MRI for this purpose. When considering the combination of CEM and US as a single appointment imaging strategy for preoperative staging of breast cancer, there is only limited room for an additional benefit of breast MRI. For tumor size measurements, equal performance of both CEM and MRI are observed. Sensitivity of both techniques for detecting breast cancer is comparable, meaning that both techniques are capable of detecting additional ipsilateral or contralateral tumor foci. However, specificity is in favor of CEM, meaning that there is a slightly lower chance of having false positive findings in preoperative staging of the breast. Axillary US can be performed during the same appointment as CEM, with equal performance and limitations as evaluation of the axilla on standard breast MRI examinations. Finally, there is no need to actively pursue the detection of IMLN metastases, meaning that additional MRI to do so is not required. This review provides a 'pro-CEM' perceptive on the arguments why breast MRI is hardly necessary when CEM in combination with US has been performed as a single appointment imaging strategy in breast cancer patients.

Differentiating Breast Tumors from Background Parenchymal Enhancement at Contrast-Enhanced Mammography: The Role of Radiomics-A Pilot Reader Study

Background: The purpose of this study was to assess the effectiveness of the radiomic analysis of contrast-enhanced spectral mammography (CESM) in discriminating between breast cancers and background parenchymal enhancement (BPE). Methods: This retrospective study included 38 patients that underwent CESM examinations for clinical purposes between January 2019–December 2020. A total of 57 malignant breast lesions and 23 CESM examinations with 31 regions of BPE were assessed through radiomic analysis using MaZda software. The parameters that demonstrated to be independent predictors for breast malignancy were exported into the B11 program and a k-nearest neighbor classifier (k-NN) was trained on the initial groups of patients and was tested using a validation group. Histopathology results obtained after surgery were considered the gold standard. Results: Radiomic analysis found WavEnLL_s_2 parameter as an independent predictor for breast malignancies with a sensitivity of 68.42% and a specificity of 83.87%. The prediction model that included CH1D6SumAverg, CN4D6Correlat, Kurtosis, Perc01, Perc10, Skewness, and WavEnLL_s_2 parameters had a sensitivity of 73.68% and a specificity of 80.65%. Higher values were obtained of WavEnLL_s_2 and the prediction model for tumors than for BPEs. The comparison between the ROC curves provided by the WaveEnLL_s_2 and the entire prediction model did not show statistically significant results (p = 0.0943). The k-NN classifier based on the parameter WavEnLL_s_2 had a sensitivity and specificity on training and validating groups of 71.93% and 45.16% vs. 60% and 44.44%, respectively. Conclusion: Radiomic analysis has the potential to differentiate CESM between malignant lesions and BPE. Further quantitative insight into parenchymal enhancement patterns should be performed to facilitate the role of BPE in personalized clinical decision-making and risk assessment.

Contrast-Enhanced Mammography and Radiomics Analysis for Noninvasive Breast Cancer Characterization: Initial Results

PURPOSE

To investigate the potential of contrast-enhanced mammography (CEM) and radiomics analysis for the noninvasive differentiation of breast cancer invasiveness, hormone receptor status, and tumor grade.

PROCEDURES

This retrospective study included 100 patients with 103 breast cancers who underwent pretreatment CEM. Radiomics analysis was performed using MAZDA software. Lesions were manually segmented. Radiomic features were derived from first-order histogram (HIS), co-occurrence matrix (COM), run length matrix (RLM), absolute gradient, autoregressive model, the discrete Haar wavelet transform (WAV), and lesion geometry. Fisher, probability of error and average correlation (POE+ACC), and mutual information (MI) coefficients informed feature selection. Linear discriminant analysis followed by k-nearest neighbor classification (with leave-one-out cross-validation) was used for pairwise texture-based separation of tumor invasiveness and hormone receptor status using histopathology as the standard of reference.

RESULTS

Radiomics analysis achieved the highest accuracies of 87.4 % for differentiating invasive from noninvasive cancers based on COM+HIS/MI, 78.4 % for differentiating HR positive from HR negative cancers based on COM+HIS/Fisher, 97.2 % for differentiating human epidermal growth factor receptor 2 (HER2)-positive/HR-negative from HER2-negative/HR-positive cancers based on RLM+WAV/MI, 100 % for differentiating triple-negative from triple-positive breast cancers mainly based on COM+WAV+HIS/POE+ACC, and 82.1 % for differentiating triple-negative from HR-positive cancers mainly based on WAV+HIS/Fisher. Accuracies for differentiating grade 1 vs. grades 2 and 3 cancers were 90 % for invasive cancers (based on COM/MI) and 100 % for noninvasive cancers (almost entirely based on COM/MI).

CONCLUSIONS

Radiomics analysis with CEM has potential for noninvasive differentiation of tumors with different degrees of invasiveness, hormone receptor status, and tumor grade.

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.

Giant epidermal inclusion cyst with infection arising within the breast parenchyma: a case report

Epidermal inclusion cysts (EICs) of the breast develop in the deep breast parenchyma, and they are very rare. Only about 10 cases have been reported in the English-language literature to date. In this report, we present a rare case of a giant EIC with infection arising within the deep breast parenchyma. Unlike a typical EIC of the breast, the EIC in the present case was a cystic and solid lesion containing a large amount of liquid within the cyst and popcorn-like calcification in the wall. In this report, we describe the contrast-enhanced spectral mammography (CESM), ultrasonography, and computed tomography findings and provide a reference for the diagnosis of EICs. To the best of our knowledge, this is the first report of the CESM findings of an EIC. Our case illustrates that CESM has excellent performance similar to that of magnetic resonance imaging and is much more effective than conventional digital mammography. Additionally, our case indicates that precise correlation of CESM with ultrasonography findings contributes to the diagnosis of EICs. This rare case with multiple imaging findings will increase the awareness of EICs in the breast parenchyma.

Radiomics and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography in the Breast Lesions Classification

The aim of the study was to estimate the diagnostic accuracy of textural features extracted by dual-energy contrast-enhanced mammography (CEM) images, by carrying out univariate and multivariate statistical analyses including artificial intelligence approaches. In total, 80 patients with known breast lesion were enrolled in this prospective study according to regulations issued by the local Institutional Review Board. All patients underwent dual-energy CEM examination in both craniocaudally (CC) and double acquisition of mediolateral oblique (MLO) projections (early and late). The reference standard was pathology from a surgical specimen for malignant lesions and pathology from a surgical specimen or fine needle aspiration cytology, core or Tru-Cut needle biopsy, and vacuum assisted breast biopsy for benign lesions. In total, 104 samples of 80 patients were analyzed. Furthermore, 48 textural parameters were extracted by manually segmenting regions of interest. Univariate and multivariate approaches were performed: non-parametric Wilcoxon–Mann–Whitney test; receiver operating characteristic (ROC), linear classifier (LDA), decision tree (DT), k-nearest neighbors (KNN), artificial neural network (NNET), and support vector machine (SVM) were utilized. A balancing approach and feature selection methods were used. The univariate analysis showed low accuracy and area under the curve (AUC) for all considered features. Instead, in the multivariate textural analysis, the best performance considering the CC view (accuracy (ACC) = 0.75; AUC = 0.82) was reached with a DT trained with leave-one-out cross-variation (LOOCV) and balanced data (with adaptive synthetic (ADASYN) function) and a subset of three robust textural features (MAD, VARIANCE, and LRLGE). The best performance (ACC = 0.77; AUC = 0.83) considering the early-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of ten robust features (MEAN, MAD, RANGE, IQR, VARIANCE, CORRELATION, RLV, COARSNESS, BUSYNESS, and STRENGTH). The best performance (ACC = 0.73; AUC = 0.82) considering the late-MLO view was reached with a NNET trained with LOOCV and balanced data (with ADASYN function) and a subset of eleven robust features (MODE, MEDIAN, RANGE, RLN, LRLGE, RLV, LZLGE, GLV_GLSZM, ZSV, COARSNESS, and BUSYNESS). Multivariate analyses using pattern recognition approaches, considering 144 textural features extracted from all three mammographic projections (CC, early MLO, and late MLO), optimized by adaptive synthetic sampling and feature selection operations obtained the best results (ACC = 0.87; AUC = 0.90) and showed the best performance in the discrimination of benign and malignant lesions.

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.

Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images

Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a set of 58 regions of interest (ROIs) extracted from 53 patients referred to Istituto Tumori "Giovanni Paolo II" of Bari (Italy) for the breast cancer screening phase between March 2017 and June 2018. We extracted 464 features of different kinds, such as points and corners of interest, textural and statistical features from both the original ROIs and the ones obtained by a Haar decomposition and a gradient image implementation. The features data had a large dimension that can affect the process and accuracy of cancer classification. Therefore, a classification scheme for dimension reduction was needed. Specifically, a principal component analysis (PCA) dimension reduction technique that includes the calculation of variance proportion for eigenvector selection was used. For the classification method, we trained three different classifiers, that is a random forest, a naïve Bayes and a logistic regression, on each sub-set of principal components (PC) selected by a sequential forward algorithm. Moreover, we focused on the starting features that contributed most to the calculation of the related PCs, which returned the best classification models. The method obtained with the aid of the random forest classifier resulted in the best prediction of benign/malignant ROIs with median values for sensitivity and specificity of 88.37% and 100%, respectively, by using only three PCs. The features that had shown the greatest contribution to the definition of the same were almost all extracted from the LE images. Our system could represent a valid support tool for radiologists for interpreting CESM images.

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.

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

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

Contrast-Enhanced Spectral Mammography-Based Radiomics Nomogram for the Prediction of Neoadjuvant Chemotherapy-Insensitive Breast Cancers

Purpose

We developed and validated a contrast-enhanced spectral mammography (CESM)-based radiomics nomogram to predict neoadjuvant chemotherapy (NAC)-insensitive breast cancers prior to treatment.

Methods

We enrolled 117 patients with breast cancer who underwent CESM examination and NAC treatment from July 2017 to April 2019. The patients were grouped randomly into a training set (n = 97) and a validation set (n = 20) in a ratio of 8:2. 792 radiomics features were extracted from CESM images including low-energy and recombined images for each patient. Optimal radiomics features were selected by using analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation, to develop a radiomics score in the training set. A radiomics nomogram incorporating the radiomics score and independent clinical risk factors was then developed using multivariate logistic regression analysis. With regard to discrimination and clinical usefulness, radiomics nomogram was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC) and decision curve analysis (DCA).

Results

The radiomics nomogram that incorporates 11 radiomics features and 3 independent clinical risk factors, including Ki-67 index, background parenchymal enhancement (BPE) and human epidermal growth factor receptor-2 (HER-2) status, showed an encouraging discrimination power with AUCs of 0.877 [95% confidence interval (CI) 0.816 to 0.924] and 0.81 (95% CI 0.575 to 0.948) in the training and validation sets, respectively. DCA revealed the increased clinical usefulness of this nomogram.

Conclusion

The proposed radiomics nomogram that integrates CESM-derived radiomics features and clinical parameters showed potential feasibility for predicting NAC-insensitive breast cancers.

[Contrast-enhanced mammography]

Early detection is of great importance for the successful treatment of breast cancer and for a good prognosis. Contrast-enhanced mammography and especially contrast-enhanced spectral mammography (CESM) show promising initial results and are a valuable addition to currently available methods. The advantage of these methods is that imaging of both breasts can be performed in a single examination with a single contrast agent application. The accuracy of CESM is similar to that of magnetic resonance imaging (MRI), easily available at low costs, which is why this procedure is increasingly used in the diagnostic work up of breast cancer. CESM is also a good alternative to MRI if this cannot be performed due to contraindications.

Contrast-enhanced mammography: past, present, and future

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

Contrast-Enhanced Mammography for Screening Women after Breast Conserving Surgery

Simple Summary

Breast cancer survivors are at risk for recurrence, and the early detection of recurrence improves survival. Therefore, imaging surveillance is performed for women who have breast-conserving surgery. The aim of our retrospective study was to compare routine mammography with contrast-enhanced mammography in the screening (asymptomatic) post-treatment setting. We confirmed that when screening women with breast conservation surgery, contrast-enhanced mammography had a higher cancer detection rate (15.4/1000) and positive predictive value of biopsies (42.9%) than full-field digital mammography (6.2/1000 and 37.5%, respectively).

Abstract

To investigate the value of contrast-enhanced mammography (CEM) compared to full-field digital mammography (FFDM) in screening breast cancer patients after breast-conserving surgery (BCS), this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved retrospective, single-institution study included 971 CEM exams in 541 asymptomatic patients treated with BCS who underwent screening CEM between January 2013 and November 2018. Histopathology, or at least a one-year follow-up, was used as the standard of reference. Twenty-one of 541 patients (3.9%) were diagnosed with ipsi- or contralateral breast cancer: six (28.6%) cancers were seen with low-energy images (equivalent to FFDM), an additional nine (42.9%) cancers were detected only on iodine (contrast-enhanced) images, and six interval cancers were identified within 365 days of a negative screening CEM. Of the 10 ipsilateral cancers detected on CEM, four were detected on low-energy images (40%). Of the five contralateral cancers detected on CEM, two were detected on low-energy images (40%). Overall, the cancer detection rate (CDR) for CEM was 15.4/1000 (15/971), and the positive predictive value (PPV3) of the biopsies performed was 42.9% (15/35). For findings seen on low-energy images, with or without contrast, the CDR was 6.2/1000 (6/971), and the PPV3 of the biopsies performed was 37.5% (6/16). In the post-BCS screening setting, CEM has a higher CDR than FFDM.

Contrast-Enhanced Digital Mammography: Technique, Clinical Applications, and Pitfalls

OBJECTIVE. Contrast-enhanced digital mammography (CEDM) combines the high spatial resolution of mammography with the improved enhancement provided by contrast medium. In this article, CEDM technique-the current and potential clinical applications and current challenges-will be reviewed. CONCLUSION. CEDM is a promising technique in the supplemental evaluation of patients with mammographically inconclusive findings and potentially in the screening of women with mammographically dense breasts. CEDM is emerging as a cost-effective alternative to dynamic contrast-enhanced MRI to stage newly diagnosed breast cancer and evaluate response to neoadjuvant chemotherapy.

Retrospective Comparison of Contrast-Enhanced Spectral Mammography with Digital Mammography in Assessing Tumor Size in 668 Cases of Breast Cancer

Background

Contrast-enhanced spectral mammography (CESM) is digital mammography with contrast agent. This promising new breast imaging method can be used for planning surgical treatment. This study compared CESM versus digital mammography (MG) in evaluating tumor size in breast cancer.

Material/Methods

Comparison of tumor dimensions in CESM, MG, and histopathology was made. The correlation of these data was assessed by histopathological type, biological subtype, grading of the carcinoma, and patient age.

Results

The average difference in tumor size between CESM and histopathological examination was 5 mm. The differences in size measurement between CESM and MG were significant (p=0.00). The Pearson’s linear correlation coefficients of CESM versus HP and MG versus HP were −0.01 (p=0.79) and −0.25 (p=0.00), respectively, indicating no differences between CESM and HP based on the lesion size. A weak negative correlation between those values was observed on MG. No relationship was found between the tumor size in CESM and the biological subtype, carcinoma malignancy degree, or patient age.

Conclusions

CESM is a new diagnostic method in breast cancer. The accuracy of measurement of tumor size using CESM is independent of lesion size, but it overestimates the size by 5 mm on average. The difference is not dependent on grading, biological subtype of the carcinoma, or patient age. They concern the histopathological type, and values are significantly greater in pre-invasive carcinomas.

Contrast-Enhanced Spectral Mammography Versus Ultrasonography: Diagnostic Performance in Symptomatic Patients with Dense Breasts

Objective

To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) versus ultrasonography (US) in symptomatic patients with dense breasts, while using histology as the gold standard.

Materials and Methods

After obtaining approval from the local ethics board, this prospective study collected data from patients with symptomatic breasts who underwent CESM and US examinations from May 1, 2017 to September 30, 2017. We then selected those with dense breasts and pathological results as our sample population. Both CESM and US results were classified by a radiologist through the Breast Imaging Reporting and Data System, and the results were compared with their corresponding histological results. The chi-square test was conducted to compare the diagnostic performance of CESM and US, and the receiver operating characteristic curves for the two imaging modalities were obtained.

Results

A total of 131 lesions from 115 patients with dense breasts were included in this study. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 93.8%, 88.1%, 88.2%, 93.7%, and 90.8% for CESM, and 90.6%, 82.1%, 82.9%, 90.2%, and 86.3% for US, respectively. The p values for sensitivity, specificity, PPV, NPV, and accuracy were 0.687, 0.388, 0.370, 0.702, and 0.238, respectively. The area under the curve of CESM (0.917) was comparable with that of US (0.884); however, the differences between CESM and US were not statistically significant (p = 0.225). Eight false-positive cases and 4 false-negative cases for breast cancer were found in CESM, while 12 false-positive cases and 6 false-negative cases were found in US.

Conclusion

The diagnostic performances of CESM and US are comparable in symptomatic women with dense breasts; however, the routine use of additional US imaging is questionable for lesions that can be detected by CESM.

Clinical performance of contrast-enhanced spectral mammography in pre-surgical evaluation of breast malignant lesions in dense breasts: a single center study

PURPOSE

To compare the efficacy of contrast-enhanced spectral mammography, with ultrasound, full field digital mammography and magnetic resonance imaging in detection and size estimation of histologically proven breast tumors.

METHODS

This open-label, single center, prospective study, included 160 dense breast women with at least one suspicious mammary lesion evaluated by ultrasound, full field digital mammography and magnetic resonance imaging in whom a mammary tumor was histologically proven after surgery performed at the European Institute of Oncology between January 2013 and December 2015. Following the complete diagnostic procedure, the patients were further investigated by contrast-enhanced spectral mammography prior to surgery.

RESULTS

Overall, the detection rate of malignant breast lesions (in situ and invasive) was 93.8% (165/176) for contrast-enhanced spectral mammography, 94.4% (168/178) for ultrasound, 85.5 (147/172) for full field digital mammography and 97.7% (173/177) for magnetic resonance imaging. Radiological measurements were concordant with the post-surgical pathological measurements of the invasive tumor (i.e., within 5 mm) in: 64.6% for contrast-enhanced spectral mammography, 62.0% for ultrasound, 45.2% for full field digital mammography (p < 0.0001) and 69.9% for magnetic resonance imaging (p = 0.28); underestimated in: 17.4% for contrast-enhanced spectral mammography, 19.6% for ultrasound, 24.2% for full field digital mammography (p = 0.03) and 6.7% for magnetic resonance imaging (p = 0.0005); and overestimated in: 16.2% for contrast-enhanced spectral mammography, 16.6% for ultrasound, 16.6% for full field digital mammography and 22.7% for magnetic resonance imaging (p = 0.02).

CONCLUSIONS

Our data suggest that contrast-enhanced spectral mammography improves on full field digital mammography and is comparable to ultrasound and magnetic resonance imaging in terms of detection sensitivity and size estimation of malignant lesions in dense breasts.

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.

Factors Associated With Background Parenchymal Enhancement on Contrast-Enhanced Mammography

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

The new method, the old problem - role of contrast-enhanced spectral mammography in the diagnosis of breast cancer among Polish women

Purpose

The aim of the study was to evaluate spectral mammography (CESM) in diagnosing breast cancer, which is based on sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Material and methods

The study included a group of 547 women who underwent spectral mammography and histopathological verification of the lesion, previously seen in mammography and/or ultrasound. In the group of 547 women, 593 focal lesions were diagnosed. All CESM examinations were carried-out with a digital mammography device dedicated to performing dual-energy CESM acquisitions. An intravenous injection of 1.5 ml/kg of body mass of non-ionic contrast agent was performed.

Results

The analysis includes 593 breast lesions, in this group cancer was detected in 327 (55.14%) lesions, and in 256 (43.17%) cases benign lesions were confirmed by histopathological examination and at least 12 months of observation. The method shows differentiation of benign and malignant lesions in the breast: sensitivity of 97.86%, specificity of 59.4%, PPV – 74.76%, NPV – 95.76%.

Conclusions

Spectral mammography could be an ideal method to detect breast cancer. Thanks to the high NPV (95.76%), it facilitates the exclusion of cancer in situations where pathological contrast enhancement is not observed. The unsatisfactory specificity of the study (59.4%) would not make it safe to avoid a core needle biopsy of lesions that undergo contrast enhancement.

Management of breast cancer risk in BRCA1/2 mutation carriers who are unaffected with cancer

Pathogenic mutations in BRCA1 and BRCA2 genes markedly increase the risk of breast cancer and other cancers such as ovarian/fallopian tube, pancreatic, prostate, and melanoma. Patients with BRCA1 mutations have a slightly higher lifetime risk of breast cancer than BRCA2 mutation carriers, and both BRCA1 and BRCA2 carriers tend to develop breast cancer at an earlier age than the general population. In this review, we will discuss management recommendations to reduce breast cancer risk for BRCA1/2 mutation carriers including special populations of carriers such as pregnant or lactating patients and men. Breast cancer screening, including clinical breast examination, mammogram, and breast MRI, is important for detecting breast cancer at an early and likely curable stage. In addition to screening, counseling on risk-reducing surgeries is strongly recommended for BRCA1/2 carriers. Risk-reducing mastectomy decreases the risk of breast cancer development, and risk-reducing salpingo-oophorectomy decreases ovarian cancer-specific as well as overall mortality, but controversy exists regarding its impact on breast cancer-specific mortality. Given the effectiveness of screening for breast cancer, further management should be carried out on an individual basis taking into account quality of life and psychosocial factors, and recommendations should be readdressed periodically as science progresses and patients' goals may change.

Contrast Enhanced Digital Mammography (CEDM) Helps to Safely Reduce Benign Breast Biopsies for Low to Moderately Suspicious Soft Tissue Lesions

RATIONALE AND OBJECTIVES

To preliminarily asses if Contrast Enhanced Digital Mammography (CEDM) can accurately reduce biopsy rates for soft tissue BI-RADS 4A or 4B lesions.

MATERIALS AND METHODS

Eight radiologists retrospectively and independently reviewed 60 lesions in 54 consenting patients who underwent CEDM under Health Insurance Portability and Accountability Act compliant institutional review board-approved protocols. Readers provided Breast Imaging Reporting & Data System ratings sequentially for digital mammography/digital breast tomosynthesis (DM/DBT), then with ultrasound, then with CEDM for each lesion. Area under the curve (AUC), true positive rates and false positive rates, positive predictive values and negative predictive values were calculated. Statistical analysis accounting for correlation between lesion-examinations and between-reader variability was performed using OR/DBM (for SAS v.3.0), generalized linear mixed model for binary data (proc glimmix, SAS v.9.4, SAS Institute, Cary North Carolina), and bootstrap.

RESULTS

The cohort included 49 benign, two high-risk and nine cancerous lesions in 54 women aged 34-74 (average 50) years. Reader-averaged AUC for CEDM was significantly higher than DM/DBT alone (0.85 versus 0.66, p < 0.001) or with US (0.85 versus 0.75, p = 0.001). CEDM increased true positive rates from 0.74 under DB/DBT, and 0.89 with US, to 0.90 with CEDM, (p = 0.019 DM/DBT versus CEDM, p = 0.78 DM/DBT + US versus CEDM) and decreased false positive rates from 0.47 using DM/DBT and 0.61 with US to 0.39 with CEDM (p = 0.017 DM/DBT versus CEDM, p = 0.001 DM/DBT+ US versus CEDM). For an expected cancer rate of 10%, CEDM positive predictive values was 20.5% (95% CI: 16%-27%) and negative predictive values 98.3% (95% CI: 96%-100%).

CONCLUSION

Addition of CEDM for evaluation of low-moderate suspicion soft tissue breast lesions can substantially reduce biopsy of benign lesions without compromising cancer detection.

Quantitative Analysis of Enhancement Intensity and Patterns on Contrast-enhanced Spectral Mammography

CESM is an emerging digital mammography technology with a high breast cancer detection and a limited diagnostic specificity. In order to improve specificity, we quantitatively assessed enhancement intensity of breast lesions with different pathological types and hormonal receptor status and evaluated the consistency of enhancement patterns between CESM and DCE-MRI. A total of 145 lesions were enrolled, consisting of 43 malignant (17 non-infiltrating cancers and 26 infiltrating cancers) and 99 benign lesions. The diagnostic performance of enhancement intensity in the former positions was significantly higher than that in the latter positions (AUC: 0.834 vs. 0.755, p = 0.0008). Infiltrating cancers showed the highest enhancement intensity, while benign lesions the lowest (mean CNR₁: 7.6% vs. 2.7%; median CNR₁: 6.8% vs. 2.7%). Enhancement intensity of ER or PR positive group was weaker than negative group, while HER-2 positive group was stronger than negative group. 28 patients with 28 lesions performed both CESM and DCE-MRI examinations, showing a coincidence rate of 64.2% and moderate agreement (k = 0.515) between CESM and DCE-MRI. In conclusion, quantitative analysis of enhancement characteristics is feasible to the diagnosis practice on CESM.

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.

Added value of contrast-enhanced mammography (CEM) in staging of malignant breast lesions-a feasibility study

OBJECTIVES

The aim of this feasibility study was to evaluate the added value of contrast-enhanced mammography (CEM) in preoperative staging of malignant breast lesions, beyond standard assessment with digital mammography and ultrasound, as a base for a future prospective randomized trial.

MATERIALS AND METHODS

Forty-seven patients, with confirmed or strongly suspected malignant breast lesions after standard assessment (digital mammography (DM) and ultrasound (US)), scheduled for primary surgery, were invited to undergo CEM as an additional preoperative procedure. The primary endpoint was change in treatment due to CEM findings, defined as mastectomy instead of partial mastectomy or contrariwise, bilateral surgery instead of unilateral or neoadjuvant treatment instead of primary surgery. Accuracy in tumour extent estimation compared to histopathology was evaluated by Bland-Altman statistics. Number of extra biopsies and adverse events were recorded.

RESULTS

In 10/47 patients (21%), findings from CEM affected the primary treatment. Agreement with histopathology regarding extent estimation was better for CEM (mean difference - 1.36, SD ± 18.45) in comparison with DM (- 4.18, SD ± 26.20) and US (- 8.36, SD ± 24.30). Additional biopsies were taken from 19 lesions in 13 patients. Nine biopsies showed malignant outcome. No major adverse events occurred.

CONCLUSION

The feasibility of preoperative additional CEM was found to be satisfactory without any serious negative effects. Results imply an added value of CEM in preoperative staging of breast cancer. Further evaluation in larger prospective randomized trials is needed.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03402529. Registered 18 January 2018-retrospectively registered.

Evaluation of average glandular dose and investigation of the relationship with compressed breast thickness in dual energy contrast enhanced digital mammography and digital breast tomosynthesis

PURPOSE

To quantitatively assess the dose of Dual energy contrast enhanced digital mammography (CEDM) and digital breast tomosynthesis (DBT) and to investigate the relationship between average absorbed glandular dose (AGD), compressed breast thickness (CBT) and compression force (CF).

MATERIALS AND METHODS

All CEDM and DBT examinations were performed in cranio-caudal (CC) and medio-lateral oblique (MLO) view. Exposure parameters of 135 mammographic procedures that using AEC (automatic exposure control) mode were recorded. AGDs were calculated. Kruskal Wallis test was performed.

RESULTS

CBT population ranged from 23 to 94 mm with a thickness median value of 52 mm in CC view and of 57 mm in MLO views. CEDM AGD median value was significatively lower than DBT AGD in each views (p << 0.01). AGD showed a positive correlation and linear regression with CBT for both CEDM and DBT while CF did not show a correlation and linear regression with AGD. The highest values were found for MLO view: R2 of 0.74 for CEDM and R2 of 0.61 for DBT. Kruskal Wallis test shows that there was a difference statistically significant between AGD values of CEDM and DBT in CC view respect to MLO views (p < 0.01).

CONCLUSIONS

Dose values of both techniques meet the recommendations for maximum dose in mammography. The results of the present study indicated that there was significant difference between AGD for CEDM and DBT exposure in different views (AGD in CC views had the lowest value) and that CBT could influence the AGD while CF was not correlated to AGD.

A meta-analysis of contrast-enhanced spectral mammography versus MRI in the diagnosis of breast cancer

Background

To identify the performance of contrast‐enhanced spectral mammography (CESM) and magnetic resonance imaging (MRI) for breast cancer diagnosis by pooling the open published data.

Methods

A systematic review of studies relevant to CESM and MRI in the diagnosis of breast cancer were screened in the electronic databases of Pubmed, EMBASE, the Cochrane Library, Web of Science, Google scholar and CNKI. The methodical quality of the included publications was evaluated by the quality assessment of diagnostic accuracy studies‐2 (QUADAS‐2). The diagnostic sensitivity, specificity and area under the ROC curve (AUC) were pooled and the true positive (TP), false positive (FP), false negative (FN) and true negative (TN) of the original studies were calculated.

Results

A total of 13 diagnostic publications were identified and included in the meta‐analysis. Of those included, five were retrospective studies and the remaining eight were prospective work. The combined data indicating the pooled sensitivity and specificity of CESM and MRI were 0.97 (95% CI: 0.95–0.98), 0.66 (95% CI: 0.59–0.71), 0.97 (95% CI: 0.95–0.98),and 0.52 (95% CI: 0.46–0.58), respectively. The pooled +LR and –LR for CESM were 2.70 (95% CI: 1.57–4.65), 0.06 (95% CI: 0.04–0.09), and 2.01 (95% CI: 1.78–2.26), 0.08 (95% CI: 0.05–0.11) for MRI, respectively. For the diagnostic odds ratio (DOR), the pooled results of CESM and MRI were 60.15 (95% CI: 24.72–146.37) and 31.34 (95% CI: 19.61–50.08), respectively. The AUC of the symmetric receiver operating characteristic curve (SROC) was 0.9794 and 0.9157 for CESM and MRI, respectively, calculated using the Moses model in the diagnosis of breast cancer.

Conclusions

Both CESM and MRI are effective methods for the detection of breast cancer with high diagnostic sensitivity. The diagnostic performance of CESM appears to be more effective than MRI.

Preferences and Attitudes Regarding Adjunct Breast Cancer Screening Among Patients with Dense Breasts

OBJECTIVE

New breast screening modalities are being investigated to address the need for more sensitive breast cancer screening in women with dense breasts. We investigated the preferences and attitudes of these patients regarding adjunct screening modalities to help evaluate the acceptability of these exams.

METHODS

In this institutional review board-approved prospective study, patients with dense breasts on their prior mammogram were invited to complete a survey. Patients were asked to estimate their personal breast cancer risk compared with peers, indicate their level of concern related to screening callbacks, radiation exposure, and intravenous (IV) contrast allergies, and identify which factors might deter them from getting adjunct screening exams.

RESULTS

Five hundred eight patients with dense breasts presenting for screening mammography completed surveys. While most patients (304/508, 59.9%) felt it was likely or very likely that cancer could be missed on their mammogram, only 8.9% (45/508) had undergone adjunct screening exams in the past 3 years. The most commonly cited deterrents to adjunct screening were cost (340/508, 66.9%), pain (173/508, 34.1%), and concern that adjunct screening could lead to additional procedures (158/508, 31.1%). When asked to select among three hypothetical breast cancer screening modalities, patients strongly preferred the more sensitive examination, even if this involved greater cost (162/508, 31.9%) or IV-contrast administration (315/508, 62.0%).

CONCLUSION

Our data suggest that patients with dense breasts prefer adjunct screening exams that are both sensitive and inexpensive, although an increase in sensitivity could outweigh additional cost or even IV-line placement.

The added value of digital breast tomosynthesis in improving diagnostic performance of BI-RADS categorization of mammographically indeterminate breast lesions

Background

Mammographic findings are seen more clearly in tomographic images with consequent improvement of Breast Imaging Reporting and Data System (BI-RADS) in categorization of indeterminate breast lesions. This study aimed to evaluate the added value of digital breast tomosynthesis (DBT) to BI-RADS classification in categorization of indeterminate breast lesions after digital mammography (DM) as an initial approach.

Methods and results

We prospectively evaluated 296 women with BI-RADS indeterminate breast lesions (BI-RADS 0, 3, and 4) by DM between January 2018 and October 2019. All patients underwent DBT. Two radiologists evaluated lesions and assigned a BI-RADS category to each lesion according to BI-RADS lexicon 2013 classification using DM, DBT, and combined DM and DBT. The results were compared in terms of main radiological features, diagnostic performance, and BI-RADS classification using histopathology as the reference standard. A total of 355 lesions were detected on DBT and 318 lesions on DM. Thirty-seven lesions were detected by DBT and not seen by DM. The final diagnoses of 355 lesions were 58.3% benign and 41.7% malignant. In comparison to DM, DBT produced 31.5% upgrading and 35.2% downgrading of BI-RADS scoring of breast lesions. DBT reduced number of BI-RADS 3 and 4, compared to DM. All upgraded BI-RADS 4 were malignant. The combination of DBT and DM significantly increased the performance of BI-RADS in the diagnosis of indeterminate breast lesions versus DM or DBT alone (p < 0.001).

Conclusion

Adding DBT to BI-RADS improves its diagnostic performance in detection and characterization of mammography indeterminate breast lesions.

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.

A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI

BACKGROUND

Differentiate malignant from benign enhancing foci on breast magnetic resonance imaging (MRI) through radiomic signature.

METHODS

Forty-five enhancing foci in 45 patients were included in this retrospective study, with needle biopsy or imaging follow-up serving as a reference standard. There were 12 malignant and 33 benign lesions. Eight benign lesions confirmed by over 5-year negative follow-up and 15 malignant histopathologically confirmed lesions were added to the dataset to provide reference cases to the machine learning analysis. All MRI examinations were performed with a 1.5-T scanner. One three-dimensional T1-weighted unenhanced sequence was acquired, followed by four dynamic sequences after intravenous injection of 0.1 mmol/kg of gadobenate dimeglumine. Enhancing foci were segmented by an expert breast radiologist, over 200 radiomic features were extracted, and an evolutionary machine learning method ("training with input selection and testing") was applied. For each classifier, sensitivity, specificity and accuracy were calculated as point estimates and 95% confidence intervals (CIs).

RESULTS

A k-nearest neighbour classifier based on 35 selected features was identified as the best performing machine learning approach. Considering both the 45 enhancing foci and the 23 additional cases, this classifier showed a sensitivity of 27/27 (100%, 95% CI 87-100%), a specificity of 37/41 (90%, 95% CI 77-97%), and an accuracy of 64/68 (94%, 95% CI 86-98%).

CONCLUSION

This preliminary study showed the feasibility of a radiomic approach for the characterisation of enhancing foci on breast MRI.

Preoperative assessment of contrast-enhanced spectral mammography of diagnosed breast cancers after sonographic biopsy: Correlation to contrast-enhanced magnetic resonance imaging and 5-year postoperative follow-up

To assess the feasibility of using contrast-enhanced spectral mammography (CESM) for operative planning of patients with breast cancers who were initially diagnosed by sonographic guided biopsy.With the approval of the Institutional Review Board of our hospital, we retrospectively reviewed the data on patients with breast cancers who underwent CESM and contrast-enhanced magnetic resonance imaging (CE-MRI) prior to operation and were followed up for at least 5 years postoperatively. The patients with breast cancer diagnosed by sonographic guided biopsy without mammography were included for analysis. The size and number of cancers on low-energy mammograms (LE-MG), recombined subtracted mammograms (RSM), and CE-MRI were recorded and compared with microscopic histopathologic data and at least 5 years of clinical follow-up data.Fifty-one cancerous breasts of 46 patients were included in the analysis. All the principal cancers could be detected by RSM or CE-MRI; however, only 45 were by LE-MG. The Pearson correlation coefficients for the size on microscopy were 0.44 for LE-MG, 0.77 for RSM, and 0.84 for CE-MRI (all P-values ≤.001). Regarding the microscopic reports, RSM or CE-MRI had sensitivities of 100% and a positive predictive value of 63.6% for multicentric cancers. One breast cancer with partial mastectomy recurred after 3 years of follow-up.CESM was feasible for assessing the cancer extension and multicentric cancers as secondary examination in patients with diagnosed breast cancers after sonographic biopsy.

Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification

To compare diagnostic performance of contrast-enhanced dual-energy digital mammography (CEDM) and digital breast tomosynthesis (DBT) alone and in combination compared to 2D digital mammography (MX) and dynamic contrast-enhanced MRI (DCE-MRI) in women with breast lesions. We enrolled 100 consecutive patients with breast lesions (BIRADS 3-5 at imaging or clinically suspicious). CEDM, DBT, and DCE-MRI 2D were acquired. Synthetized MX was obtained by DBT. A total of 134 lesions were investigated on 111 breasts of 100 enrolled patients: 53 were histopathologically proven as benign and 81 as malignant. Nonparametric statistics and receiver operating characteristic (ROC) curve were performed. Two-dimensional synthetized MX showed an area under ROC curve (AUC) of 0.764 (sensitivity 65%, specificity 80%), while AUC was of 0.845 (sensitivity 80%, specificity 82%) for DBT, of 0.879 (sensitivity 82%, specificity 80%) for CEDM, and of 0.892 (sensitivity 91%, specificity 84%) for CE-MRI. DCE-MRI determined an AUC of 0.934 (sensitivity 96%, specificity 88%). Combined CEDM with DBT findings, we obtained an AUC of 0.890 (sensitivity 89%, specificity 74%). A difference statistically significant was observed only between DCE-MRI and CEDM (P = .03). DBT, CEDM, CEDM combined to tomosynthesis, and DCE-MRI had a high ability to identify multifocal and bilateral lesions with a detection rate of 77%, 85%, 91%, and 95% respectively, while 2D synthetized MX had a detection rate for multifocal lesions of 56%. DBT and CEDM have superior diagnostic accuracy of 2D synthetized MX to identify and classify breast lesions, and CEDM combined with DBT has better diagnostic performance compared with DBT alone. The best results in terms of diagnostic performance were obtained by DCE-MRI. Dynamic information obtained by time-intensity curve including entire phase of contrast agent uptake allows a better detection and classification of breast lesions.

Adding the merits of contrast to the ease of mammography; can we highlight what’s behind breast asymmetries?

Background

Breast symmetry is one of the major things that radiologists assess when looking at mammograms and is one of the most challenging mammographic findings to evaluate. Contrast-enhanced spectral mammography (CESM) is an emerging mammography technique that has shown comparable sensitivity and specificity to MRI. The purpose of this study is to assess the value of CESM in characterization of breast asymmetries (BAs) and if it should be incorporated in its diagnostic work-up.

Results

Three hundred sixty-five patients with mean age of 47 years were included in the study. CESM was performed aiming for characterization of 380 suspicious or indeterminate breast asymmetries. Assessment of subtracted high-energy images (HEI) markedly improves the overall accuracy reaching 88.4%. Further improvement of the overall accuracy was achieved on combined assessment of the low-energy images (LEI), subtracted high-energy images (HEI), and ultrasound reaching 91.3%.

Conclusion

CESM is considered as a valuable complementary imaging tool considering the evaluation of breast asymmetries and should be incorporated in its diagnostic work-up in cases not resolved on an initial combined mammography and targeted ultrasound study especially in the presence of a heterogeneous dense breast parenchyma. Yet, this may be hindered in the presence of inflammatory signs because of the overlapping imaging criteria.

Preoperative loco-regional staging of invasive lobular carcinoma with contrast-enhanced digital mammography (CEDM)

The aim of our study was to assess the performance of contrast-enhanced digital mammography (CEDM) in the preoperative loco-regional staging of invasive lobular carcinoma (ILC) patients, about the valuation of the extension of disease and in measurement of lesions. Then, we selected retrospectively, among the 1500 patients underwent to CEDM at the Breast Diagnostics Department of the Careggi University Hospital of Florence and the National Cancer Institute of Milan from September 2016 to November 2018, 31 women (mean age 57.1 aa; range 41-78 aa) with a definitive histological diagnosis of ILC. CEDM has proved to be a promising imaging technique, being characterized by a sensitivity of 100% in the detection of the index lesion, and of 84.2% in identifying any adjunctive lesions: It was the presence of a non-mass enhancement (NME) to lower the sensitivity of the technique (25% vs. 100% for mass-like enhancements or a mass closely associated with a NME). Specificity in the characterization of additional lesions was 66.7%, and the diagnosis of the extension of disease was correct in 77.4% of cases: NME also led to a decrease in diagnostic accuracy in the evaluation of disease extension up to 40% versus 85% for masses and 80% for masses associated with NME (M/NME). Moreover, in 12/31 (38.7%), CEDM allowed to correctly identify lesions not shown by mammography + ultrasonography + tomosynthesis: In the half of these (6/12), there was a multicentricity, thus allowing an adequate surgical planning change. CEDM was also very accurate in analyzing the maximum diameter of the masses, while it was much less reliable in the case of the M/NME and pure NME. In conclusion, CEDM is a new promising imaging technique in the loco-regional preoperative staging and in the evaluation of disease extension for ILC, especially in case of mass enhancement lesions.

Radiomics Analysis on Contrast-Enhanced Spectral Mammography Images for Breast Cancer Diagnosis: A Pilot Study

Contrast-enhanced spectral mammography is one of the latest diagnostic tool for breast care; therefore, the literature is poor in radiomics image analysis useful to drive the development of automatic diagnostic support systems. In this work, we propose a preliminary exploratory analysis to evaluate the impact of different sets of textural features in the discrimination of benign and malignant breast lesions. The analysis is performed on 55 ROIs extracted from 51 patients referred to Istituto Tumori “Giovanni Paolo II” of Bari (Italy) from the breast cancer screening phase between March 2017 and June 2018. We extracted feature sets by calculating statistical measures on original ROIs, gradiented images, Haar decompositions of the same original ROIs, and on gray-level co-occurrence matrices of the each sub-ROI obtained by Haar transform. First, we evaluated the overall impact of each feature set on the diagnosis through a principal component analysis by training a support vector machine classifier. Then, in order to identify a sub-set for each set of features with higher diagnostic power, we developed a feature importance analysis by means of wrapper and embedded methods. Finally, we trained an SVM classifier on each sub-set of previously selected features to compare their classification performances with respect to those of the overall set. We found a sub-set of significant features extracted from the original ROIs with a diagnostic accuracy greater than 80 % . The features extracted from each sub-ROI decomposed by two levels of Haar transform were predictive only when they were all used without any selection, reaching the best mean accuracy of about 80 % . Moreover, most of the significant features calculated by HAAR decompositions and their GLCMs were extracted from recombined CESM images. Our pilot study suggested that textural features could provide complementary information about the characterization of breast lesions. In particular, we found a sub-set of significant features extracted from the original ROIs, gradiented ROI images, and GLCMs calculated from each sub-ROI previously decomposed by the Haar transform.