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

Contrast-enhanced Mammography versus MR Imaging of the Breast

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

State-of-the-art for contrast-enhanced mammography

Contrast-enhanced mammography (CEM) is an emerging breast imaging technology with promise for breast cancer screening, diagnosis, and procedural guidance. However, best uses of CEM in comparison with other breast imaging modalities such as tomosynthesis, ultrasound, and MRI remain inconclusive in many clinical settings. This review article summarizes recent peer-reviewed literature, emphasizing retrospective reviews, prospective clinical trials, and meta-analyses published from 2020 to 2023. The intent of this article is to supplement prior comprehensive reviews and summarize the current state-of-the-art of CEM.

BIRADS 4 - Is it possible to downgrade lesions that do not enhance on recombinant contrast-enhanced mammography images?

PURPOSE

Analysis of the morphology of lesions classified into the BI-RADS 4 category and assessment of the possibility of downgrade the BI-RADS category in those that did not show enhancement on recombinant contrast-enhanced mammography (CEM) images.

METHOD

The retrospective, single-center study included 528 patients who underwent a core needle biopsy performed from January 2017 to November 2022 due to a breast lesion classified as BI-RADS 4 on CEM. Patients' electronic records and imaging examinations were reviewed. Individual lesions were classified into the morphological categories of mass, non-mass, and microcalcifications. Sensitivity, specificity, positive as well as negative predictive values were calculated for the whole group and individual morphological categories. The influence of the lesions' diameter on the results was analyzed.

RESULTS

CEM NPV for the whole group was 93.9% (±95% CI: 90.0-96.4), for mass lesions 100% (±95% CI: 94.5-100), for non-mass lesions 97.8% (±95% CI: 87.0-99.9) and 87.9% (±95% CI: 80.3-93.0) for microcalcifications. Given that 230 out of 383 benign lesions were not contrast-enhancing, 60.1% of unnecessary CNBs would have been correctly avoided. CEM sensitivity for lesions < 20 mm was lower than for lesions ≥ 20 mm and was respectively 86.6% (±95% CI: 76.8-92.8) vs 94.6% (±95% CI: 86.0-98.2), respectively.

CONCLUSION

CEM is characterized by high sensitivity in the detection of malignant lesions in the case of lesions with mass and non-mass morphology. The high NPV for recombinant images suggests that in the case of these lesions, the lack of enhancement supports the benign nature of the lesion and may lead to a downgrade of the BI-RADS category.

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

RATIONALE AND OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Abbreviated Molecular Breast Imaging: Feasibility and Future Considerations

OBJECTIVE

Molecular breast imaging (MBI) is a supplemental screening modality consistently demonstrating incremental cancer detection over mammography alone; however, its lengthy duration may limit widespread utilization. The study purpose was to assess feasibility of an abbreviated MBI protocol, providing readers with mediolateral oblique (MLO) projections only and assessing performance in lesion detection and localization.

METHODS

Retrospective IRB-exempt blinded reader study administered to 5 fellowship-trained breast imaging radiologists. Independent reads performed for 124 screening MBI cases, half abnormal and half negative/normal. Readers determined whether an abnormality was present, side of abnormality, and location of abnormality (medial/lateral). Abnormal cases had confirmatory biopsy or surgical pathology; normal cases had imaging follow-up ensuring true negative results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess performance. A false negative result indicated that a reader failed to detect abnormal uptake; a false positive result indicated a reader incorrectly called an abnormality for a negative case. Tests for association included chi-square, Fisher-exact, and analysis of variance.

RESULTS

Mean reader performance for detecting abnormal uptake: sensitivity 96.8%, specificity 98.7%, PPV 98.8%, and NPV 96.9%. Accuracy in localizing lesions to the medial or lateral breast was 100%. There were no associations in reader performance with reader experience, reader technique, lesion morphology, or lesion pathology. Median lesion size was 1.0 cm (range: 0.4-8.0 cm). All readers correctly identified 97.7% (42/43) of lesions with malignant or elevated risk pathology.

CONCLUSION

An abbreviated MBI protocol (MLO images only) maintained high accuracy in lesion detection and localization.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Cancer Conspicuity on Low-energy Images of Contrast-enhanced Mammography Compared With 2D Mammography

OBJECTIVE

Low-energy (LE) images of contrast-enhanced mammography (CEM) have been shown to be noninferior to digital mammography. However, our experience is that LE images are superior to 2D mammography. Our purpose was to compare cancer appearance on LE to 2D images.

METHODS

In this IRB-approved retrospective study, seven breast radiologists evaluated 40 biopsy-proven cancer cases on craniocaudal (CC) and mediolateral oblique (MLO) LE images and recent 2D images for cancer visibility, confidence in margins, and conspicuity of findings using a Likert scale. Objective measurements were performed using contrast-to-noise ratio (CNR) estimated from regions of interest placed on tumor and background parenchyma. Reader agreement was evaluated using Fleiss kappa. Per-reader comparisons were performed using Wilcoxon test and overall comparisons used three-way analysis of variance.

RESULTS

Low-energy images showed improved performance for visibility (CC LE 4.0 vs 2D 3.5, P < 0.001 and MLO LE 3.7 vs 2D 3.5, P = 0.01), confidence in margins (CC LE 3.2 vs 2D 2.8, P < 0.001 and MLO LE 3.1 vs 2D 2.9, P < 0.008), and conspicuity compared to tissue density compared to 2D mammography (CC LE 3.6 vs 2D 3.2, P < 0.001 and MLO LE 3.5 vs 2D 3.2, P < 0.001). The average CNR was significantly higher for LE than for digital mammography (CC 2.1 vs 3.2, P < 0.001 and MLO 2.1 vs 3.4, P < 0.001).

CONCLUSION

Our results suggest that cancers may be better visualized on the LE CEM images compared with the 2D digital mammogram.

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.

The Usefulness of Spectral Mammography in Surgical Planning of Breast Cancer Treatment-Analysis of 999 Patients with Primary Operable Breast Cancer

Contrast-enhanced spectral mammography (CESM) is a promising, digital breast imaging method for planning surgeries. The study aimed at comparing digital mammography (MG) with CESM as predictive factors in visualizing multifocal-multicentric cancers (MFMCC) before determining the surgery extent. We analyzed 999 patients after breast cancer surgery to compare MG and CESM in terms of detecting MFMCC. Moreover, these procedures were assessed for their conformity with postoperative histopathology (HP), calculating their sensitivity and specificity. The question was which histopathological types of breast cancer were more frequently characterized by multifocality–multicentrality in comparable techniques as regards the general number of HP-identified cancers. The analysis involved the frequency of post-CESM changes in the extent of planned surgeries. In the present study, MG revealed 48 (4.80%) while CESM 170 (17.02%) MFMCC lesions, subsequently confirmed in HP. MG had MFMCC detecting sensitivity of 38.51%, specificity 99.01%, PPV (positive predictive value) 85.71%, and NPV (negative predictive value) 84.52%. The respective values for CESM were 87.63%, 94.90%, 80.57% and 96.95%. Moreover, no statistically significant differences were found between lobular and NST cancers (27.78% vs. 21.24%) regarding MFMCC. A treatment change was required by 20.00% of the patients from breast-conserving to mastectomy, upon visualizing MFMCC in CESM. In conclusion, mammography offers insufficient diagnostic sensitivity for detecting additional cancer foci. The high diagnostic sensitivity of CESM effectively assesses breast cancer multifocality/multicentrality and significantly changes the extent of planned surgeries. The multifocality/multicentrality concerned carcinoma, lobular and invasive carcinoma of no special type (NST) cancers with similar incidence rates, which requires further confirmation.

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.

[Artificial intelligence in breast imaging : Areas of application from a clinical perspective]

Klinisches/methodisches Problem

Bei der Mammadiagnostik gilt es, klinische sowie multimodal bildgebende Informationen mit perkutanen und operativen Eingriffen zu koordinieren. Aus dieser Komplexität entsteht eine Reihe von Problemen: übersehene Karzinome, Überdiagnose, falsch-positive Befunde, unnötige weiterführende Bildgebung, Biopsien und Operationen.

Radiologische Standardverfahren

Folgende Untersuchungsverfahren werden in der Mammadiagnostik eingesetzt: Röntgenmammographie, Tomosynthese, kontrastangehobene Mammographie, (multiparametrischer) Ultraschall, Magnetresonanztomographie, Computertomographie, nuklearmedizinische Verfahren sowie deren Hybridvarianten.

Methodische Innovationen

Künstliche Intelligenz (KI) verspricht Abhilfe bei praktisch allen Problemen der Mammadiagnostik. Potenziell lassen sich Fehlbefunde vermeiden, bildgebende Verfahren effizienter einsetzen und möglicherweise auch biologische Phänotypen von Mammakarzinomen definieren.

Leistungsfähigkeit

Auf KI basierende Software wird für zahlreiche Anwendungen entwickelt. Am weitesten fortgeschritten sind Systeme für das Screening mittels Mammographie. Probleme sind monozentrische sowie kurzfristig am finanziellen Erfolg orientierte Ansätze.

Bewertung

Künstliche Intelligenz (KI) verspricht eine Verbesserung der Mammadiagnostik. Durch die Vereinfachung von Abläufen, die Reduktion monotoner und ergebnisloser Tätigkeiten und den Hinweis auf mögliche Fehler ist eine Beschleunigung von dann weitgehend fehlerfreien Abläufen denkbar.

Empfehlung für die Praxis

In diesem Beitrag werden die Anforderungen der Mammadiagnostik und mögliche Einsatzgebiete der der KI beleuchtet. Je nach Definition gibt es bereits praktisch anwendbare Softwaretools für die Mammadiagnostik. Globale Lösungen stehen allerdings noch aus.