Low-Risk Women with Suspicious Microcalcifications in Mammography-Can an Additional Breast MRI Reduce the Biopsy Rate?

BACKGROUND

In the German Mammography Screening Program, 62% of ductal carcinoma in situ (DCIS) and 38% of invasive breast cancers are associated with microcalcifications (MCs). Vacuum-assisted stereotactic breast biopsies are necessary to distinguish precancerous lesions from benign calcifications because mammographic discrimination is not possible. The aim of this study was to investigate if breast magnetic resonance imaging (MRM) could assist the evaluation of MCs and thus help reduce biopsy rates.

METHODS

In this IRB-approved study, 58 women (mean age 58 +/- 24 years) with 59 suspicious MC clusters in the MG were eligible for this prospective single-center trial. Additional breast magnetic resonance imaging (MRI) was conducted before biopsy.

RESULTS

The breast MRI showed a sensitivity of 86%, a specificity of 84%, a positive predictive value (PPV) of 75% and a negative predictive value (NPV) of 91% for the differentiation between benign and malignant in these 59 MCs found with MG. Breast MRI in addition to MG could increase the PPV from 36% to 75% compared to MG alone. The MRI examination led to nine additional suspicious classified lesions in the study cohort. A total of 55% (5/9) of them turned out to be malignant. A total of 32 of 59 (54 %) women with suspicious MCs and benign histology were classified as non-suspicious by MRI.

CONCLUSION

An additionally performed breast MRI could have increased the diagnostic reliability in the assessment of MCs. Further, in our small cohort, a considerable number of malignant lesions without mammographically visible MCs were revealed.

Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images

Background Reducing the amount of contrast agent needed for contrast-enhanced breast MRI is desirable. Purpose To investigate if generative adversarial networks (GANs) can recover contrast-enhanced breast MRI scans from unenhanced images and virtual low-contrast-enhanced images. Materials and Methods In this retrospective study of breast MRI performed from January 2010 to December 2019, simulated low-contrast images were produced by adding virtual noise to the existing contrast-enhanced images. GANs were then trained to recover the contrast-enhanced images from the simulated low-contrast images (approach A) or from the unenhanced T1- and T2-weighted images (approach B). Two experienced radiologists were tasked with distinguishing between real and synthesized contrast-enhanced images using both approaches. Image appearance and conspicuity of enhancing lesions on the real versus synthesized contrast-enhanced images were independently compared and rated on a five-point Likert scale. P values were calculated by using bootstrapping. Results A total of 9751 breast MRI examinations from 5086 patients (mean age, 56 years ± 10 [SD]) were included. Readers who were blinded to the nature of the images could not distinguish real from synthetic contrast-enhanced images (average accuracy of differentiation: approach A, 52 of 100; approach B, 61 of 100). The test set included images with and without enhancing lesions (29 enhancing masses and 21 nonmass enhancement; 50 total). When readers who were not blinded compared the appearance of the real versus synthetic contrast-enhanced images side by side, approach A image ratings were significantly higher than those of approach B (mean rating, 4.6 ± 0.1 vs 3.0 ± 0.2; P < .001), with the noninferiority margin met by synthetic images from approach A (P < .001) but not B (P > .99). Conclusion Generative adversarial networks may be useful to enable breast MRI with reduced contrast agent dose. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bahl in this issue.

Factors Associated With Breast Cancer Screening Behaviors Among Women With Dense Breasts

OBJECTIVE

We sought to identify patient factors associated with patient-reported screening behaviors in women with dense breasts.

METHODS

An IRB-approved survey study of women with dense breasts presenting for annual screening mammography at an outpatient imaging center was previously conducted from March 2017 to February 2018. The survey included questions regarding mammographic screening frequency and recent participation in supplemental screening. These survey data were combined post hoc with clinical and demographic data and socioeconomic data imputed from census data. Logistic regression was used to identify patient factors associated with reported screening behaviors.

RESULTS

Surveys were completed by 508 women (median age, 59.0 years; range, 31.0-86.0 years) with dense breasts. Multivariable analysis demonstrated an independent association of undergoing mammographic screening annually with a history of discussing breast density with a doctor (adjusted odds ratio [AOR], 2.60; P = 0.019). Undergoing supplemental screening in the previous three years was independently associated with younger age (AOR, 1.59; P = 0.004), strong family history of breast cancer (AOR, 3.84; P = 0.027), higher perceived personal risk for breast cancer (AOR, 3.47; P = 0.004), and increased concern about radiation associated with screening examinations (AOR, 3.31; P = 0.006).

CONCLUSION

Women with dense breasts who had discussed breast density with a doctor were more likely to report undergoing annual screening mammography, while younger women and women with a strong family history of breast cancer, higher perceived personal risk for breast cancer, or greater concern about radiation were more likely to report recently undergoing supplemental screening.

Abbreviated MRI for Comprehensive Regional Lymph Node Staging during Pre-Operative Breast MRI

Background: The detection of regional lymph node metastases (LNM), in particular significant LNM (≥N2), is important to guide treatment decisions in women with breast cancer. The purpose of this study was to determine whether a coronal pulse sequence as part of pre-operative breast MRI is useful to identify women without significant LNM. Material: Retrospective study between January 2017 and December 2019 on 414 consecutive women with breast cancer who underwent pre-operative breast MRI on a 1.5 T system. For lymph node (LN) staging, a coronal pre-contrast non-fat-suppressed T1-weighted TSE sequence was acquired with the system’s built-in body coil, covering the chest wall; acquisition time 3:12 min. Two radiologists rated the likelihood of LNM on a 3-point scale (absent/possible/present). Validation was obtained by histology from sentinel LN biopsy, axillary LN dissection, and/or PET/CT. Results: 368/414 women were staged to have no or non-significant LNM (pN0 in 282/414, pN1 in 86/414), and significant LNM (≥pN2) in 46/414. For identification of women with significant LNM, MRI was true-positive in 42/46, false-negative in 4/46, true-negative in 327/368, and false-positive in 41/83, the latter mostly caused by women with N1-disease (38/41), yielding an NPV and PPV for significant LNM of 98.8% [95%-CI: 97.0–100%] and 50.6% [43.1–58.1%], respectively. Conclusions: A 3 min coronal T1-weighted pulse sequence covering the chest wall as part of pre-operative breast MRI is useful to rule out significant LNM with high NPV. Where MRI staging is positive for significant LNM, additional work-up is indicated to improve the distinction of N1 and N2 disease.

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

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

Challenges and Changes of the Breast Cancer Screening Paradigm

Since four decades mammography is used for early breast cancer detection in asymptomatic women and still remains the gold standard imaging modality. However, population screening programs can be personalized and women can be divided into different groups based on risk factors and personal preferences. The availability of new and evolving imaging modalities, for example, digital breast tomosynthesis, dynamic-contrast-enhanced magnetic resonance imaging (MRI), abbreviated MRI protocols, diffusion-weighted MRI, and contrast-enhanced mammography leads to new challenges and perspectives regarding the feasibility and potential harms of breast cancer screening. The aim of this review is to discuss the current guidelines for different risk groups, to analyze the recent published studies about the diagnostic performance of the imaging modalities and to discuss new developments and future perspectives. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 6.

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

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

Breast MRI: an illustration of benign findings

Despite its unparalleled sensitivity for aggressive breast cancer, breast MRI continually excites criticism for a specificity that lags behind that of modern mammographic techniques. Radiologists reporting breast MRI need to recognise the range of benign appearances on breast MRI to avoid unnecessary biopsy. This review summarises the reported diagnostic accuracy of breast MRI with particular attention to the technique's specificity, provides a referenced reporting strategy and discusses factors that compromise diagnostic confidence. We then present a pictorial review of benign findings on breast MRI. Enhancing radiological skills to discriminate malignant from benign findings will minimise false positive biopsies, enabling optimal use of multiparametric breast MRI for the benefit of screening clients and breast cancer patients.

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

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

Contrast-enhanced mammography in breast cancer screening

Contrast-enhanced mammography (CEM) is a promising vascular-based breast imaging technique with high diagnostic performance in detecting breast cancer. Dual-energy acquisition using low and high energy x-ray spectra following intravenous iodinated contrast injection provides both anatomic and functional information in the same examination. The low-energy images are equivalent to standard digital mammography and the post-processed recombined images depict enhancement analogous to contrast-enhanced breast magnetic resonance imaging (MRI). Thus, CEM has the potential to detect abnormal morphologic features as well as neovascularity associated with breast cancer. Since its emergence in 2011, CEM has consistently demonstrated superior performance compared with standard mammography and mammography plus ultrasound, particularly in women with dense breasts, with high sensitivity approaching that of MRI, supporting its use as a cost-effective diagnostic and screening tool. CEM has been primarily used in the diagnostic setting to evaluate patients with screening abnormalities or with symptomatic breasts, to perform preoperative staging of newly diagnosed breast cancer, and to evaluate response to neoadjuvant chemotherapy. More recently, CEM has been performed to screen women who have an intermediate to high lifetime risk of developing breast cancer. In addition to its high diagnostic performance, CEM is less expensive and more accessible than MRI and potentially better tolerated by patients. Minor drawbacks to CEM include a slightly increased radiation dose compared with standard mammography and a low risk for contrast allergy reaction. The aim of this study is to review the background, current literature, and future applications of CEM in breast cancer screening.

Limited value of multiparametric MRI with dynamic contrast-enhanced and diffusion-weighted imaging in non-mass enhancing breast tumors

PURPOSE

To investigate the diagnostic value of multiparametric MRI (mpMRI) including dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in non-mass enhancing breast tumors.

METHOD

Patients who underwent mpMRI, who were diagnosed with a suspicious non-mass enhancement (NME) on DCE-MRI (BI-RADS 4/5), and who subsequently underwent image-guided biopsy were retrospectively included. Two radiologists independently evaluated all NMEs, on both DCE-MR images and high-b-value DW images. Different mpMRI reading approaches were evaluated: 1) with a fixed apparent diffusion coefficient (ADC) threshold (<1.3 malignant, ≥1.3 benign) based on the recommendation by the European Society of Breast Imaging (EUSOBI); 2) with a fixed ADC threshold (<1.5 malignant, ≥1.5 benign) based on recently published trial data; 3) with an ADC threshold adapted to the assigned BI-RADS classification using a previously published reading method; and 4) with individually determined best thresholds for each reader.

RESULTS

The final study sample consisted of 66 lesions in 66 patients. DCE-MRI alone had the highest sensitivity for breast cancer detection (94.8-100 %), outperforming all mpMRI reading approaches (R1 74.4-87.1 %, R2 71.7-94.8 %) and DWI alone (R1 74.4 %, R2 79.4 %). The adapted approach achieved the best specificity for both readers (85.1 %), resulting in the best diagnostic accuracy for R1 (86.5 %) but a moderate diagnostic accuracy for R2 (77.2 %).

CONCLUSION

mpMRI has limited added diagnostic value to DCE-MRI in the assessment of NME.

MRI Breast: Current Imaging Trends, Clinical Applications, and Future Research Directions

Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique in diagnosing breast cancer and is essential in improving cancer detection, lesion characterization, and determining therapy response. In addition to the dynamic contrast-enhanced (DCE) technique, functional techniques such as magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) further characterize and differentiate benign and malignant lesions thus, improving diagnostic accuracy. There is now an increasing clinical usage of MRI breast, including screening in high risk and supplementary screening tools in average-risk patients. MRI is becoming imperative in assisting breast surgeons in planning breast-conserving surgery for preoperative local staging and evaluation of neoadjuvant chemotherapy response. Other clinical applications for MRI breast include occult breast cancer detection, investigation of nipple discharge, and breast implant assessment. There is now an abundance of research publications on MRI Breast with several areas that still remain to be explored. This review gives a comprehensive overview of the clinical trends of MRI breast with emphasis on imaging features and interpretation using conventional and advanced techniques. In addition, future research areas in MRI breast include developing techniques to make MRI more accessible and costeffective for screening. The abbreviated MRI breast procedure and an area of focused research in the enhancement of radiologists' work with artificial intelligence have high impact for the future in MRI Breast.

Comparison of Abbreviated Breast MRI vs Digital Breast Tomosynthesis for Breast Cancer Detection among Women with a History of Breast Cancer

RATIONALE AND OBJECTIVES

To compare the diagnostic performance of abbreviated breast MRI (AB-MRI) and digital breast tomosynthesis (DBT) in women with a personal history (PH) of breast cancer as a postoperative screening tool.

MATERIALS AND METHODS

A total of 471 patients who completed both DBT and AB-MRI examinations were included in this study (median age, 54.5 years). The detected cancer characteristics were analyzed. The cancer detection rate (CDR), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) were calculated by receiver operating characteristic (ROC) curve analysis.

RESULTS

Eleven malignancies were diagnosed, and most of the detected cancers were stage I (7 of 11, 63.6%). Eight were invasive ductal carcinomas (IDC), and 3 were ductal carcinoma in situ (DCIS). Of the 11 recurrences, 6 malignancies were detected by DBT, and 11 were detected by AB-MRI. AB-MRI detected all 8 IDC and 3 DCIS lesions, and DBT detected 6 of 8 IDC lesions. The CDRs for DBT and AB-MRI screenings were 12.7 and 23.4 per 1,000 women, respectively. The sensitivity, specificity, PPV, NPV, and accuracy of DBT versus AB-MRI were 54.6% versus 100%, 97.6% versus 96.5%, 35.3% versus 40.7%, 98.9% versus 100%, and 96.6% versus 96.6%, respectively. AB-MRI showed a higher AUC value (0.983) than DBT (0.761) (p = 0.0049).

CONCLUSION

AB-MRI showed an improved CDR, especially for invasive cancer. The diagnostic performance of AB-MRI was superior to that of DBT with high sensitivity and PPV without sacrificing specificity in women with a PH of breast cancer.

Improving breast cancer diagnostics with deep learning for MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast cancer diagnosis and personalize management of patients undergoing DCE-MRI. On the internal test set (n = 3936 exams), our system achieved an area under the receiver operating characteristic curve (AUROC) of 0.92 (95% CI: 0.92 to 0.93). In a retrospective reader study, there was no statistically significant difference (P = 0.19) between five board-certified breast radiologists and the DL system (mean ΔAUROC, +0.04 in favor of the DL system). Radiologists' performance improved when their predictions were averaged with DL's predictions [mean ΔAUPRC (area under the precision-recall curve), +0.07]. We demonstrated the generalizability of the DL system using multiple datasets from Poland and the United States. An additional reader study on a Polish dataset showed that the DL system was as robust to distribution shift as radiologists. In subgroup analysis, we observed consistent results across different cancer subtypes and patient demographics. Using decision curve analysis, we showed that the DL system can reduce unnecessary biopsies in the range of clinically relevant risk thresholds. This would lead to avoiding biopsies yielding benign results in up to 20% of all patients with BI-RADS category 4 lesions. Last, we performed an error analysis, investigating situations where DL predictions were mostly incorrect. This exploratory work creates a foundation for deployment and prospective analysis of DL-based models for breast MRI.

Addressing Misinformation About the Canadian Breast Screening Guidelines

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

BC-miR: Monitoring Breast Cancer-Related miRNA Profile in Blood Sera—A Prosperous Approach for Tumor Detection

Breast cancer is the most frequent cancer with a high fatality rate amongst women worldwide. Diagnosing at an early stage is challenging, and due to the limitations of the currently used techniques, including mammography and imaging diagnostics, it still remains unascertained. Serum biomarkers can be a solution for this as they can be isolated in a less painful, more cost-effective, and minimally invasive manner. In this study, we shed light on the relevant role of multiple microRNAs (miRNAs) as potential biomarkers in breast cancer diagnosis. We monitored the expressional changes of 15 pre-selected miRNAs in a large cohort, including 65 patients with breast cancer and 42 healthy individuals. We performed thorough statistical analyses on the cohort sample set and determined the diagnostic accuracy of individual and multiple miRNAs. Our study reveals a potential improvement in diagnostics by implicating the monitoring of miR-15a+miR-16+miR-221 expression in breast cancer management.

Evaluating the effectiveness of abbreviated breast MRI (abMRI) interpretation training for mammogram readers: a multi-centre study assessing diagnostic performance, using an enriched dataset

BACKGROUND

Abbreviated breast MRI (abMRI) is being introduced in breast screening trials and clinical practice, particularly for women with dense breasts. Upscaling abMRI provision requires the workforce of mammogram readers to learn to effectively interpret abMRI. The purpose of this study was to examine the diagnostic accuracy of mammogram readers to interpret abMRI after a single day of standardised small-group training and to compare diagnostic performance of mammogram readers experienced in full-protocol breast MRI (fpMRI) interpretation (Group 1) with that of those without fpMRI interpretation experience (Group 2).

METHODS

Mammogram readers were recruited from six NHS Breast Screening Programme sites. Small-group hands-on workstation training was provided, with subsequent prospective, independent, blinded interpretation of an enriched dataset with known outcome. A simplified form of abMRI (first post-contrast subtracted images (FAST MRI), displayed as maximum-intensity projection (MIP) and subtracted slice stack) was used. Per-breast and per-lesion diagnostic accuracy analysis was undertaken, with comparison across groups, and double-reading simulation of a consecutive screening subset.

RESULTS

37 readers (Group 1: 17, Group 2: 20) completed the reading task of 125 scans (250 breasts) (total = 9250 reads). Overall sensitivity was 86% (95% confidence interval (CI) 84-87%; 1776/2072) and specificity 86% (95%CI 85-86%; 6140/7178). Group 1 showed significantly higher sensitivity (843/952; 89%; 95%CI 86-91%) and higher specificity (2957/3298; 90%; 95%CI 89-91%) than Group 2 (sensitivity = 83%; 95%CI 81-85% (933/1120) p < 0.0001; specificity = 82%; 95%CI 81-83% (3183/3880) p < 0.0001). Inter-reader agreement was higher for Group 1 (kappa = 0.73; 95%CI 0.68-0.79) than for Group 2 (kappa = 0.51; 95%CI 0.45-0.56). Specificity improved for Group 2, from the first 55 cases (81%) to the remaining 70 (83%) (p = 0.02) but not for Group 1 (90-89% p = 0.44), whereas sensitivity remained consistent for both Group 1 (88-89%) and Group 2 (83-84%).

CONCLUSIONS

Single-day abMRI interpretation training for mammogram readers achieved an overall diagnostic performance within benchmarks published for fpMRI but was insufficient for diagnostic accuracy of mammogram readers new to breast MRI to match that of experienced fpMRI readers. Novice MRI reader performance improved during the reading task, suggesting that additional training could further narrow this performance gap.

Abbreviated Screening MRI for Women with a History of Breast Cancer: Comparison with Full-Protocol Breast MRI

Background Few studies have compared abbreviated breast MRI with full-protocol MRI in women with a personal history of breast cancer (PHBC), and they have not adjusted for confounding variables. Purpose To compare abbreviated breast MRI with full-protocol MRI in women with PHBC by using propensity score matching to adjust for confounding variables. Materials and Methods In this single-center retrospective study, women with PHBC who underwent full-protocol MRI (January 2008-August 2017) or abbreviated MRI (September 2017-April 2019) were identified. With use of a propensity score-matched cohort, screening performances were compared between the two MRI groups with the McNemar test or a propensity score-adjusted generalized estimating equation. The coprimary analyses were sensitivity and specificity. The secondary analyses were the cancer detection rate, interval cancer rate, positive predictive value for biopsies performed (PPV3), and Breast Imaging Reporting and Data System (BI-RADS) category 3 short-term follow-up rate. Results There were 726 women allocated to each MRI group (mean age ± SD, 50 years ± 8 for both groups). Abbreviated MRI and full-protocol MRI showed comparable sensitivity (15 of 15 cancers [100%; 95% CI: 78, 100] vs nine of 13 cancers [69%; 95% CI: 39, 91], respectively; P = .17). Abbreviated MRI showed higher specificity than full-protocol MRI (660 of 711 examinations [93%; 95% CI: 91, 95] vs 612 of 713 examinations [86%; 95% CI: 83, 88], respectively; P < .001). The cancer detection rate (21 vs 12 per 1000 examinations), interval cancer rate (0 vs five per 1000 examinations), and PPV3 (61% [14 of 23 examinations] vs 41% [nine of 22 examinations]) were comparable (all P < .05). The BI-RADS category 3 short-term follow-up rate of abbreviated MRI was less than half that of full-protocol MRI (5% [36 of 726 examinations] vs 12% [84 of 726 examinations], respectively; P < .001). Ninety-three percent (14 of 15) of cancers detected at abbreviated MRI were node-negative T1-invasive cancers (n = 6) or ductal carcinoma in situ (n = 8). Conclusion Abbreviated breast MRI showed comparable sensitivity and superior specificity to full-protocol MRI in breast cancer detection in women with a personal history of breast cancer. © RSNA, 2022 Online supplemental material is available for this article.

Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time

OBJECTIVES

To investigate the feasibility of automatically identifying normal scans in ultrafast breast MRI with artificial intelligence (AI) to increase efficiency and reduce workload.

METHODS

In this retrospective analysis, 837 breast MRI examinations performed on 438 women from April 2016 to October 2019 were included. The left and right breasts in each examination were labelled normal (without suspicious lesions) or abnormal (with suspicious lesions) based on final interpretation. Maximum intensity projection (MIP) images of each breast were then used to train a deep learning model. A high sensitivity threshold was calculated based on the detection trade - off (DET) curve on the validation set. The performance of the model was evaluated by receiver operating characteristic analysis of the independent test set. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with the high sensitivity threshold were calculated.

RESULTS

The independent test set consisted of 178 examinations of 149 patients (mean age, 44 years ± 14 [standard deviation]). The trained model achieved an AUC of 0.81 (95% CI: 0.75-0.88) on the independent test set. Applying a threshold of 0.25 yielded a sensitivity of 98% (95% CI: 90%; 100%), an NPV of 98% (95% CI: 89%; 100%), a workload reduction of 15.7%, and a scan time reduction of 16.6%.

CONCLUSION

This deep learning model has a high potential to help identify normal scans in ultrafast breast MRI and thereby reduce radiologists' workload and scan time.

KEY POINTS

• Deep learning in TWIST may eliminate the necessity of additional sequences for identifying normal breasts during MRI screening. • Workload and scanning time reductions of 15.7% and 16.6%, respectively, could be achieved with the cost of 1 (1 of 55) false negative prediction.

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

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

Sensitivity of Contrast-Enhanced Breast MRI vs X-ray Mammography Based on Cancer Histology, Tumor Grading, Receptor Status, and Molecular Subtype: A Supplemental Analysis of 2 Large Phase III Studies

Background:

The impact of certain tumor parameters on the sensitivity of imaging tools is unknown. The purpose was to study the impact of breast cancer histology, tumor grading, single receptor status, and molecular subtype on the sensitivity of contrast-enhanced breast magnetic resonance imaging (CE-BMRI) vs X-ray mammography (XRM) to detect breast cancer.

Materials and Methods:

We ran a supplemental analysis of 2 global Phase III studies which recruited patients with histologically proven breast cancers. The sensitivity of CE-BMRI vs XRM to detect cancer lesions with different histologies, tumor grading, single receptor status, and molecular subtype was compared. Six blinded readers for each study evaluated the images. Results were summarized as the “Mean Reader.” For each reader, sensitivity was defined as the proportion of detected lesions vs the total number of lesions identified by the standard of reference. Two-sided 95% confidence intervals were calculated for within-group proportions, and for the difference between CE-BMRI and XRM, using a normal approximation to the binomial distribution.

Results:

In 778 patients, 1273 cancer lesions were detected. A total of 435 patients had 1 lesion, 254 had 2 lesions, and 77 had 3 or more lesions. The sensitivity of CE-BMRI was significantly higher compared with XRM irrespective of the histology. The largest difference was seen for invasive lobular carcinoma (22.3%) and ductal carcinoma in situ (19%). Across all 3 tumor grades, the sensitivity advantage of CE-BMRI over XRM ranged from 15.7% to 18.5%. Contrast-enhanced breast magnetic resonance imaging showed higher sensitivity compared with XRM irrespective of single receptor expressions (15.3%-19.4%). The sensitivities for both imaging methods were numerically higher for the more aggressive ER– (estrogen receptor), PR– (progesterone receptor), and HER2+ (human epidermal growth factor receptor 2) tumors. Irrespective of molecular subtype, sensitivity of CE-BMRI was 14.8% to 18.9% higher compared with XRM.

Conclusions:

Contrast-enhanced breast magnetic resonance imaging showed significantly higher sensitivity compared with XRM independent of tumor histology, tumor grading, single receptor status, and molecular subtype.

Trial Registration: ClinicalTrials.gov: NCT01067976 and NCT01104584.

Breast MRI during pregnancy and lactation: clinical challenges and technical advances

The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.

Dynamic contrast-enhanced breast magnetic resonance imaging findings that affect the magnetic resonance-directed ultrasound correlation of non-mass enhancement lesions: a single-center retrospective study

OBJECTIVE

Our single-center retrospective study aimed to evaluate the relationship between magnetic resonance (MR)-directed ultrasound (MDUS) detectability and MRI findings of non-mass enhancement (NME) lesions, regarding the morphologic and enhancement features, the distance from the skin and nipple, and the presence of concomitant landmarks.

METHODS

A total of 350 MRI-detected NME lesions that were determined between January 2015 and May 2019 and subsequently underwent MDUS were analyzed. The MRI findings, biopsy results, and follow-up outcomes of lesions were recorded. The correlation between the MRI findings of the lesions and MDUS detectability was analyzed.

RESULTS

114 (32.6%) of the 350 lesions had a counterpart in the MDUS. Respectively, 66 (37.9%), 38 (43.2%) and 59 (38.3%) of the lesions detected in MDUS were larger than 20 mm in size, with a distance of less than 20 mm to the nipple and 15 mm to the skin. The lesion size and lesion distance to the nipple and skin were significantly associated with a ultrasound correlate (p < 0.05). The MDUS detection rate was significantly higher in NME lesions with MR findings including diffuse distribution (p < 0.001), clustered-ring enhancement pattern (p < 0.001), washout kinetic curve (p = 0.006), and MR-BIRADS category 5 (p < 0.001). Multivariate logistic regression showed that only the clustered-ring enhancement pattern was significantly associated with an MDUS correlation (p < 0.001).

CONCLUSION

Statistically significant correlations were found between the size, distance to the nipple and skin, distribution pattern, enhancement pattern and kinetic curve of the NME lesions on MRI and ultrasound detectability.

ADVANCES IN KNOWLEDGE

We found that clustered-ring enhancement patterns were significantly more frequent in MR-directed ultrasound detectable lesions.

Background parenchymal enhancement in contrast-enhanced MR imaging suggests systemic effects of intrauterine contraceptive devices

OBJECTIVES

Levonorgestrel-releasing intrauterine contraceptive devices (LNG-IUDs) are designed to exhibit only local hormonal effects. There is an ongoing debate on whether LNG-IUDs can have side effects similar to systemic hormonal medication. Benign background parenchymal enhancement (BPE) in dynamic contrast-enhanced (DCE) MRI has been established as a sensitive marker of hormonal stimulation of the breast. We investigated the association between LNG-IUD use and BPE in breast MRI to further explore possible systemic effects of LNG-IUDs.

METHODS

Our hospital database was searched to identify premenopausal women without personal history of breast cancer, oophorectomy, and hormone replacement or antihormone therapy, who had undergone standardized DCE breast MRI at least twice, once with and without an LNG-IUD in place. To avoid confounding aging-related effects on BPE, half of included women had their first MRI without, the other half with, LNG-IUD in place. Degree of BPE was analyzed according to the ACR categories. Wilcoxon-matched-pairs signed-rank test was used to compare the distribution of ACR categories with vs. without LNG-IUD.

RESULTS

Forty-eight women (mean age, 46 years) were included. In 24/48 women (50% [95% CI: 35.9-64.1%]), ACR categories did not change with vs. without LNG-IUDs. In 23/48 women (48% [33.9-62.1%]), the ACR category was higher with vs. without LNG-IUDs; in 1/48 (2% [0-6%]), the ACR category was lower with vs. without LNG-IUDs. The change of ACR category depending on the presence or absence of an LNG-IUD proved highly significant (p < 0.001).

CONCLUSION

The use of an LNG-IUD can be associated with increased BPE in breast MRI, providing further evidence that LNG-IUDs do have systemic effects.

KEY POINTS

• The use of levonorgestrel-releasing intrauterine contraceptive devices is associated with increased background parenchymal enhancement in breast MRI. • This suggests that hormonal effects of these devices are not only confined to the uterine cavity, but may be systemic. • Potential systemic effects of levonorgestrel-releasing intrauterine contraceptive devices should therefore be considered.

Synthesizing the First Phase of Dynamic Sequences of Breast MRI for Enhanced Lesion Identification

Objective

To develop a deep learning model for synthesizing the first phases of dynamic (FP-Dyn) sequences to supplement the lack of information in unenhanced breast MRI examinations.

Methods

In total, 97 patients with breast MRI images were collected as the training set (n = 45), the validation set (n = 31), and the test set (n = 21), respectively. An enhance border lifelike synthesize (EDLS) model was developed in the training set and used to synthesize the FP-Dyn images from the T1WI images in the validation set. The peak signal-to-noise ratio (PSNR), structural similarity (SSIM), mean square error (MSE) and mean absolute error (MAE) of the synthesized images were measured. Moreover, three radiologists subjectively assessed image quality, respectively. The diagnostic value of the synthesized FP-Dyn sequences was further evaluated in the test set.

Results

The image synthesis performance in the EDLS model was superior to that in conventional models from the results of PSNR, SSIM, MSE, and MAE. Subjective results displayed a remarkable visual consistency between the synthesized and original FP-Dyn images. Moreover, by using a combination of synthesized FP-Dyn sequence and an unenhanced protocol, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MRI were 100%, 72.73%, 76.92%, and 100%, respectively, which had a similar diagnostic value to full MRI protocols.

Conclusions

The EDLS model could synthesize the realistic FP-Dyn sequence to supplement the lack of enhanced images. Compared with full MRI examinations, it thus provides a new approach for reducing examination time and cost, and avoids the use of contrast agents without influencing diagnostic accuracy.

Cost-effectiveness of abbreviated-protocol MRI screening for women with mammographically dense breasts in a national breast cancer screening program

Introduction

Magnetic resonance imaging (MRI) has shown the potential to improve the screening effectiveness among women with dense breasts. The introduction of fast abbreviated protocols (AP) makes MRI more feasible to be used in a general population. We aimed to investigate the cost-effectiveness of AP-MRI in women with dense breasts (heterogeneously/extremely dense) in a population-based screening program.

Methods

A previously validated model (SiMRiSc) was applied, with parameters updated for women with dense breasts. Breast density was assumed to decrease with increased age. The base scenarios included six biennial AP-MRI strategies, with biennial mammography from age 50–74 as reference. Fourteen alternative scenarios were performed by varying screening interval (triennial and quadrennial) and by applying a combined strategy of mammography and AP-MRI. A 3% discount rate for both costs and life years gained (LYG) was applied. Model robustness was evaluated using univariate and probabilistic sensitivity analyses.

Results

The six biennial AP-MRI strategies ranged from 132 to 562 LYG per 10,000 women, where more frequent application of AP-MRI was related to higher LYG. The optimal strategy was biennial AP-MRI screening from age 50–65 for only women with extremely dense breasts, producing an incremental cost-effectiveness ratio of € 18,201/LYG. At a threshold of € 20,000/LYG, the probability that the optimal strategy was cost-effective was 79%.

Conclusion

Population-based biennial breast cancer screening with AP-MRI from age 50–65 for women with extremely dense breasts might be a cost-effective alternative to mammography, but is not an option for women with heterogeneously dense breasts.

•

AP-MRI can be cost-effective for screening women with extremely dense breast.

•

The more frequent the use of AP-MRI, the more life years will be gained.

•

Biennial AP-MRI for women with extremely dense breast up to age 65 is optimal.

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.

MRI-Based Machine Learning in Differentiation Between Benign and Malignant Breast Lesions

Background

Differential diagnosis between benign and malignant breast lesions is of crucial importance relating to follow-up treatment. Recent development in texture analysis and machine learning may lead to a new solution to this problem.

Method

This current study enrolled a total number of 265 patients (benign breast lesions:malignant breast lesions = 71:194) diagnosed in our hospital and received magnetic resonance imaging between January 2014 and August 2017. Patients were randomly divided into the training group and validation group (4:1), and two radiologists extracted their texture features from the contrast-enhanced T1-weighted images. We performed five different feature selection methods including Distance correlation, Gradient Boosting Decision Tree (GBDT), least absolute shrinkage and selection operator (LASSO), random forest (RF), eXtreme gradient boosting (Xgboost) and five independent classification models were built based on Linear discriminant analysis (LDA) algorithm.

Results

All five models showed promising results to discriminate malignant breast lesions from benign breast lesions, and the areas under the curve (AUCs) of receiver operating characteristic (ROC) were all above 0.830 in both training and validation groups. The model with a better discriminating ability was the combination of LDA + gradient boosting decision tree (GBDT). The sensitivity, specificity, AUC, and accuracy in the training group were 0.814, 0.883, 0.922, and 0.868, respectively; LDA + random forest (RF) also suggests promising results with the AUC of 0.906 in the training group.

Conclusion

The evidence of this study, while preliminary, suggested that a combination of MRI texture analysis and LDA algorithm could discriminate benign breast lesions from malignant breast lesions. Further multicenter researches in this field would be of great help in the validation of the result.

Supplemental Cancer Screening for Women With Dense Breasts: Guidance for Health Care Professionals

Mammography is the standard for breast cancer screening. The sensitivity of mammography in identifying breast cancer, however, is reduced for women with dense breasts. Thirty-eight states have passed laws requiring that all women be notified of breast tissue density results in their mammogram report. The notification includes a statement that differs by state, encouraging women to discuss supplemental screening options with their health care professionals (HCPs). Several supplemental screening tests are available for women with dense breast tissue, but no established guidelines exist to direct HCPs in their recommendation of preferred supplemental screening test. Tailored screening, which takes into consideration the patient's mammographic breast density and lifetime breast cancer risk, can guide breast cancer screening strategies that are more comprehensive. This review describes the benefits and limitations of the various available supplemental screening tests to guide HCPs and patients in choosing the appropriate breast cancer screening.

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

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

Ultra-High b-Value Diffusion-Weighted Imaging-Based Abbreviated Protocols for Breast Cancer Detection

OBJECTIVES

Contrast-enhanced (CE) magnetic resonance imaging (MRI) is the most effective imaging modality for breast cancer detection. A contrast agent-free examination technique would be desirable for breast MRI screening. The purpose of this study was to evaluate the capability to detect and characterize suspicious breast lesions with an abbreviated, non-contrast-enhanced MRI protocol featuring ultra-high b-value diffusion-weighted imaging (DWI) compared with CE images.

MATERIALS AND METHODS

The institutional review board-approved prospective study included 127 female subjects with different clinical indications for breast MRI. Magnetic resonance imaging examinations included DWI sequences with b-values of 1500 s/mm2 (b1500) and 2500 s/mm2 (b2500), native T1- and T2-weighted images, and CE sequences at 1.5 T and 3 T scanners. Two reading rounds were performed, including either the b1500 or the b2500 DWI in consecutive assessment steps: (A) maximum intensity projections (MIPs) of DWI, (B) DWI and apparent diffusion coefficient maps, (C) as (B) but with additional native T1- and T2-weighted images, and (D) as (C) but with additional CE images (full-length protocol). Two readers independently determined the presence of a suspicious lesion. Histological confirmation was obtained for conspicuous lesions, whereas the full MRI data set was obtained for inconspicuous and clearly benign lesions. Statistical analysis included calculation of diagnostic accuracy and interrater agreement via the intraclass correlation coefficient.

RESULTS

The cohort comprised 116 cases with BI-RADS 1 findings and 138 cases with BI-RADS ≥2 findings, including 38 histologically confirmed malignancies. For (A), breasts without pathological findings could be recognized with high diagnostic accuracy (negative predictive value, ≥97.0%; sensitivity, ≥92.1% for both readers), but with a limited specificity (≥58.3%; positive predictive value, ≥28.6%). Within the native readings, approach (C) with b2500 performed best (negative predictive value, 99.5%; sensitivity, 97.4%; specificity, 88.4%). The intraclass correlation coefficient was between 0.683 (MIP b1500) and 0.996 (full protocol).

CONCLUSIONS

A native abbreviated breast MRI protocol with advanced high b-value DWI might allow nearly equivalent diagnostic accuracy as CE breast MRI and seems to be well suited for lesion detection purposes.

Is Elevated Choline on Magnetic Resonance Spectroscopy a Reliable Marker of Breast Lesion Malignancy?

Background

Contemporary magnetic resonance imaging (MRI) of the breast represents a powerful diagnostic modality for cancer detection, with excellent sensitivity and high specificity. Magnetic resonance spectroscopy (MRS) is being explored as an additional tool for improving specificity in breast cancer detection, using multiparametric MRI. The aim of this study was to examine the possibility of 1H-MRS to discriminate malignant from benign breast lesions, using elevated choline (Cho) peak as an imaging biomarker.

Methods

A total of 60 patients were included in this prospective study: 30 with malignant (average age, 55.2 years; average lesion size, 35 mm) and 30 with benign breast lesions (average age, 44.8 years; average lesion size, 20 mm), who underwent multiparametric MRI with multivoxel 3D ¹H-MRS on a 1.5-T scanner in a 3-year period. Three patients with benign breast lesions were excluded from the study. All lesions were histologically verified. Peaks identified on ¹H-MRS were lipid (0.9, 2.3, 2.8, and 5.2 ppm), choline (3.2 ppm), and water peaks (4.7 ppm). Sensitivity and specificity, as well as positive and negative predictive values, were defined using ROC curves. Cohen's Kappa test of inter-test reliability was performed [testing the agreement between ¹H-MRS and histologic finding, and ¹H-MRS and MR mammography (MRM)].

Results

Choline peak was elevated in 24/30 malignant lesions and in 20/27 benign breast lesions. The sensitivity of ¹H-MRS was 0.8, specificity was 0.741, positive predictive value was 0.774, and negative predictive value was 0.769. Area under ROC was 0.77 (CI 0.640-0.871). Inter-test reliability between ¹H-MRS and histologic finding was 0.543 (moderate agreement) and that between ¹H-MRS and MRM was 0.573 (moderate agreement). False-negative findings were most frequently observed in invasive lobular cancers, while false-positive findings were most frequently observed in adenoid fibroadenomas.

Conclusion

Although elevation of the choline peak has a good sensitivity and specificity in breast cancer detection, both are significantly lower than those of multiparametric MRM. Inclusion of spectra located on tumor margins as well as analysis of lipid peaks could aid both sensitivity and specificity. An important ratio of false-positive and false-negative findings in specific types of breast lesions (lobular cancer and adenoid fibroadenoma) suggests interpreting these lesions with a caveat.

Patient Characteristics Associated With Patient-Reported Deterrents to Adjunct Breast Cancer Screening of Patients With Dense Breasts

BACKGROUND. The success of adjunct breast cancer screening of women with dense breasts can be enhanced by identifying and addressing patient concerns regarding adjunct screening modalities. OBJECTIVE. The purpose of this study was to identify patient characteristics associated with patient-reported concerns about adjunct breast cancer screening to facilitate the development of a more effective screening model for women with dense breasts. METHODS. Patients with dense breasts completed surveys between March 2017 and February 2018 regarding factors that might deter them from adjunct screening and about which of three hypothetical screening examinations they might prefer. Additional patient data were extracted from medical records, and socioeconomic data were imputed from federal census data. Logistic regression analyses were conducted to identify associations between patient characteristics and patient attitudes toward adjunct screening. RESULTS. Surveys were completed by 508 women (median age, 59.0 years) with dense breasts. Lower confidence in the sensitivity of mammography of dense breasts was independently associated with lesser concern about adjunct screening examination time (1 divided by adjusted odds ratio [1/AOR], 0.55 [95% CI, 0.34-0.89]), additional imaging that could result (1/AOR, 0.51 [95% CI, 0.31-0.85]), and greater preference for a more sensitive hypothetical screening examination (1/AOR, 1.85 [95% CI, 1.20-2.86]). Concern about examination cost, the most commonly cited deterrent to adjunct screening (66.9%), was independently associated with younger age (1/AOR, 1.45 [95% CI, 1.01-2.08]) but not with imputed socioeconomic variables or other tested variables. Younger age was also associated with lesser concern about pain (1/AOR, 0.69 [95% CI, 0.48-0.99]), additional imaging that could result (1/AOR, 0.48 [95% CI, 0.31-0.76]), and IV contrast administration (1/AOR, 0.56 [95% CI, 0.37-0.83]). CONCLUSION. Younger age and lower confidence in the sensitivity of mammography among women with dense breasts are independently associated with lesser patient concern about common deterrents to adjunct breast cancer screening. Younger age is independently associated with greater concern about the cost of undergoing adjunct breast cancer screening. CLINICAL IMPACT. Concerns about adjunct screening may be reduced by educating patients about the lower sensitivity of mammography of dense breasts and by finding ways to address or mitigate the financial and daily-life impact of adjunct screening, especially for younger patients.

MRI versus Mammography plus Ultrasound in Women at Intermediate Breast Cancer Risk: Study Design and Protocol of the MRIB Multicenter, Randomized, Controlled Trial

In women at high/intermediate lifetime risk of breast cancer (BC-LTR), contrast-enhanced magnetic resonance imaging (MRI) added to mammography ± ultrasound (MX ± US) increases sensitivity but decreases specificity. Screening with MRI alone is an alternative and potentially more cost-effective strategy. Here, we describe the study protocol and the characteristics of enrolled patients for MRIB feasibility, multicenter, randomized, controlled trial, which aims to compare MRI alone versus MX+US in women at intermediate breast cancer risk (aged 40-59, with a 15-30% BC-LTR and/or extremely dense breasts). Two screening rounds per woman were planned in ten centers experienced in MRI screening, the primary endpoint being the rate of cancers detected in the 2 arms after 5 years of follow-up. From July 2013 to November 2015, 1254 women (mean age 47 years) were enrolled: 624 were assigned to MX+US and 630 to MRI. Most of them were aged below 50 (72%) and premenopausal (45%), and 52% used oral contraceptives. Among postmenopausal women, 15% had used hormone replacement therapy. Breast and/or ovarian cancer in mothers and/or sisters were reported by 37% of enrolled women, 79% had extremely dense breasts, and 41% had a 15-30% BC-LTR. The distribution of the major determinants of breast cancer risk profiles (breast density and family history of breast and ovarian cancer) of enrolled women varied across centers.

Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

Background High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive screenings. Thus, methods to distinguish true-positive MRI screening results from false-positive ones are needed. Purpose To build prediction models based on clinical characteristics and MRI findings to reduce the rate of false-positive screening MRI findings in women with extremely dense breasts. Materials and Methods Clinical characteristics and MRI findings in Dutch breast cancer screening participants (age range, 50-75 years) with positive first-round MRI screening results (Breast Imaging Reporting and Data System 3, 4, or 5) after a normal screening mammography with extremely dense breasts (Volpara density category 4) were prospectively collected within the randomized controlled Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial from December 2011 through November 2015. In this secondary analysis, prediction models were built using multivariable logistic regression analysis to distinguish true-positive MRI screening findings from false-positive ones. Results Among 454 women (median age, 52 years; interquartile range, 50-57 years) with a positive MRI result in a first supplemental MRI screening round, 79 were diagnosed with breast cancer (true-positive findings), and 375 had false-positive MRI results. The full prediction model (area under the receiver operating characteristics curve [AUC], 0.88; 95% CI: 0.84, 0.92), based on all collected clinical characteristics and MRI findings, could have prevented 45.5% (95% CI: 39.6, 51.5) of false-positive recalls and 21.3% (95% CI: 15.7, 28.3) of benign biopsies without missing any cancers. The model solely based on readily available MRI findings and age had a comparable performance (AUC, 0.84; 95% CI: 0.79, 0.88; P = .15) and could have prevented 35.5% (95% CI: 30.4, 41.1) of false-positive MRI screening results and 13.0% (95% CI: 8.8, 18.6) of benign biopsies. Conclusion Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive first-round screening MRI rate and benign biopsy rate in women with extremely dense breasts. Clinical trial registration no. NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Imbriaco in this issue.

Molecular Breast Imaging: A Scientific Review

Molecular breast imaging (MBI) is a nuclear medicine technique that has evolved considerably over the past two decades. Technical advances have allowed reductions in administered doses to the point that they are now acceptable for screening. The most common radiotracer used in MBI, 99mTc-sestamibi, has a long history of safe use. Biopsy capability has become available in recent years, with early clinical experience demonstrating technically successful biopsies of MBI-detected lesions. MBI has been shown to be an effective supplemental screening tool in women with dense breasts and is also utilized for breast cancer staging, assessment of response to neoadjuvant chemotherapy, problem solving, and as an alternative to breast MRI in women who have a contraindication to MRI. The degree of background parenchymal uptake on MBI shows promise as a tool for breast cancer risk stratification. Radiologist interpretation is guided by a validated MBI lexicon that mirrors the BI-RADS lexicon. With short interpretation times, a fast learning curve for radiologists, and a substantially lower cost than breast MRI, MBI provides many benefits in the practices in which it is utilized. This review will discuss the current state of MBI technology, clinical applications of MBI, MBI interpretation, radiation dose associated with MBI, and the future of MBI.

Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review

Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.

Breast Density and Risk of Interval Cancers: The Effect of Annual Versus Biennial Screening Mammography Policies in Canada

Regular screening mammography reduces breast cancer mortality. However, in women with dense breasts, the performance of screening mammography is reduced, which is reflected in higher interval cancer rates (ICR). In Canada, population-based screening mammography programs generally screen women biennially; however, some provinces and territories offer annual mammography for women with dense breast tissue routinely and/or on recommendation of the radiologist. This study compared the ICRs in those breast screening programs with a policy of annual vs. those with biennial screening for women with dense breasts. Among 148,575 women with dense breasts screened between 2008 to 2010, there were 288 invasive interval breast cancers; screening programs with policies offering annual screening for women with dense breasts had fewer interval cancers 63/70,814 (ICR 0.89/1000, 95% CI: 0.67-1.11) compared with those with policies of usual biennial screening 225/77,761 (ICR 1.45 /1000 (annualized), 95% CI: 1.19-1.72) i.e. 63% higher (p = 0.0016). In screening programs where radiologists' screening recommendations were able to be analyzed, a total of 76,103 women were screened, with 87 interval cancers; the ICR was lower for recommended annual (65/69,650, ICR 0.93/1000, 95% CI: 0.71, 1.16) versus recommended biennial screening (22/6,453, ICR 1.70/1000 (annualized), 95%CI: 0.70, 2.71)(p = 0.0605). Screening program policies of annual as compared with biennial screening in women with dense breasts had the greatest impact on reducing interval cancer rates. We review our results in the context of current dense breast notification in Canada.