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Background Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the machine learning convolutional neural networks (CNNs) on multiparametric MRI to detect nodal metastasis with 18FDG-PET as ground truths. Materials and Methods Data were obtained via a retrospective search. Inclusion criteria were patients with bilateral breast MRI and 18FDG-PETand/or CT scans obtained before neoadjuvant chemotherapy. In total, 238 aLNs were obtained from 56 breast cancer patients with 18FDG-PET and/or CT and breast MRI data. Radiologists scored each node based on all MRI as diseased and non–diseased nodes. Five models were built using T1-W MRI, T2-W MRI, DCE MRI, T1-W + T2-W MRI, and DCE + T2-W MRI model. Performance was evaluated using receiver operating curve (ROC) analysis, including area under the curve (AUC). Results All CNN models yielded similar performance with an accuracy ranging from 86.08% to 88.50% and AUC ranging from 0.804 to 0.882. The CNN model using T1-W MRI performed better than that using T2-W MRI in detecting nodal metastasis. CNN model using combined T1- and T2-W MRI performed the best compared to all other models (accuracy = 88.50%, AUC = 0.882), but similar in AUC to the DCE + T2-W MRI model (accuracy = 88.02%, AUC = 0.880). All CNN models performed better than radiologists in detecting nodal metastasis (accuracy = 65.8%). Conclusion xxxxxx

Background: Breast carcinoma is classified in keeping with its morphologic features. As regards the WHO classification, the histopathological kinds of the breast carcinoma; ductal carcinomas, lobular carcinomas, and uncommon kinds, these are associated with particular imaging features, primarily based on every kind. Additionally, predictive biologic markers along with estrogen, progesterone receptors, HER2 receptor status, and Ki-67 may be suitable to sub-classify breast carcinoma into the intrinsic subtypes primarily based totally on gene expression profiling into: Luminal A, Luminal B, HER2+, and Triple Negative. Correlation among the imaging and the molecular subtypes has discovered an enormously circumscribed lesions with posterior acoustic enhancement without calcification inside the triple negative breast cancer subtype, microcalcifications are seen with the HER2+ subtype, but speculated lesions of irregular margin and posterior acoustic shadow with the luminal A and B subtypes, MRI is a longtime supplemental method to mammography and ultrasonography for the assessment of breast lesions. Diffusion-weighted MR imaging (DWI) has lately been incorporated into the breast MRI, moreover dynamic contrast enhanced MRI (DCE-MRI). Conclusion: Understanding medical collaboration of molecular subtypes and imaging features can assist the radiologist to help the clinician to adjust treatment consistent with the patient condition and tumor characteristics.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI examinations to reduce radiologist workload are needed. Purpose To determine the feasibility of an automated triaging method using deep learning (DL) to dismiss the highest number of MRI examinations without lesions while still identifying malignant disease. Materials and Methods This secondary analysis of data from the Dense Tissue and Early Breast Neoplasm Screening, or DENSE, trial evaluated breast MRI examinations from the first screening round performed in eight hospitals between December 2011 and January 2016. A DL model was developed to differentiate between breasts with lesions and breasts without lesions. The model was trained to dismiss breasts with normal phenotypical variation and to triage lesions (Breast Imaging Reporting and Data System [BI-RADS] categories 2-5) using eightfold internal-external validation. The model was trained on data from seven hospitals and tested on data from the eighth hospital, alternating such that each hospital was used once as an external test set. Performance was assessed using receiver operating characteristic analysis. At 100% sensitivity for malignant disease, the fraction of examinations dismissed from radiologic review was estimated. Results A total of 4581 MRI examinations of extremely dense breasts from 4581women (mean age, 54.3 years; interquartile range, 51.5-59.8 years) were included. Of the 9162 breasts, 838 had at least one lesion (BI-RADS category 2-5, of which 77 were malignant) and 8324 had no lesions. At 100% sensitivity for malignant lesions, the DL model considered 90.7% (95% CI: 86.7, 94.7) of the MRI examinations with lesions to be nonnormal and triaged them to radiologic review. The DL model dismissed 39.7% (95% CI: 30.0, 49.4) of the MRI examinations without lesions. The DL model had an average area under the receiver operating characteristic curve of 0.83 (95% CI: 0.80, 0.85) in the differentiation between normal breast MRI examinations and MRI examinations with lesions. Conclusion Automated analysis of breast MRI examinations in women with dense breasts dismissed nearly 40% of MRI scans without lesions while not missing any cancers. ClinicalTrials.gov: NCT01315015 © RSNA, 2021

Background: Breast cancer is a collection of diseases defined by distinct pathological (e.g., ductal, lobular, mucinous) and molecular characteristics (e.g., ER and PR, HER2 amplification, and more recently transcriptome-based classifications such as luminal and basal cancers). Molecular subtyping is beneficial for the diagnosis and individualized treatment of breast cancer.MRI is a supplemental technique to mammography and ultrasonography for the evaluation of breast lesions and to predict molecular subtypes of breast cancer. Studies have highlighted the value of DCE-MRI in reflecting the anatomic and functional properties of tumors and facilitating treatment. Objectives: The aim of this work was to assess the utility of MRI as an accurate method for detection of molecular subtypes of breast cancer. Patients and Methods: a retrospective clinical study of 2-years enrollment duration. The study was conducted at Radiology Department, Assuit University Hospitals on 50 lesions, patient age ranging from 23 to 66 years old with mean age was (46.9 ± SD) years. MR imaging studies were performed using a 1.5 T Magnetom Vision scanner with dedicated bilateral phased-array breast coil (Siemens, Erlangen, Germany). MRI sequences were 1. Axial T1WI. 2. Axial T2WI. 3. Axial STIR. 4. Axial DWI and ADC. 5. DCE-MRI. Results: The study included 50 lesions; 21 lesions were Luminal A, 15 lesions were Luminal B, 10 lesions were HER2+, and 4 lesions were TN. Histopathology 39 lesions were IDC-NOS, 1 lesion was IDC (medullary type), 7 lesions were mixed pathology IDC + DCIS, and 3 lesions were ILC. As regard the correlation between the histopathological type and grade, both were specific in differentiation between the molecular subtypes. According to the MRI findings it was found that T2 Intratumoral signal intensity, STIR, and the margin of the lesion were highly specific in differentiation, both L.N status and number were found that they were highly specific in differentiation (p

We describe a 78-year-old initially presenting with left breast cancer, status post mastectomy and bilateral dual-lumen breast implant placement, subsequently developed lung cancer years later status post lobectomy, who later developed FDG-avid pleural nodularity and thickening. The differential diagnosis of pleural thickening and nodularity can be broad, including metastatic cancer, asbestos-related pleural disease, loculated fluid (including simple pleural effusion, hemothorax, or chylothorax), and pleural infection. However, in the setting of two different primary malignancies, our patient's FGD-avid pleural thickening was concerning for metastatic disease. Further workup with a core-needle biopsy of the pleural nodule revealed “droplets of foreign material and foreign body giant cell reaction consistent with contents of ruptured medical device”, without evidence of malignancy. Prior imaging did not indicate breast implant compromise. A subsequent mammogram suggested findings of bilateral implant rupture, however, no further clinical workup was performed. A screening mammogram a decade later indicated possible extracapsular silicone within the right breast and left mastectomy site and an MRI was recommended for further workup. Subsequent MRI showed bilateral extracapsular silicone implant rupture with a thick layer of silicone signal within the left pleura in a similar distribution to her pleural thickening and nodularity. Her breast MRI findings, in conjunction with her pleural biopsy result, are concordant with pleural silicone granulomas from extracapsular breast implant rupture via radio-occult tract from prior left lobectomy procedure.

Introduction This retrospective study aimed to determine the percentage of MRI-detected breast cancers diagnosed using targeted ultrasound and standard 14-gauge (14g) biopsy in the setting of an Australian breast MRI service. This is of clinical relevance because malignancies not identifiable on mammography or by ultrasound may then require more invasive, technically demanding and costly MRI-guided interventional procedures, usually by large-core vacuum-assisted biopsy (VAB) or hook-wire localisation with open surgical biopsy. Methods On review of the 12-year period 2006-2018, we identified 67 new breast cancer events in 64 women where the diagnosis was made on the basis of the MRI scan findings either alone (n = 60) or in combination with a concurrent mammogram (n = 7), with no recorded clinical abnormality. The percentage in which malignancy was confirmed on histopathology using targeted ultrasound in combination with 14g biopsy was determined versus other biopsy methods, for both invasive cancer and in situ disease. Results Ultrasound-guided 14g biopsy was successful in establishing the presence of malignancy in 42/46 (91%) of events with a final diagnosis of invasive cancer, with 2 more proven by MRI-guided interventional procedures (1 VAB and 1 hook-wire) and 1 by open surgical biopsy. In the final case, a 5 mm focus on MRI with no sonographic correlate at the initial presentation was only identified and biopsied by ultrasound at 12-month follow-up. For events with a final diagnosis of DCIS/pLCIS (pleomorphic LCIS, n = 2), US-guided 14g biopsy was successful in 10/21 (48%), while 4/7 events with corresponding mammographic microcalcifications were proven by x-ray stereotactic interventions. A further 5 events had MRI-guided interventions (3 VAB and 2 hook-wires) and 1 an open surgical biopsy to confirm malignancy. In the final case (a woman with a 30 × 20 mm focal area of non-mass enhancement with corresponding microcalcifications consistent with DCIS), a pathologic diagnosis was not made until the patient presented 5 years later with invasive disease. There were also 3 instances of upgrades to invasion on final surgical pathology, one from pLCIS to microinvasion and 2 others from DCIS to IDC. Among the DCIS/pLCIS events, semi-random 14g core biopsy (sampling at the expected location of the MRI abnormality without a specific sonographic correlate) proved to be successful in 3 women. Conclusion Ultrasound-guided 14g core biopsy established a malignant diagnosis in 91% of invasive cancers and in 48% of DCIS/pLCIS cases. This relatively non-invasive, technically easy to perform and low-cost biopsy procedure can be used immediately when targeted ultrasound shows a correlate for a suspicious MRI scan finding. Careful imaging-pathologic correlation is required after 14g biopsy, and a discordant result will usually prompt recourse to an MRI-guided VAB or hook-wire localisation.

The purpose of this study is to evaluate the direct and indirect effects of a web-based, Protection Motivation Theory (PMT)–informed breast cancer education and decision support tool on intentions for risk-reducing medication and breast MRI among high-risk women. Women with ≥ 1.67% 5-year breast cancer risk (N = 995) were randomized to (1) control or (2) the PMT-informed intervention. Six weeks post-intervention, 924 (93% retention) self-reported PMT constructs and behavioral intentions. Bootstrapped mediations evaluated the direct effect of the intervention on behavioral intentions and the mediating role of PMT constructs. There was no direct intervention effect on intentions for risk-reducing medication or MRI (p’s ≥ 0.12). There were significant indirect effects on risk-reducing medication intentions via perceived risk, self-efficacy, and response efficacy, and on MRI intentions via perceived risk and response efficacy (p’s ≤ 0.04). The PMT-informed intervention effected behavioral intentions via perceived breast cancer risk, self-efficacy, and response efficacy. Future research should extend these findings from intentions to behavior. ClinicalTrials.gov Identifier: NCT03029286 (date of registration: January 24, 2017).

BACKGROUND The associations between diffusion kurtosis imaging (DKI)-derived parameters and clinical prognostic factors of breast cancer have not been fully evaluated; this knowledge may have implications for outcome prediction and treatment strategies. PURPOSE To determine associations between quantitative diffusion parameters derived from DKI and diffusion-weighted imaging (DWI) and the prognostic factors and molecular subtypes of breast cancer. STUDY TYPE Retrospective. POPULATION A total of 383 women (mean age, 53.8 years; range, 31-82 years) with breast cancer who underwent preoperative breast MRI including DKI and DWI. FIELD STRENGTH/SEQUENCE A 3.0 T; DKI using a spin-echo echo-planar imaging (EPI) sequence (b values: 200, 500, 1000, 1500, and 2000 sec/mm2 ), DWI using a readout-segmented EPI sequence (b values: 0 and 1000 sec/mm2 ) and dynamic contrast-enhanced breast MRI. ASSESSMENT Two radiologists (J.Y.K. and H.S.K. with 9 years and 1 year of experience in MRI, respectively) independently measured kurtosis, diffusivity, and apparent diffusion coefficient (ADC) values of breast cancer by manually placing a regions of interest within the lesion. Diffusion measures were compared according to nodal status, grade, and molecular subtypes. STATISTICAL TESTS Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, receiver operating characteristic (ROC) analysis, and multivariate logistic regression analysis. (Statistical significance level of P

PURPOSE: To introduce proton density water-fraction (PDWF) as a confounder-corrected MR-based biomarker of mammographic breast density, a known risk factor for breast cancer. METHODS: Chemical shift encoded (CSE) MR images were acquired using a low flip angle to provide proton density contrast from multiple echo times. Fat and water images, corrected for known biases, were produced by a six-echo confounder-corrected (CC) CSE-MRI algorithm. Fibroglandular tissue (FGT) volume was calculated from whole-breast segmented PDWF maps at 1.5T and 3T. The method was evaluated in (1) a physical fat-water phantom and (2) normal volunteers. Results from two- and three-echo CSE-MRI methods were included for comparison. RESULTS: Six-echo CC-CSE-MRI produced unbiased estimates of the total water volume in the phantom (mean bias 3.3%) and was reproducible across protocol changes (repeatability coefficient=14.8 cm(3) and 13.97 cm(3) at 1.5T and 3.0T respectively) and field strengths (repeatability coefficient=51.7 cm(3)) in volunteers, while the two- and three-echo CSE-MRI approaches produced biased results in phantoms (mean bias 30.7% and 10.4%) that was less reproducible across field strengths in volunteers (repeatability coefficient=82.3 cm(3) and 126.3 cm(3)). Significant differences in measured FGT volume was found between the six-echo CC-CSE-MRI and the two- and three-echo CSE-MRI approaches (P = 0.002 and P =0.001). CONCLUSION: The use of six-echo CC-CSE-MRI to create unbiased PDWF maps that reproducibly quantify FGT in the breast is demonstrated. Further studies are needed to correlate this quantitative MR biomarker for breast density with mammography and overall risk for breast cancer.

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.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Breast cancer (BC) is the second most common cancer in women, affecting 1 in 8 women in the United States (12.5%) in their lifetime. However, some women have a higher lifetime risk of BC because of genetic and lifestyle factors, mammographic breast density, and reproductive and hormonal factors. Because BC risk is variable, screening and prevention strategies should be individualized after considering patient-specific risk factors. Thus, health care professionals need to be able to assess risk profiles, identify high-risk women, and individualize screening and prevention strategies through a shared decision-making process. In this article, we review the risk factors for BC, risk-assessment models that identify high-risk patients, and preventive medications and lifestyle modifications that may decrease risk. We also discuss the benefits and limitations of various supplemental screening methods.

Objective To review MRI findings of pure lobular neoplasia (LN) on MRI guided biopsy, evaluate surgical and clinical outcomes, and assess imaging findings predictive of upgrade to malignancy. Methods HIPAA compliant, IRB-approved retrospective review of our MRI-guided breast biopsy database from October 2008–January 2015. Biopsies yielding atypical lobular hyperplasia or lobular carcinoma in situ were included in the analysis; all biopsy slides were reviewed by a dedicated breast pathologist. Imaging indications, MRI findings, and histopathology were reviewed. Statistical analysis was performed using the two-tailed Fisher exact-test and the t-test, and 95% CIs were determined. A p Results Database search yielded 943 biopsies in 785 patients of which 65/943 (6.9%) reported LN as the highest risk pathologic lesion. Of 65 cases, 32 were found to have LN as the dominant finding on pathology and constituted the study population. All 32 findings were mammographically and sonographically occult. Three of 32 (9.3%) cases of lobular neoplasia were upgraded to malignancy, all LCIS (one pleomorphic and two classical). The most common MRI finding was focal, heterogenous non-mass enhancement with low T2 signal. No clinical features or imaging findings were predictive of upgrade to malignancy. Conclusion Incidence of pure lobular neoplasia on MRI guided biopsy is low, with comparatively low incidence of upgrade to malignancy. No imaging or clinical features are predictive of upgrade on surgical excision, therefore, prudent radiologic-pathologic correlation is necessary.

Background This study aims to observe and analyze the effect of diffusion weighted magnetic resonance imaging (MRI) on the patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. Methods Fifty patients (mean age, 48.7 years) with stage II–III breast cancer who underwent neoadjuvant chemotherapy and preoperative MRI between 2016 and 2020 were retrospectively evaluated. The associations between preoperative breast MRI findings/clinicopathological features and outcomes of neoadjuvant chemotherapy were assessed. Results Clinical stage at baseline (OR: 0.104, 95% confidence interval (CI) 0.021–0.516, P = 0.006) and standard apparent diffusion coefficient (ADC) change (OR: 9.865, 95% CI 1.024–95.021, P = 0.048) were significant predictive factors of the effects of neoadjuvant chemotherapy. The percentage increase of standard ADC value in pathologic complete response (pCR) group was larger than that in non-pCR group at first time point (P P Conclusions Our findings support that change in standard ADC values and clinical stage at baseline can predict the effects of neoadjuvant chemotherapy for patients with breast cancer in early stage.

Background Although nonmass enhancement (NME) extension to the nipple at preoperative MRI frequently leads to sacrifice of the nipple-areolar complex (NAC), its correlation with pathologically confirmed NAC involvement is unclear. Purpose To evaluate the diagnostic accuracy of using NME extension to the subareolar region at breast MRI to predict pathologic nipple involvement and the eligibility for nipple-sparing mastectomy. Materials and Methods From November 2017 to November 2019, the authors prospectively enrolled participants with breast cancer and NME within 2 cm of the nipple at breast MRI who underwent surgery that included removal of the NAC. The authors evaluated NME extensions that were ipsilateral and contiguous with the biopsy-proven tumor lesions on images acquired during the early contrast phases. Pathologic nipple involvement and the distance from the nipple to the nearest cancer cell were evaluated by using serial vertical sectioning of the area extending from the entire NAC to the tumor. The primary end point was the positive predictive value (PPV) of NME, which was calculated as follows: (number with pathologic nipple invasion and NME extension to the nipple at breast MRI/number with NME extension to the nipple at breast MRI) × 100. Results Of 64 women (mean age, 52 years ± 9.8 [standard deviation]), 49 (77%) had NME extension to the nipple at breast MRI. The PPV of NME extension to the nipple was 86% (42 of 49 women; 95% CI: 73, 94). Among the 15 participants without NME extension to the nipple, only one (7%) had pathologic nipple involvement. The diagnostic accuracy of using NME extension to the nipple was 88% (56 of 64 women; 95% CI: 77, 95). The radiologic distance correlated well with the pathologic distance (Spearman correlation coefficient = 0.71, P = .003). Conclusion Nonmass enhancement extension to the nipple base at preoperative MRI has a high positive predictive value for identifying tumor involvement of the nipple, a contraindication to nipple-sparing mastectomy. © RSNA, 2021 Online supplemental material is available for this article.

Background The optimal axillary lymph node (ALN) management strategy in patients diagnosed with ductal carcinoma in situ (DCIS) preoperatively remains controversial. The value of breast magnetic resonance imaging (MRI) to predict ALN metastasis pre-operative DCIS patients was evaluated. Methods Patients with primary DCIS with or without pre-operative breast MRI evaluation and underwent breast surgery were recruited from single institution. The value of breast MRI for ALN evaluation, predictors of breast and ALN surgeries, upgrade from DCIS to invasive cancer, and ALN metastasis were analyzed. Results A total of 682 cases with pre-operative diagnosis of DCIS were enrolled in current study. The rate of upgrade to invasive cancer were found in 34.2% of specimen, and this upgrade rate is 23% for patients who received breast conserving surgery and 40.7% for mastectomy (p Conclusion Breast MRI had high NPV to predict ALN metastasis in pre-OP DCIS patients, which is useful and could be provided as shared decision-making reference.

Background. Breast cancer is the most common cancer in women worldwide. Despite advances in treatment of breast cancer, early-stage breast cancer detection is limited by screening mammography and often requires additional breast imaging.The purpose of the study was to analyze available data on modern imaging techniques of additional breast visualization used for improving breast cancer screening.Material and methods. The review includes data from randomized controlled trials and meta-analyzes on the effectiveness of breast imaging techniques for early-stage breast cancer detection. The search was carried out in pubmed, Web of science, scopus and cochrane library databases. Out of 100 publications published over the past 7 years, 51 were included in the presented review.Results. Breast cancer screening using various imaging techniques has been carried out in the world for more than 30 years, and over the past 10 years significant progress has been made in improving X-ray, ultrasound and magnetic resonance technologies in the early breast cancer detection. At present, healthcare organizers are faced with the question of choosing a vector for improving the breast cancer screening program by introducing digital tomosynthesis, contrast spectral mammography, or accelerated mri. According to the current results of the analysis of literature data, contrast spectral mammography and accelerated mri have the highest sensitivity, but studies of sensitivity, specificity, positive and negative predictive values (ppv, npv) are ongoing.Conclusion. The data presented in the review confirm the necessity for finding the vector for improving the breast cancer screening program using multicenter prospective trials.

Several articles in the literature have demonstrated a promising role for breast MRI techniques that are more economic in total exam time than others when used as supplement to mammography for detection and diagnosis of breast cancer. There are many technical factors that must be considered in the shortened breast MRI protocols to cut down time of standard ones, including using optimal fat suppression, gadolinium-chelates intravascular contrast administrations for dynamic imaging with post processing subtractions and maximum intensity projections (MIP) high spatial and temporal resolution among others. Multiparametric breast MRI that includes both gadolinium-dependent, i.e., dynamic contrast-enhanced (DCE-MRI) and gadolinium-free techniques, i.e., diffusion-weighted/diffusion-tensor magnetic resonance imaging (DWI/DTI) are shown by several investigators that can provide extremely high sensitivity and specificity for detection of breast cancer. This article provides an overview of the proven indications for breast MRI including breast cancer screening for higher than average risk, determining chemotherapy induced tumor response, detecting residual tumor after incomplete surgical excision, detecting occult cancer in patients presenting with axillary node metastasis, detecting residual tumor after incomplete breast cancer surgical excision, detecting cancer when results of conventional imaging are equivocal, as well patients suspicious of having breast implant rupture. Despite having the highest sensitivity for breast cancer detection, there are pitfalls, however, secondary to false positive and false negative contrast enhancement and contrast-free MRI techniques. Awareness of the strengths and limitations of different approaches to obtain state of the art MR images of the breast will facilitate the work-up of patients with suspicious breast lesions.

There has been an increase in reporting clinical or radiological axillary lymphadenopathy after the coronavirus disease (COVID-19) vaccination. Cancer care is complex and multidisciplinary, which requires care events to be orchestrated promptly; radiology often serves a key role in diagnosis, post-diagnosis and is sometimes the patient’s first step in cancer care initiation, especially in breast cancer. Radiologists are also a key role in other Multidisciplinary Teams (MDT) dealing with different departments. Therefore, identifying unnecessary management within the health system can generally enhance the patient’s experience, reduce the pressure from providing extra health services, and reduce health costs. Based on personal observation and previous literature, the author concludes that patients having breast cancer or recent breast cancer diagnosis in the pre- or peri-treatment setting could benefit from receiving a vaccination, if possible, in the anterolateral thigh or contralateral arm regardless if this vaccine is for influenza, HPV, etc. Whether this is applicable for the COVID-19 vaccine remains unanswered. This approach will potentially reduce the patient anxiety from having a recurrence or failure of treatment and decrease the strain of the health care system both functionally and economically. In addition, this approach can potentially reduce or eliminate cancellations, delays, and rescheduling of relevant imaging modalities. Also, the author suggests adding a history of vaccinations to all the imaging request forms; countries with digital health services can reap the benefit of generating extensive epidemiological data of post-vaccination lymphadenopathy. Thus, creating new base-evidence guidelines for managing reactive post-vaccination lymphadenopathy, and potentially avoiding duplicating unnecessary imaging and patient over-treatment.

The significance of background parenchymal enhancement (BPE) on screening and diagnostic breast MRI continues to be elucidated. Background parenchymal enhancement was initially deemed probably benign and followed or thought of as an artifact degrading the accuracy of breast cancer detection on breast MRI examinations. Subsequent research has focused on understanding the role of BPE regarding screening breast MRI. Today, there is growing evidence that a myriad of factors affect BPE, which in turn may influence patient outcomes. Additionally, BPE could represent an important risk factor for the future development of breast cancer. This article aims to describe the most up-to-date research on BPE as it relates to screening breast MRI in premenopausal women.

To investigate machine learning approaches for radiomics-based prediction of prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor heterogeneity and angiogenesis properties on magnetic resonance imaging (MRI). This prospective study examined 291 invasive cancers in 288 patients who underwent breast MRI at 3 T before treatment between May 2017 and July 2019. Texture and perfusion analyses were performed and a total of 160 parameters for each cancer were extracted. Relationships between MRI parameters and prognostic biomarkers were analyzed using five machine learning algorithms. Each model was built using only texture features, only perfusion features, or both. Model performance was compared using the area under the receiver-operating characteristic curve (AUC) and the DeLong method, and the importance of MRI parameters in prediction was derived. Texture parameters were associated with the status of hormone receptors, human epidermal growth factor receptor 2, and Ki67, tumor size, grade, and molecular subtypes (p < 0.002). Perfusion parameters were associated with the status of hormone receptors and Ki67, grade, and molecular subtypes (p < 0.003). The random forest model integrating texture and perfusion parameters showed the highest performance (AUC = 0.75). The performance of the random forest model was the best with a special scale filter of 0 (AUC = 0.80). The important parameters for prediction were texture irregularity (entropy) and relative extracellular extravascular space (Ve). Radiomic machine learning that integrates tumor heterogeneity and angiogenesis properties on MRI has the potential to noninvasively predict prognostic factors of breast cancer. • Machine learning, integrating tumor heterogeneity and angiogenesis properties on MRI, can be applied to predict prognostic biomarkers and molecular subtypes in breast cancer. • The random forest model showed the best predictive performance among the five machine learning models (logistic regression, decision tree, naive Bayes, random forest, and artificial neural network). • The most important MRI parameters for predicting prognostic factors in breast cancer were texture irregularity (entropy) among texture parameters and relative extracellular extravascular space (Ve) among perfusion parameters.

Objectives We examined the effects of aging and of gadolinium-based contrast agent (GBCA) exposure on MRI measurements in brain nuclei of healthy women. Methods This prospective, IRB-approved single-center case-control study enrolled 100 healthy participants of our high-risk screening center for hereditary breast cancer, who had received at least six doses of macrocyclic GBCA (exposed group) or were newly entering the program (GBCA-naïve group). The cutoff “at least six doses” was chosen to be able to include a sufficient number of highly exposed participants. All participants underwent unenhanced 3.0-T brain MRI including quantitative T1, T2, and R2* mapping and T1- and T2-weighted imaging. The relaxation times/signal intensities were derived from region of interest measurements in the brain nuclei performed by a radiologist and a neuroradiologist, both board certified. Statistical analysis was based on descriptive evaluations and uni-/multivariable analyses. Results The participants (exposed group: 49, control group: 51) were aged 42 ± 9 years. In a multivariable model, age had a clear impact on R2* (p < 0.001–0.012), T2 (p = 0.003–0.048), and T1 relaxation times/signal intensities (p < 0.004–0.046) for the majority of deep brain nuclei, mostly affecting the substantia nigra, globus pallidus (GP), nucleus ruber, thalamus, and dentate nucleus (DN). The effect of prior GBCA administration on T1 relaxation times was statistically significant for the DN, GP, and pons (p = 0.019–0.037). Conclusions In a homogeneous group of young to middle-aged healthy females aging had an effect on T2 and R2* relaxation times and former GBCA applications influenced the measured T1 relaxation times. Key Points The quantitative T1, T2, and R2* relaxation times measured in women at high risk of developing breast cancer showed characteristic bandwidth for all brain nuclei examined at 3.0-T MRI. The effect of participant age had a comparatively strong impact on R2*, T2, and T1 relaxation times for the majority of brain nuclei examined. The effect of prior GBCA administrations on T1 relaxation times rates was comparatively less pronounced, yielding statistically significant results for the dentate nucleus, globus pallidus, and pons. Summary statement Healthy women with and without previous GBCA-enhanced breast MRI exhibited age-related T2* and T2 relaxation alterations at 3.0 T-brain MRI. T1 relaxation alterations due to prior GBCA administration were comparatively less pronounced.

Background The role of preoperative MRI in women 35 years of age or younger with breast cancer remains controversial. Purpose To determine the association between preoperative MRI and surgical outcomes in women aged 35 years or younger with breast cancer by using propensity score (PS) analysis to investigate the impact of preoperative MRI. Materials and Methods Women 35 years of age or younger diagnosed with breast cancer between 2007 and 2017 who had or had not undergone preoperative breast MRI were retrospectively identified. The MRI detection rate of additional suspicious lesions was analyzed, and changes in surgical management were recorded. Inverse probability weighting (IPW) and PS matching were used to adjust 19 variables and to create a balance between the two groups. Surgical outcomes were compared by using univariable logistic regression. Results Among 964 women (mean age ± standard deviation, 32 years ± 3), 665 (69%) had undergone preoperative MRI (MRI group; mean age, 32 years ± 3) and 299 (31%) had not (no-MRI group; mean age, 32 years ± 3). In the MRI group, additional suspicious lesions were found in 178 of the 665 women (27%), with 88 of those 178 women (49%) having malignant lesions. The surgical management was changed in 99 of the 665 women (15%) due to MRI findings, which was appropriate for 62 of those 99 women (63%). In the IPW analysis, the MRI group showed lower odds of repeat surgery (odds ratio [OR], 0.13; 95% CI: 0.07, 0.21; P < .001) and higher odds of initial mastectomy (OR, 1.62; 95% CI: 1.17, 2.25; P = .004). However, there was no difference in the overall mastectomy rate (OR, 1.24; 95% CI: 0.91, 1.68; P = .17) compared with the no-MRI group. These results were consistent when using the PS matching method. Conclusion Preoperative MRI in young women with breast cancer is useful for detecting additional malignancy and improving surgical outcomes by reducing the repeat surgery rate, with a similar likelihood of overall mastectomy. © RSNA, 2021 Online supplemental material is available for this article.

BACKGROUND. Higher categories of background parenchymal enhancement (BPE) increase breast cancer risk. However, current clinical BPE categorization is subjective. OBJECTIVE. Using a semiautomated segmentation algorithm, we calculated quantitative BPE measures and investigated the utility of individual features and feature pairs in significantly predicting subsequent breast cancer risk compared with radiologist-assigned BPE category. METHODS. In this retrospective case-control study, we identified 95 women at high risk of breast cancer but without a personal history of breast cancer who underwent breast MRI. Of these women, 19 subsequently developed breast cancer and were included as cases. Each case was age matched to four control patients (76 control patients total). Sociodemographic characteristics were compared between the cases and matched control patients using the Mann-Whitney U test. From each dynamic contrast-enhanced MRI examination, quantitative fibroglandular tissue and BPE measures were computed by averaging enhancing voxels above enhancement ratio thresholds (0–100%), totaling the enhancing volume above thresholds (BPE volume in cm(3)), and estimating the percentage of enhancing tissue above thresholds relative to total breast volume (BPE%) on each gadolinium-enhanced phase. For the 91 imaging features generated, we compared predictive performance using conditional logistic regression with 80:20 holdout cross validation and ROC curve analysis. ROC AUC was the figure of merit. Sensitivity, specificity, PPV, and NPV were also computed. All feature pairs were exhaustively searched to identify those with the highest AUC and Youden index. A DeLong test was used to compare predictive performance (AUCs). RESULTS. Women subsequently diagnosed with breast cancer were more likely to have mild, moderate, or marked BPE (odds ratio, 3.0; 95% CI, 0.9–10.0; p = .07). According to ROC curve analysis, a BPE category threshold greater than minimal resulted in a maximized AUC (0.62) in distinguishing cases from control patients. Compared with BPE category, the first gadolinium-enhanced (phase 1) BPE% at the 30% and 40% enhancement ratio thresholds yielded significantly higher AUC values of 0.85 (p = .0007) and 0.84 (p = .0004), respectively. Feature combinations showed similar AUC values with improved sensitivity. CONCLUSION. Preliminary data indicate that quantitative BPE measures may outperform radiologist-assigned category in breast cancer risk prediction. CLINICAL IMPACT. Future risk prediction models that incorporate quantitative measures warrant additional investigation.

Objectives: The purpose of this study was to assess the accuracy of contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging in distinguishing benign from malignant non-mass-like breast lesions. Methods: 103 lesions showing non-mass-like enhancement in 100 consecutive patients were analyzed. Distribution, internal enhancement patterns, and contrast kinetic curve patterns were classified according to the BI-RADS lexicon. Apparent diffusion coefficient (ADC) values were obtained from manually placed regions of interest (ROIs) on diffusion-weighted images. The optimal ADC value threshold for the distinction between benign and malignant lesions was determined by ROC analysis. Univariate and multivariate analyses were performed to identify independent predictors of malignancy, and the probability of malignancy was calculated for various combinations of findings. Histological diagnosis obtained by means of core needle biopsy was used as gold standard. Results: According to the univariate and multivariate analysis, odds ratios for malignancy were significantly elevated for clumped or clustered ring internal enhancement and low ADC values (p < 0.001), whereas distribution patterns and contrast kinetic patterns were not significantly correlated with benignity or malignancy. In non-mass lesions with homogeneous or heterogeneous internal enhancement and ADC values greater than 1.26×10 -3 mm 2 /s, no malignancy was detected, while all other combinations of findings had a probability of malignancy ranging from 22.2 to 76.6%. Conclusions: A combination of BI-RADS descriptors of internal enhancement and ADC values is useful for the differential diagnosis of lesions showing non-mass enhancement. Lesions with homogeneous or heterogeneous enhancement and high ADC can be followed up, while all other lesions should be biopsied. Doi: 10.28991/SciMedJ-2021-0302-1 Full Text: PDF

During pregnancy and lactation, the breast undergoes unique changes that manifest as varied clinical and imaging findings. Understanding the expected physiologic changes of the breast as well as recognizing the best imaging modalities for a given clinical scenario can help the radiologist identify the abnormalities arising during this time. Discussion with the patient about the safety of breast imaging can reassure patients and improve management. This article reviews the physiologic changes of the breast during pregnancy and lactation; the safety and utility of various imaging modalities; upto-date consensus on screening guidelines; recommendations for diagnostic evaluation of breast pain, palpable abnormalities, and nipple discharge; and recommendations regarding advanced modalities such as breast MRI. In addition, the commonly encountered benign and malignant entities affecting these patients are discussed.

Objective It is unknown how patients prioritize gadolinium-based contrast media (GBCM) benefits (detection sensitivity) and risks (reactions, gadolinium retention, cost). The purpose of this study is to measure preferences for properties of GBCM in women at intermediate or high risk of breast cancer undergoing annual screening MRI. Methods An institutional reviewed board-approved prospective discrete choice conjoint survey was administered to patients at intermediate or high risk for breast cancer undergoing screening MRI at 4 institutions (July 2018–March 2020). Participants were given 15 tasks and asked to choose which of two hypothetical GBCM they would prefer. GBCMs varied by the following attributes: sensitivity for cancer detection (80–95%), intracranial gadolinium retention (1–100 molecules per 100 million administered), severe allergic-like reaction rate (1–19 per 100,000 administrations), mild allergic-like reaction rate (10–1000 per 100,000 administrations), out-of-pocket cost ($25–$100). Attribute levels were based on published values of existing GBCMs. Hierarchical Bayesian analysis was used to derive attribute “importance.” Preference shares were determined by simulation. Results Response (87% [247/284]) and completion (96% [236/247]) rates were excellent. Sensitivity (importance = 44.3%, 95% confidence interval = 42.0–46.7%) was valued more than GBCM-related risks (mild allergic-like reaction risk (19.5%, 17.9–21.1%), severe allergic-like reaction risk (17.0%, 15.8–18.1%), intracranial gadolinium retention (11.6%, 10.5–12.7%), out-of-pocket expense (7.5%, 6.8–8.3%)). Lower income participants placed more importance on cost and less on sensitivity (p < 0.01). A simulator is provided that models GBCM preference shares by GBCM attributes and competition. Conclusions Patients at intermediate or high risk for breast cancer undergoing MRI screening prioritize cancer detection over GBCM-related risks, and prioritize reaction risks over gadolinium retention. Key Points • Among women undergoing annual breast MRI screening, cancer detection sensitivity (attribute “importance,” 44.3%) was valued more than GBCM-related risks (mild allergic reaction risk 19.5%, severe allergic reaction risk 17.0%, intracranial gadolinium retention 11.6%, out-of-pocket expense 7.5%). • Prospective four-center patient preference data have been incorporated into a GBCM choice simulator that allows users to input GBCM properties and calculate patient preference shares for competitor GBCMs. • Lower-income women placed more importance on out-of-pocket cost and less importance on cancer detection (p < 0.01) when prioritizing GBCM properties.

To investigate the impact of response evaluation after neoadjuvant chemotherapy (NAC) in breast cancer patients, assessed by both magnetic resonance imaging (MRI) and pathology, on disease-free survival (DFS). This single-center, retrospective cohort study included consecutive breast cancer patients who underwent NAC and preoperative breast MRI. Resolution of invasive carcinoma in the breast and axilla was defined as complete pathological response (pCR). Radiological complete response (rCR) was defined as the absence of abnormal enhancement in the tumor site. Kaplan-Meier estimator was used to estimate the disease-free survival on 60 months. Cox regression analysis was used to estimate hazard ratio (HR) values. In total, 317 patients were included with a mean age of 47.3 years and a mean tumor size of 39.8 mm. The most common immunophenotype was luminal (44.9%), followed by triple-negative (26.8%). Overall, 126 patients (39.7%) had an rCR, while 119 (37.5%) had pCR; the radiological and pathological responses agreed in 252 cases (79.5%). During follow-up, patients who had rCR and pCR had a better DFS curve compared to patients with non-rCR and non-pCR, while those who had rCR or pCR presented an intermediate curve (Log-rank p = 0.003). Multivariate analysis showed a higher risk of recurrence in patients with non-rCR and non-pCR (HR: 5,626; p = 0.020) and those who had a complete response on MRI or pathology only (HR: 4,369; p = 0.067), when compared to patients with rCR and pCR. The association of MRI and pathological responses after NAC might better stratify the risk of recurrence and prognosis in breast cancer patients. • Association of response evaluation after neoadjuvant chemotherapy by pathology and MRI allows better stratification of prognosis. • Complete response to neoadjuvant chemotherapy on pathology and MRI was related to better disease-free survival. • Complete response on MRI or pathology only had a greater risk of recurrence.

Background/Aim: BI-RADS category 4 breast lesions have widely varying malignancy rates and they are almost always evaluated with biopsy. However, especially in the 4a subgroup with a benign character of up to 98%, many patients undergo unnecessary invasive procedures. Breast MRI can be a good problem-solving method to reduce unnecessary invasive procedures, but there are very few publications on BI-RADS category 4 solid lesions. This study aimed to investigate the contribution of breast MRI in Breast Imaging Reporting and Data System (BI-RADS) category 4 solid mass lesions detected by Mammography and Ultrasonography.Methods: In this retrospective cohort study, ultrasound reports of patients examined in the radiology breast imaging unit between January 2015 and December 2017 were reviewed. Cases reported as BI-RADS category 4 with a solid mass on ultrasonography were determined. Patients without histopathological diagnosis and/or breast MRI were excluded from the study. After the implementation of the exclusion criteria, 121 solid lesions of 104 female patients were included in the study. US and MRI images of the patients were re-evaluated by two radiologists and BI-RADS scoring was performed again. The obtained data were analyzed statistically together with histopathological data.Results: With breast MRI, 74 of 121 BI-RADS category 4 lesions were downgraded while 13 lesions were upgraded. Of the 74 downgraded lesions, 61 were BI-RADS category 2 and 3, which do not require a biopsy. Only one of these lesions was histopathologically malignant. Of the 13 lesions upgraded, 6 were in BI-RADS category 5, two of which were benign. The sensitivity, specificity, positive and negative predictive values of MRI were 93.8%, 56.2%, 24.6%, and 98.3%, respectively. Conclusion: In our study, breast MRI reduced the BI-RADS categories to 2 and 3 in approximately half of the BI-RADS category 4 solid lesions detected by ultrasound. Therefore, problem-solving MRI may be useful to avoid unnecessary invasive procedures in these patients.

Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2-overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor-positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response.©RSNA, 2021.

Breast MRI is the most sensitive modality for the detection of breast cancer. However, false-negative cases may occur, in which the cancer is not visualized at MRI and is instead diagnosed with another imaging modality. The authors describe the causes of false-negative breast MRI results, which can be categorized broadly as secondary to perceptual errors or cognitive errors, or nonvisualization secondary to nonenhancement of the tumor. Tips and strategies to avoid these errors are discussed. Perceptual errors occur when an abnormality is not prospectively identified, yet the examination is technically adequate. Careful development of thorough search patterns is critical to avoid these errors. Cognitive errors occur when an abnormality is identified but misinterpreted or mischaracterized as benign. The radiologist may avoid these errors by utilizing all available prior examinations for comparison, viewing images in all planes to better assess the margins and shapes of abnormalities, and appropriately integrating all available information from the contrast-enhanced, T2-weighted, and T1-weighted images as well as the clinical history. Despite this, false-negative cases are inevitable, as certain subtypes of breast cancer, including ductal carcinoma in situ, invasive lobular carcinoma, and certain well-differentiated invasive cancers, may demonstrate little to no enhancement at MRI, owing to differences in angiogenesis and neovascularity. MRI is a valuable diagnostic tool in breast imaging. However, MRI should continue to be used as a complementary modality, with mammography and US, in the detection of breast cancer. ©RSNA, 2021.

Purpose: To evaluate the utility of high-resolution, 3-D diffusion-weighted imaging (DWI) in the detection of breast cancer and to compare the sensitivity, specificity, and area under the curves of DWI and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Material and method: Prospective IEC approved study included 131 breast lesions detected on mammography and breast ultrasound. Cases underwent MRI on a 3 Tesla scanner using a dedicated breast coil. T2WI, STIR, T1WI, and dynamic post contrast MR. DWI MRI with b value of 50, 800, and 1500 s/mm2. Post-processing data with apparent diffusion coefficient (ADC) calculations and kinetic curves were obtained. Characteristics for lesions were analysed as per ACR BI-RADS descriptors. Final histopathological diagnosis was considered as the standard of reference. c2 test, t-test, receiver operating characteristic (ROC) curve analysis, pairwise comparison of ROC curves, sensitivity, specificity, diagnostic accuracy, and area under the curve (AUC) were calculated. Results: Sixty-six (50.38%) malignant and 65 (59.62%) benign lesions were included in the study. The mean ADC of malignant lesions was 0.870 × 10-3 mm2/s and 1.637 × 10-3 mm2/s (p < 0.0001) for benign lesions. Sensitivity and specificity for DWI were 95.45% and 90.76%, respectively, and for DCE-MRI they were 96.97% and 87.69%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) were obtained at 91.30% and 95.16%, respectively, in DWI while in DCE-MRI they were 88.88% and 96.61%, respectively. The AUC for ADC was 0.979. In ROC comparison of AUC for DWI 0.931 and for DCE-MRI 0.923, the difference between the areas was 0.00781 (p = 0.782). Conclusions: High-resolution DWI is a non-contrast MRI technique, which improves the lesion detection with diagnostic performance comparable to DCE-MRI and has potential as an adjunct with screening mammography.

In 2016, the World Health Organization added Breast Implant-Associated Anaplastic Large Cell lymphoma as a provisionally recognized lymphoma to the family of existing Anaplastic Large Cell lymphomas. Current estimates of the lifetime risk of the disease in women with textured breast implants range from 1:1,000 to 1:30,000. The mean interval from implant placement to diagnosis is 10.7 ± 4.6 years and the most common clinical symptom at presentation is breast swelling. A high level of clinical suspicion is recommended in patients presenting with breast symptoms and/or peri-implant fluid collection occurring more than 1 year after breast implant placement. Ultrasound is the imaging modality of choice, with a high sensitivity for peri-implant fluid and a high specificity for peri-implant mass. When ultrasound is inconclusive, breast MRI is indicated. As of today, all confirmed cases have tested positive for CD30 immunohistochemistry and the disease has shown to have an excellent prognosis when it is diagnosed earlier (localized disease), and when complete surgery, consisting of explantation, capsulectomy, and removal of any associated capsule mass, is performed. This overview summarizes the available epidemiological and clinical data of Breast Implant-Associated Anaplastic Large Cell lymphoma, with an emphasis on imaging features.

To evaluate the diagnostic accuracy of breast MRI in identifying lesions requiring excision for patients with suspicious nipple discharge but normal mammograms and ultrasounds. Between September 2013 and May 2019, 106 female participants (mean age 57.9 years) were consecutively included in this prospective multicenter study; 102 were retained for analysis. MRI was considered negative in the absence of suspicious enhancement and positive in cases of ipsilateral abnormal enhancement (BI-RADS 3 to 5). Final diagnoses were based on histological findings of surgical or percutaneous biopsies or at 1-year follow-up. We considered all lesions requiring excision found on pathology (papilloma, atypia, nipple adenomatosis, or cancer) as positive results. We considered spontaneous resolution of the discharge at 1 year as a negative result. MRI showed ipsilateral abnormal enhancement in 54 patients (53%) revealing 46 lesions requiring excision (31 benign papillomas, 5 papillomas with atypia, 2 nipple adenomatosis, and 8 cancers) and 8 benign lesions not requiring excision. No suspicious enhancement was found in the remaining 48 participants (47%). Forty-two were followed up at 1 year with spontaneous resolution of the discharge and six underwent surgery (revealing 2 benign papillomas). MRI diagnostic accuracy for the detection of a lesion requiring excision was as follows: sensitivity 96%, specificity 85%, positive predictive value 85%, and negative predictive value 96%. In patients with suspicious nipple discharge and normal mammogram and ultrasound, MRI demonstrates excellent performance to identify lesions for which excision is required. Normal MRI indicates it is safe to propose follow-up only management, thus avoiding unnecessary duct excision. ClinicalTrials.gov NCT02819362 • Breast MRI can be useful for the management of patients with suspicious nipple discharge and negative mammogram and ultrasound. • MRI detected a lesion requiring excision in 46 participants (45%) with unexplained discharge. • If breast MRI is negative, follow-up is a safe alternative for these patients.

Breast dynamic contrast-enhanced MRI (DCE-MRI) is the most sensitive imaging modality for the detection of breast cancer. Screening MRI is currently performed predominantly in patients at high risk for breast cancer, but it could be of benefit in patients at intermediate risk for breast cancer and patients with dense breasts. Decreasing scan time and image interpretation time could increase cost-effectiveness, making screening MRI accessible to a larger group of patients. Abbreviated breast MRI (Ab-MRI) reduces scan time by decreasing the number of sequences obtained, but as multiple delayed contrast enhanced sequences are not obtained, no kinetic information is available. Ultrafast techniques rapidly acquire multiple sequences during the first minute of gadolinium contrast injection and provide information about both lesion morphology and vascular kinetics. Diffusion-weighted imaging is a noncontrast MRI technique with the potential to detect mammographically occult cancers. This review article aims to discuss the current indications of breast MRI as a screening tool, examine the standard breast DCE-MRI technique, and explore alternate screening MRI protocols, including Ab-MRI, ultrafast MRI, and noncontrast diffusion-weighted MRI, which can decrease scan time and interpretation time.

Aims The aim of the study is to evaluate the characteristic imaging features of breast cancer on mammogram, ultrasound, and magnetic resonance imaging (MRI) in women less than 40 years of age and to assess the degree of correlation between clinico-radio-pathological features and biological behavior.Methods and Materials A prospective observational study on consecutive women under 40 years of age evaluated with ultrasound of breast, digital mammogram, or contrast-enhanced breast MRI, diagnosed with breast cancer on histopathology and molecular analysis done at our center between January and December 2019 were included. Patient demographics, clinical presentation, family history, BRCA mutation status, imaging, pathological findings, and molecular status were determined.Results Out of 2,470 women diagnosed with breast cancer, 354 (14.3%) were less than 40 years of age who were included in this study. Mammography showed positive findings in 85%, ultrasonography in 94.3%, and MRI in 96.4% of women. Majority of the women (69.6%) presented in the late stage (Stage III and IV) with high-grade carcinoma in 39.5% and triple-negative breast cancer (TNBC) in 45.7%. Tumors with human epidermal growth factor-2neu expression were associated with the presence of microcalcifications (p-value = 0.006), and TNBC with circumscribed margins or BI-RADS 3/4a category on imaging (p-value = 0.007) and high-grade invasive carcinoma compared with others (p-value Conclusion The incidence of breast cancer in Indian women less than 40 years of age is relatively high as compared with the West. The detection of breast cancer in young women remains challenging due to dense breast tissue, lower incidence rate, and lack of regular breast screening. While ultrasound is the recommended imaging method for evaluation of breast under the age of 40 years, we found a better characterization of lesions and higher cancer detection rates when they were also evaluated with mammography and MRI.

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. (C) RSNA, 2021

Despite the breast volume being an essential metric component of any aesthetic or reconstructive breast surgery, up to date, there has been no accepted measurement technique that is globally accepted by breast surgeons. Appropriate measurement might lead to decrease of the reoperation rates. We introduced a novel technique that provides simply accurate volume measurement. Thirty patients with breast cancer who were scheduled for modified radical mastectomy were included in the study. Preoperative breast volume measurement using the novel device and breast MRI studies was done for all patients; meanwhile, the gold standard technique (d irect water displacement measurement of mastectomy specimen) was used to measure the volume of breast specimen following mastectomy. There were strongly positive correlations between the device and gold standard technique (r = 0.957) in 23 patients, and (r = 0.997) in 30 patients when MRI was compared to gold standard measurements. In group 1 (breast volume < 500), there is a strong correlation between the device and gold standard (r = 0.914) and for the MRI and gold standard (r = 0.965). In group 2 (500–1000), there was also a strong correlation between the device and gold standard (r = 0.986) and for the MRI and gold standard (r = 0.989) as well. The novel device had been proven to be cost-efficient, simple, reproducible technique with minimal learning curve. It provides reliably comparable results to gold standard techniques and MRI measurement in breast volumes up to 1000 cc. It utilized simple material and basic principles that can be easily used in most settings. Level of evidence: Level IV, diagnostic study.

Objective: The purpose of this study was to perform a systematic review and meta-analysis to determine the diagnostic performance of current noninvasive imaging modalities for assessment of axillary response after neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer patients. Summary of Background Data: NST can lead to downstaging of axillary lymph node disease. Imaging can potentially provide information about the axillary response to NST and, consequently, tailor the surgical management. Methods: PubMed and Embase were searched for studies that compared noninvasive imaging after NST with axillary surgery outcome to identify axillary response in patients with initial pathologically proven axillary lymph node metastasis. Two reviewers independently screened the studies and extracted the data. A meta-analysis was performed by computing the pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: Thirteen studies describing 2380 patients were included for final analysis. Of these patients, 1322 had undergone axillary ultrasound, 849 breast MRI, and 209 whole-body F-18-FDG PET-CT. The overall axillary pathologic complete response rate was 39.5% (941/2380). For axillary ultrasound, the pooled sensitivity, specificity, PPV, and NPV were 65%, 69%, 77%, 50%, respectively. For breast MRI, the pooled sensitivity, specificity, PPV, and NPV were 60%, 76%, 78%, 58%, respectively. For whole-body F-18-FDG PET-CT, the pooled sensitivity, specificity, PPV, and NPV were 38%, 86%, 78%, 49%, respectively. Conclusions: The diagnostic performance of current noninvasive imaging modalities is limited to accurately assess axillary response after NST in clinically node-positive breast cancer patients.

To determine the positive predictive value (PPV) of magnetic resonance imaging (MRI)-guided breast biopsy stratified by body mass index (BMI). Secondary endpoints include evaluation of indications for breast MRI and identification of factors associated with malignant biopsy. We retrospectively analyzed results of MRI-guided breast biopsies in a consecutive cohort of women at a single institution between 2014 and 2019. The PPV was compared between BMI subgroups and the overall group by the one-sample z-test. Factors associated with malignant biopsy were analyzed using multivariate regression analysis. Among 427 MRI-guided breast biopsies, the PPV was significantly higher in patients with a BMI ≥ 35 compared to BMI

Neoadjuvant therapy in breast cancer can downstage axillary lymph nodes and reduce extent of axillary surgery. As such, accurate determination of nodal status after neoadjuvant therapy and before surgery impacts surgical management. There are scarce data on the diagnostic accuracy of breast magnetic resonance imaging (MRI) for nodal evaluation after neoadjuvant therapy in patients with invasive lobular carcinoma (ILC), a diffusely growing tumor type. We retrospectively analyzed patients with stage 1–3 ILC who underwent pre-operative breast MRI after either neoadjuvant chemotherapy or endocrine therapy at our institution between 2006 and 2019. Two breast radiologists reviewed MRIs and evaluated axillary nodes for suspicious features. All patients underwent either sentinel node biopsy or axillary dissection. We evaluated sensitivity, specificity, negative and positive predictive values, and overall accuracy of the post-treatment breast MRI in predicting pathologic nodal status. Of 79 patients, 58.2% received neoadjuvant chemotherapy and 41.8% neoadjuvant endocrine therapy. The sensitivity and negative predictive value of MRI were significantly higher in the neoadjuvant endocrine therapy cohort than in the neoadjuvant chemotherapy cohort (66.7 vs. 37.9%, p = 0.012 and 70.6 vs. 40%, p = 0.007, respectively), while overall accuracy was similar. Upstaging from clinically node negative to pathologically node positive occurred in 28.0 and 41.7%, respectively. In clinically node positive patients, those with an abnormal post-treatment MRI had a significantly higher proportion of patients with ≥4 positive nodes on pathology compared to those with a normal MRI (61.1 versus 16.7%, p = 0.034). Overall, accuracy of breast MRI for predicting nodal status after neoadjuvant therapy in ILC was low in both chemotherapy and endocrine therapy cohorts. However, post-treatment breast MRI may help identify patients with a high burden of nodal disease (≥4 positive nodes), which could impact pre-operative systemic therapy decisions. Further studies are needed to assess other imaging modalities to evaluate for nodal disease following neoadjuvant therapy and to improve clinical staging in patients with ILC.

Background: The most common female cancer in Egyptis breast cancer as the age-specific incidence rates show aprogressive increase after the age of 30 years, to reach a sharppeak at the age group of 60-64 years. Many early breastcarcinomas are asymptomatic. In an effort to overcome thelimitations of mammography and ultrasonography, MagneticResonance Imaging (MRI) has been explored as a modalityfor detecting breast cancer in women at high risk and inyounger women. Dynamic Contrast-Enhanced MRI (DCE-MRI) has high accuracy for the detection of breast cancer,allowing detection of malignancy that is occult on physicalexamination, mammography, and sonography.Aim of Study: Was to assess the ability of contrast enhancedMRI in differentiation between benign and malignant breastlesions.Patients and Methods: Fifty female patients were includedtheir age ranged from 18-70 years.Results: Accuracy of DCE-MRI in differentiation betweenbenign and malignant lesions were 90% with sensitivity of100% & specificity of 70.6%.Conclusion: We concluded that DCE-MRI can be usedas diagnostic tool in detection of breast cancer.

OBJECTIVE. The purpose of this article was to determine the frequency and outcomes of new suspicious findings on breast MRI after initiation of neoadjuvant therapy. MATERIALS AND METHODS. A retrosp...

The utility of pre-operative MRI in patients with newly diagnosed invasive breast cancer remains a topic of debate. Those who advocate for pre-treatment imaging contend that MRI may detect additional disease not otherwise appreciated on conventional imaging and may provide more accurate staging information to guide treatment. Additionally, it has been proposed that MRI can be utilized to assess extent of residual disease in patients undergoing neoadjuvant chemotherapy. Conversely, those in opposition maintain that routine pre-operative MRI subjects patients to unnecessary ipsilateral mastectomies and prophylactic contralateral mastectomies with no difference in oncologic outcome. When stratified based on tumor biology and patient characteristics, the data suggests that pre-treatment MRI may be advantageous in certain subsets when compared to the general cohort of breast cancer patients. This review recapitulates the current literature on the impact of breast MRI on the surgical management and outcomes of newly diagnosed breast cancer.

Purpose Pathological complete response (pCR) predicts improved survival in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, the prognosis of patients with non-pCR remains unclear. The aim of this study was to evaluate the effect of radiological response pattern on breast cancer patients’ outcome. Method A total of 396 breast cancer patients who underwent neoadjuvant chemotherapy between 2010-2017 at Seoul St. Mary’s Hospital were retrospectively reviewed. Among them, patients who underwent 4-6 cycles of neoadjuvant chemotherapy and underwent response evaluation every 2 cycles using breast MRI were included for analysis. Early and late response ratio was calculated from breast MR images using the longest diameter of the main tumor. Early response ratio was calculated as post-2 cycle NAC / pre-NAC ratio. Late response ratio was calculated as post-4 cycle NC / post-2 cycle NAC ratio. Radiological response pattern was divided into three groups; fast-slow responder meaning early response ratio > late response ratio + 20%, slow-fast responder meaning late response ratio > early response ratio + 20% and constant responder meaning the difference between initial response ratio and later response ratio is lower than 20%. Survival analysis was done using the Kaplan-Meier method and multivariate analysis by Cox regression. Disease-free survival (DFS) was defined as locoregional recurrence, contralateral breast recurrence and distant metastasis. Result A total of 177 patients were included for analysis. Among them 19 (10.7%) patients were pCR, 122 (68.9%) patients had partial response, 29 (16.4%) patients had stable disease and 7 (4.0%) patients had progressive disease. Median follow-up period was 50 months (range, 3-112 months). Radiological response pattern was significantly associated with disease-free survival in univariate analysis (p=0.042). Fast-slow responders had significantly worse disease-free survival (DFS) in univariate analysis compared to slow-fast responders and constant responders (p=0.042, 5-year DFS 67.6%, 88.3% 67.6%). Radiological response pattern continued to be statistically significant by multivariable analysis (p=0.037). Conclusion Our results showed that fast-slow responders have worse survival compared to constant or slow-fast responders. Radiological response patterns may be useful to more accurately assess prognosis, especially when considering adjuvant chemotherapy. Citation Format: Juneyoung Ahn, Tae-kyung Yoo, Pill Sun Paik, Min Kyung Cho, Chang Ik Yoon, Woo Chan Park. Radiological response pattern predicts disease-free survival in breast cancer patients undergoing neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS13-45.

Background: For women aged 40-49, Canadian guidelines recommend individualized-decision making (based on risk assessment, values, and preferences) rather than routine screening mammography (SM). In this age group, family physicians are the gatekeepers to access SM; however, studies indicate substantial variability in practice patterns. There are few population-based data regarding uptake and patient/provider determinants of SM in this age group. We describe the uptake and frequency of SM and identify patient and provider level associations with SM in Ontario women aged 40-49. We hypothesized that SM would vary by provider characteristics and women’s demographics, suggesting lack of guideline-concordant care. Methods: This population-based retrospective cohort study linked health administrative databases to form a cohort of all Ontario women aged 40-49 between April 1, 2009 to March 31, 2019. Mammograms were identified using Ontario Health Billing codes. In order to identify mammograms that were specifically for screening, women were excluded if they had any prior breast MRI, mammogram, cancer diagnosis, oncologist visit, or breast surgical procedure. Sub-cohorts were created to identify women who had (a) at least one SM (“screen cohort”) and (b) 3 or more SM (“routine screen cohort”). Following SM, women were censored from cohorts if they had any cancer diagnosis, breast surgical procedure, oncologist visit, or death; however, breast cancer related outcomes were tracked for 6 months following SM, regardless of whether a censoring event occurred. Patient and provider characteristics were extracted for women in each cohort. A multivariable regression model was used to identify predictors of routine SM. Results: Of 2 million eligible women, 743 274 (35.6%) received a mammogram, 532 782 (25.5%) received at least one SM, and 90 651 (4.3%) received routine SM (3 or more). Table 1 demonstrates cohort characteristics. There were 0.32 and 0.52 mammograms per woman per year in the screen and routine screen cohort respectively. Call-backs were similar for women after the first SM compared to the third SM (9.5% vs 9.3%); however, there were more biopsies (3.2% vs 1.8%) and breast cancers diagnosed (1.2% vs 0.45%) within six months of the first SM. Compared to the full cohort, women in the routine screen cohort were more likely to have a family physician at cohort entry, be in higher-income quintiles, receive annual health exams, and receive have pap smears (p Conclusions: Less than 5% of Ontario women 40-49 undergo routine SM. SM is associated with patient demographics related to higher socioeconomic status which could be related to higher risk of breast cancer and/or increased access to care. SM is also associated with some provider demographics which could be independent of breast cancer risk, suggesting lack of individualized risk assessment. Qualitative work is ongoing to explore this hypothesis. This information can inform guideline implementation strategies. Table 1: Patient and Provider Characteristics of ScreeningCharacteristicpercent (%) unless otherwise notedAll Women 40-49Screen Cohort (1 or more SM)Routine Screen Cohort (3 or more SM)Patient CharacteristicsAge at Cohort entryMean (median)42.5 (40)42.8 (42)41.7 (41)Age at Cohort exitMean (median)47.3 (50)48.5 (50)49.1 (50)Family Physician at Cohort entry90.0 %92.3%94.8%Income – top quintile20.7%22.3%24%Rurality Category – most urban76.3%79.0%81.2%Birth Location – Canada74.4%72.2%71.6%Annual Health Exams: at least one51.1%72.1%75.3%Pap Smear: at least one68.4%86.6%92.9%Provider CharacteristicsFemale44.8%47.2%52.1%Canadian Graduates70.3%70.3%72.1%Fee for Service model48.0%55.0%58.8% Citation Format: Michelle B Nadler, Alex Marchand-Austin, Peter C. Austin, Alexandra Desnoyers, Brooke E. Wilson, Aisha Lofters, Noah Ivers, Eitan Amir. Patient and provider determinants of breast cancer screening among Ontario women age 40-49: A population based retrospective cohort study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-17.

Breast cancer has become the first malignant tumor in women. Early detection and early treatment are the key to improve the prognosis of breast cancer patients. The key to the screening and diagnosis of breast cancer lies in the qualitative differential diagnosis of breast nodules. With the rapid development of MRI technology, especially the application of high field strength and ultra-high field strength, the role of breast MRI is increasingly prominent. MRI has the advantages of safety, no ionizing radiation, high resolution of soft tissue, high sensitivity and specificity for the diagnosis of early breast cancer. Multimodal imaging based on reinforcement learning and iron carbon nanoparticles plays an important role in the diagnosis of breast nodules. This paper first discusses the application of iron carbon nanoparticles and breast MRI multimodal imaging technology in tumor treatment, and then studies the application of iron carbon nanoparticles mediated multimodal imaging in the diagnosis of breast nodules through experimental methods. The experimental results show that multimodal imaging has a good effect in the diagnosis of breast nodules, which is helpful for the prevention and treatment of breast nodules.

Context.— Dynamic, contrast-enhanced magnetic resonance imaging (MRI) is a highly sensitive imaging modality used for screening and diagnostic purposes. Nonmass enhancement (NME) is commonly seen on MRI of the breast. However, the pathologic correlates of NME have not been extensively explored. Consequently, concordance between MRI and pathologic findings in such cases may be uncertain and this uncertainty may cause the need for additional procedures. Objective.— To examine the histologic alterations that correspond to NME on MRI. Design.— We performed a retrospective search for women who underwent breast MRI between March 2014 and December 2016 and identified 130 NME lesions resulting in biopsy. The MRI findings and pathology slides for all cases were reviewed. The follow-up findings on any subsequent excisions were also noted. Results.— Among the 130 cases, the core needle biopsy showed 1 or more benign lesions without atypia in 80 cases (62%), atypical lesions in 21 (16%), ductal carcinoma in situ in 22 (17%), and invasive carcinoma in 7 (5%). Review of the imaging features demonstrated some statistically significant differences in lesions that corresponded to malignant lesions as compared with benign alterations, including homogeneous or clumped internal enhancement, type 3 kinetics, and T2 dark signal; however, there was considerable overlap of features between benign and malignant lesions overall. Of 130 cases, 54 (41.5%) underwent subsequent excision with only 6 cases showing a worse lesion on excision. Conclusions.— This study illustrates that NME can be associated with benign, atypical, and/or malignant pathology and biopsy remains indicated given the overlap of radiologic features.

We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI). Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer. Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (≤ 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis. In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI. • Subcentimeter tumors and presence of calcifications in the tumor are associated with false-negative diffusion-weighted imaging results in the diagnosis of invasive breast cancer. • A higher degree of background diffusion signal may lead to false-negative interpretation of diffusion-weighted imaging in patients with invasive breast cancer.

Introduction: Due to the increasing use of dynamic breast MRI and the limited availability of MR-guided interventions, MRI-detected lesions usually undergo a second-look ultrasound (SLUS). We investigated the safety of a negative SLUS and a benign SLUS correlate in excluding malignant and high-risk lesions (B3) and evaluated criteria for the rate of detection on SLUS. Methods: In the retrospective analysis, all breast MRIs performed between 2011 and 2013 were screened for newly detected lesions. We analyzed the SLUS detection rate dependent on breast density, mass character, lesion size, and histology. We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of a negative and benign SLUS for malignant lesions (B5) and lesions requiring surgical excision (including high-risk and B5 lesions). Results: We successfully correlated 110 of 397 lesions. The detection rate was significantly higher for mass than for non-mass lesions and correlated with lesion size for mass lesions only. Lesions without/with a benign SLUS correlate were more frequently benign (including B3) or required no further procedure (B2). The sensitivity of SLUS in the detection of B3 and B5 lesions was 58%, and 73% in the detection of B5 lesions. The NPV of a negative or benign SLUS for B3 and B5 lesions was 89%, and 96% for B5 lesions. Discussion: SLUS is a safe diagnostic tool for the management of MRI-detected lesions and can spare patients from undergoing invasive procedures.