A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance.

PURPOSE: HER3, a member of the EGFR receptor family, plays a central role in driving oncogenic cell proliferation in breast cancer. Novel HER3 therapeutics are showing promising results while recently developed HER3 PET imaging modalities aid in predicting and assessing early treatment response. However, baseline HER3 expression, as well as changes in expression while on neoadjuvant therapy, have not been well-characterized. We conducted a prospective clinical study, pre- and post-neoadjuvant/systemic therapy, in patients with newly diagnosed breast cancer to determine HER3 expression, and to identify possible resistance mechanisms maintained through the HER3 receptor. EXPERIMENTAL DESIGN: The study was conducted between May 25, 2018 and October 12, 2019. Thirty-four patients with newly diagnosed breast cancer of any subtype (ER ± , PR ± , HER2 ±) were enrolled in the study. Two core biopsy specimens were obtained from each patient at the time of diagnosis. Four patients underwent a second research biopsy following initiation of neoadjuvant/systemic therapy or systemic therapy which we define as neoadjuvant therapy. Molecular characterization of HER3 and downstream signaling nodes of the PI3K/AKT and MAPK pathways pre- and post-initiation of therapy was performed. Transcriptional validation of finings was performed in an external dataset (GSE122630). RESULTS: Variable baseline HER3 expression was found in newly diagnosed breast cancer and correlated positively with pAKT across subtypes (r = 0.45). In patients receiving neoadjuvant/systemic therapy, changes in HER3 expression were variable. In a hormone receptor-positive (ER +/PR +/HER2-) patient, there was a statistically significant increase in HER3 expression post neoadjuvant therapy, while there was no significant change in HER3 expression in a ER +/PR +/HER2+ patient. However, both of these patients showed increased downstream signaling in the PI3K/AKT pathway. One subject with ER +/PR -/HER2- breast cancer and another subject with ER +/PR +/HER2 + breast cancer showed decreased HER3 expression. Transcriptomic findings, revealed an immune suppressive environment in patients with decreased HER3 expression post therapy. CONCLUSION: This study demonstrates variable HER3 expression across breast cancer subtypes. HER3 expression can be assessed early, post-neoadjuvant therapy, providing valuable insight into cancer biology and potentially serving as a prognostic biomarker. Clinical translation of neoadjuvant therapy assessment can be achieved using HER3 PET imaging, offering real-time information on tumor biology and guiding personalized treatment for breast cancer patients.

Feasibility of risk assessment for breast cancer molecular subtypes.

PURPOSE: Few breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination. METHODS: Among 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype. RESULTS: There were 3,073 ER/PR+ HER2 - , 340 ER/PR +HER2 + , 126 ER/PR-ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR-HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI. CONCLUSION: Our study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. Purpose To compare the diagnostic accuracy of a mammogram-based deep learning (DL) risk assessment model to that of traditional breast cancer risk models in patients who underwent supplemental screening with MRI. Materials and Methods This retrospective study included consecutive patients undergoing breast cancer screening MRI from September 2017 to September 2020 at four facilities. Risk was assessed using the Tyrer-Cuzick (TC) and National Cancer Institute Breast Cancer Risk Assessment Tool (BCRAT) 5-year and lifetime models as well as a DL 5-year model that generated a risk score based on the most recent screening mammogram. A risk score of 1.67% or higher defined increased risk for traditional 5-year models, a risk score of 20% or higher defined high risk for traditional lifetime models, and absolute scores of 2.3 or higher and 6.6 or higher defined increased and high risk, respectively, for the DL model. Model accuracy metrics including cancer detection rate (CDR) and positive predictive values (PPVs) (PPV of abnormal findings at screening [PPV1], PPV of biopsies recommended [PPV2], and PPV of biopsies performed [PPV3]) were compared using logistic regression models. Results This study included 2168 women who underwent 4247 high-risk screening MRI examinations (median age, 54 years [IQR, 48-60 years]). CDR (per 1000 examinations) was higher in patients at high risk according to the DL model (20.6 [95% CI: 11.8, 35.6]) than according to the TC (6.0 [95% CI: 2.9, 12.3]; P < .01) and BCRAT (6.8 [95% CI: 2.9, 15.8]; P = .04) lifetime models. PPV1, PPV2, and PPV3 were higher in patients identified as high risk by the DL model (PPV1, 14.6%; PPV2, 32.4%; PPV3, 36.4%) than those identified as high risk with the TC (PPV1, 5.0%; PPV2, 12.7%; PPV3, 13.5%; P value range, .02-.03) and BCRAT (PPV1, 5.5%; PPV2, 11.1%; PPV3, 12.5%; P value range, .02-.05) lifetime models. Conclusion Patients identified as high risk by a mammogram-based DL risk assessment model showed higher CDR at breast screening MRI than patients identified as high risk with traditional risk models. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bae in this issue.

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.

Breast cancer polygenic risk scores are associated with short-term risk of poor prognosis breast cancer.

PURPOSE: Polygenic risk scores (PRS) for breast cancer may help guide screening decisions. However, few studies have examined whether PRS are associated with risk of short-term or poor prognosis breast cancers. The study purpose was to evaluate the association of the 313 SNP breast cancer PRS with 2-year risk of poor prognosis breast cancer. METHODS: We evaluated the association of breast cancer PRS with breast cancer overall, ER + and ER- breast cancer, and poor prognosis breast cancer diagnosed within 2 years of a negative mammogram among a cohort of 3657 women using logistic regression adjusted for age, breast density, race/ethnicity, year of screening, and genetic ancestry principal components. Breast cancers were considered poor prognosis if they were metastatic, positive lymph nodes, ER/PR + HER2- and > 2 cm, ER/PR/HER2-, or HER2 + and > 1 cm. RESULTS: Of the 308 breast cancers, 137 (44%) were poor prognosis. The overall breast cancer PRS was significantly associated with breast cancer diagnosis within 2 years (OR 1.39, 95% CI 1.23-1.57, p < 0.001). The breast cancer PRS was also associated specifically with diagnosis of poor prognosis disease (OR 1.24, 95% CI 1.03-1.49, p = 0.018), but was more strongly associated with good prognosis cancer (OR 1.52 95% CI 1.29-1.80 p = 3.60 × 10-7) The ER + PRS was significantly associated with ER/PR + breast cancer (OR 1.41, 95% CI 1.24-1.61, p < 0.001) and the ER- PRS was significantly associated with ER- breast cancer (OR 1.48, 95% CI 1.08-2.02, p = 0.015). CONCLUSION: Breast cancer PRS was independently and significantly associated with diagnosis of both breast cancer overall and poor prognosis breast cancer within 2 years of a negative mammogram, suggesting PRS may help guide decisions about screening intervals and supplemental screening.

Artificial Intelligence (AI) for Screening Mammography, From the AJR Special Series on AI Applications.

Artificial intelligence (AI) applications for screening mammography are being marketed for clinical use in the interpretative domains of lesion detection and diagnosis, triage, and breast density assessment and in the noninterpretive domains of breast cancer risk assessment, image quality control, image acquisition, and dose reduction. Evidence in support of these nascent applications, particularly for lesion detection and diagnosis, is largely based on multireader studies with cancer-enriched datasets rather than rigorous clinical evaluation aligned with the application's specific intended clinical use. This article reviews commercial AI algorithms for screening mammography that are currently available for clinical practice, their use, and evidence supporting their performance. Clinical implementation considerations, such as workflow integration, governance, and ethical issues, are also described. In addition, the future of AI for screening mammography is discussed, including the development of interpretive and noninterpretive AI applications and strategic priorities for research and development.

Disparities in Same-Day Diagnostic Imaging in Breast Cancer Screening: Impact of an Immediate-Read Screening Mammography Program Implemented During the COVID-19 Pandemic.

BACKGROUND. The need for second visits between screening mammography and diagnostic imaging contributes to disparities in the time to breast cancer diagnosis. During the COVID-19 pandemic, an immediate-read screening mammography program was implemented to reduce patient visits and decrease time to diagnostic imaging. OBJECTIVE. The purpose of this study was to measure the impact of an immediate-read screening program with focus on disparities in same-day diagnostic imaging after abnormal findings are made at screening mammography. METHODS. In May 2020, an immediate-read screening program was implemented whereby a dedicated breast imaging radiologist interpreted all screening mammograms in real time; patients received results before discharge; and efforts were made to perform any recommended diagnostic imaging during the visit (performed by different radiologists). Screening mammographic examinations performed from June 1, 2019, through October 31, 2019 (preimplementation period), and from June 1, 2020, through October 31, 2020 (postimplementation period), were retrospectively identified. Patient characteristics were recorded from the electronic medical record. Multivariable logistic regression models incorporating patient age, race and ethnicity, language, and insurance type were estimated to identify factors associated with same-day diagnostic imaging. Screening metrics were compared between periods. RESULTS. A total of 8222 preimplementation and 7235 postimplementation screening examinations were included; 521 patients had abnormal screening findings before implementation, and 359 after implementation. Before implementation, 14.8% of patients underwent same-day diagnostic imaging after abnormal screening mammograms. This percentage increased to 60.7% after implementation. Before implementation, patients who identified their race as other than White had significantly lower odds than patients who identified their race as White of undergoing same-day diagnostic imaging after receiving abnormal screening results (adjusted odds ratio, 0.30; 95% CI, 0.10-0.86; p = .03). After implementation, the odds of same-day diagnostic imaging were not significantly different between patients of other races and White patients (adjusted odds ratio, 0.92; 95% CI, 0.50-1.71; p = .80). After implementation, there was no significant difference in race and ethnicity between patients who underwent and those who did not undergo same-day diagnostic imaging after receiving abnormal results of screening mammography (p > .05). The rate of abnormal interpretation was significantly lower after than it was before implementation (5.0% vs 6.3%; p < .001). Cancer detection rate and PPV1 (PPV based on positive findings at screening examination) were not significantly different before and after implementation (p > .05). CONCLUSION. Implementation of the immediate-read screening mammography program reduced prior racial and ethnic disparities in same-day diagnostic imaging after abnormal screening mammograms. CLINICAL IMPACT. An immediate-read screening program provides a new paradigm for improved screening mammography workflow that allows more rapid diagnostic workup with reduced disparities in care.

Screening Mammography Recovery After COVID-19 Pandemic Facility Closures: Associations of Facility Access and Racial and Ethnic Screening Disparities.

BACKGROUND. Screening mammography facilities closed during the COVID-19 pandemic in spring 2020. Recovery of screening volumes has varied across patient subgroups and facilities. OBJECTIVE. We compared screening mammography volumes and patient and facility characteristics between periods before COVID-19 and early and later postclosure recovery periods. METHODS. This retrospective study included screening mammograms performed in the same 2-month period (May 26-July 26) in 2019 (pre-COVID-19), 2020 (early recovery), and 2021 (late recovery after targeted interventions to expand access) and across multiple facility types (urban, suburban, community health center). Suburban sites had highest proportion of White patients and the greatest scheduling flexibility and expanded appointments during initial reopening. Findings were compared across years. RESULTS. For White patients, volumes decreased 36.6% from 6550 in 2019 (4384 in 2020) and then increased 61.0% to 6579 in 2021; for patients with races other than White, volumes decreased 53.9% from 1321 in 2019 (609 in 2020) and then increased 136.8% to 1442 in 2021. The percentage of mammograms in patients with races other than White was 16.8% in 2019, 12.2% in 2020, and 18.0% in 2021. The proportion performed at the urban center was 55.3% in 2019, 42.2% in 2020, and 45.9% in 2021; the proportion at suburban sites was 34.0% in 2019, 49.2% in 2020, and 43.5% in 2021. Pre-COVID-19 volumes were reached by the sixth week after reopening for suburban sites but were not reached during early recovery for the other sites. The proportion that were performed on Saturday for suburban sites was similar across periods, whereas the proportion performed on Saturday for the urban site was 7.6% in 2019, 5.3% in 2020, and 8.8% in 2021; the community health center did not offer Saturday appointments during recovery. CONCLUSION. After reopening, screening shifted from urban to suburban settings, with a disproportionate screening decrease in patients with races other than White. Initial delayed access at facilities serving underserved populations exacerbated disparities. Interventions to expand access resulted in late recovery volumes exceeding prepandemic volumes in patients with races other than White. CLINICAL IMPACT. Interventions to support equitable access across facilities serving diverse patient populations may mitigate potential widening disparities in breast cancer diagnosis during the pandemic.

Risk factors for an advanced breast cancer diagnosis within 2 years of a negative mammogram.

BACKGROUND: Identifying women at risk for advanced interval cancers would allow better targeting of mammography and supplemental screening. The authors assessed risk factors for advanced breast cancer within 2 years of a negative mammogram. METHODS: The authors included 293,520 negative mammograms performed from 2006 to 2015 among 74,736 women. Breast cancers were defined as advanced if they were >2 cm, were >1 cm and triple-negative or human epidermal growth factor receptor 2-positive, had positive lymph nodes, or were metastatic. Cox proportional hazards modeling was used to evaluate associations of age, breast density, menopause, mammogram type, prior breast biopsy, body mass index (BMI), and a family history of breast cancer with a cancer diagnosis within 2 years of a negative mammogram. Models were stratified by year since a negative mammogram. RESULTS: Among 1345 breast cancers, 357 were advanced (26.5%), and 988 (73.5%) were at an early stage. Breast density, prior biopsy, and family history were associated with an increased risk of both advanced and early-stage cancers. Overweight and obese women had a 40% higher risk of early-stage cancer only in year 2 (overweight hazard ratio [HR], 1.41; 95% confidence interval [CI], 1.19-1.67; P < .001; obese HR, 1.41; 95% CI, 1.17-1.70; P < .001). Obese women had a 90% increased risk of advanced cancer in year 1 (HR, 1.90; 95% CI, 1.14-3.18; P = .014), and both overweight and obese women had a 40% or greater increased risk in year 2 (overweight HR, 1.55; 95% CI, 1.14-2.07; P = .005; obese HR, 1.42; 95% CI, 1.00-2.01; P = .051). CONCLUSIONS: A higher BMI was associated with an advanced breast cancer diagnosis within 2 years of a negative mammogram. These results have important implications for risk assessment, screening intervals, and use of supplemental screening.

Potential of using mammography screening appointments to identify high-risk women: cross sectional survey results from the national health interview survey.

PURPOSE: Mammography screening encounters may represent ideal opportunities to identify high-risk women for risk-based screening. During mammography appointments, radiology practices evaluate breast density and ascertain known breast cancer risk factors. Our purpose was to evaluate the potential for mammographic screening encounters to identify high-risk women by estimating the (1) proportion of high-risk women who report that they have undergone mammographic screening and the (2) proportion of high-risk women who receive recommendations for breast MRI screening. METHODS: Women ages 30-85 without breast cancer histories were included from the 2015 National Health Interview Survey, a nationally representative cross-sectional household survey (response rate 80%). Breast Cancer Risk Assessment Tool was used to determine high-risk (lifetime risk>20%). Among high-risk women, primary outcome was proportion reporting mammography screening, secondary outcome was receipt of a breast MRI recommendation after recent mammogram, accounting for complex survey design. RESULTS: 14,958 women were included. 1.0% were high-risk of whom: 91.9% ever had a mammogram, 68.0% had a mammogram within the last year, 81.5% had a mammogram within the last 2 years. 6.4% were recommended to undergo breast MRI. Among high-risk women, women with dense breast tissue were more likely (OR 496.0, 95%CI 52.6,4674.0) and older women were less likely (OR 0.91, 95%CI 0.84,0.99) to receive recommendations for breast MRI. CONCLUSIONS: Among high-risk women, 92% reported undergoing at least one mammogram in their lives. 94% did not receive recommendations for breast MRI screening and 32% did not have a mammogram within the last year. To identify high-risk women, breast imaging centers should consider determining lifetime breast cancer risk during mammography screening visits.

Imaging Surveillance of Breast Cancer Survivors with Digital Mammography versus Digital Breast Tomosynthesis.

Background Among breast cancer survivors, detecting a breast cancer when it is asymptomatic (rather than symptomatic) improves survival; thus, imaging surveillance in these patients is warranted. Digital breast tomosynthesis (DBT) is used for screening, but data on DBT for surveillance in this high-risk population are limited. Purpose To determine whether DBT leads to improved screening performance metrics when compared with two-dimensional digital mammography among breast cancer survivors. Materials and Methods In this study, screening mammograms obtained in breast cancer survivors before and after DBT implementation were retrospectively reviewed (March 2008-February 2011 for the digital mammography group; January 2013-December 2017 for the DBT group). Mammograms were interpreted by breast imaging radiologists with the assistance of computer-aided detection. Performance metrics and tumor characteristics between the groups were compared using multivariable logistic regression models. Results The digital mammography and DBT groups were composed of 9019 and 22 887 mammographic examinations, respectively, in 8170 women (mean age, 62 years ± 12 [standard deviation]). In the DBT group, the abnormal interpretation rate was lower (5.8% [1331 of 22 887 examinations] vs 6.2% [563 of 9019 examinations]; odds ratio [OR], 0.80; 95% CI: 0.71, 0.91; P = .001) and specificity was higher (95.0% [21 502 of 22 644 examinations] vs 94.7% [8424 of 8891 examinations]; OR, 1.23; 95% CI: 1.07, 1.41; P = .003) than in the digital mammography group. The cancer detection rates did not differ (8.3 per 1000 examinations with DBT vs 10.6 with digital mammography; OR, 0.76; 95% CI: 0.57, 1.02; P = .07). The proportions of screening-detected invasive cancers, versus in situ cancers, were similar (74% [140 of 189 cancers] in the DBT group vs 72% [69 of 96 cancers] in the digital mammography group; P = .69). Of 86 interval cancers, 58% (50 of 86 cancers) manifested with symptoms, and 33% (28 of 86 cancers) were detected at screening MRI. Conclusion Among breast cancer survivors, screening with digital breast tomosynthesis led to fewer false-positive results and higher specificity but did not affect cancer detection. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Hooley and Butler in this issue.

Preoperative Breast MRI for Newly Diagnosed Ductal Carcinoma in Situ: Imaging Features and Performance in a Multicenter Setting (ECOG-ACRIN E4112 Trial).

Background There are limited data from clinical trials describing preoperative MRI features and performance in the evaluation of mammographically detected ductal carcinoma in situ (DCIS). Purpose To report qualitative MRI features of DCIS, MRI performance in the identification of additional disease, and associations of imaging features with pathologic, genomic, and surgical outcomes from the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network (ECOG-ACRIN) E4112 trial. Materials and Methods Secondary analyses of a multicenter prospective clinical trial from the ECOG-ACRIN Cancer Research Group included women with DCIS diagnosed with conventional imaging techniques (mammography and US), confirmed via core-needle biopsy (CNB), and enrolled between March 2015 and April 2016 who were candidates for wide local excision (WLE) based on conventional imaging and clinical examination results. DCIS MRI features and pathologic features from CNB and excision were recorded. Each woman without invasive upgrade of the index DCIS at WLE received a 12-gene DCIS score. MRI performance metrics were calculated. Associations of imaging features with invasive upgrade, dichotomized DCIS score (<39 vs ≥39), and single WLE success were estimated in uni- and multivariable analyses. Results Among 339 women (median age, 60 years; interquartile range, 51-66 years), most DCIS cases showed nonmass enhancement (NME) (195 of 339 [58%]) on MRI scans with larger median size than on mammograms (19 mm vs 12 mm; P < .001). Positive predictive value of MRI-prompted CNBs was 32% (21 of 66) (95% CI: 22, 44), yielding an additional cancer detection rate of 6.2% (21 of 339) (95% CI: 4.1, 9.3). MRI false-positive rate was 14.2% (45 of 318) (95% CI: 10.7, 18.4). No imaging features were associated with invasive upgrade or DCIS score (P = .05 to P = .95). Smaller size and focal NME distribution at MRI were linked to single WLE success (P < .001). Conclusion Preoperative MRI depicted ductal carcinoma in situ (DCIS) diagnosed with conventional imaging most commonly as nonmass enhancement, with larger median span than mammography, and additional cancer detection rate of 6.2%. MRI features of this subset of DCIS did not enable prediction of pathologic or genomic outcomes. Clinical trial registration no. NCT02352883 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kuhl in this issue. An earlier incorrect version of this article appeared online. This article was corrected on August 4, 2021.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.

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.

Mitigating the Impact of Coronavirus Disease (COVID-19) Vaccinations on Patients Undergoing Breast Imaging Examinations: A Pragmatic Approach.

Reports of patients with axillary adenopathy identified on breast imaging after coronavirus disease (COVID-19) vaccination are rising. We propose a pragmatic management approach based on clinical presentation, vaccination delivery, and imaging findings. In the settings of screening mammography, screening MRI, and diagnostic imaging workup of breast symptoms, with no imaging findings beyond unilateral axillary adenopathy ipsilateral to recent (within the past 6 weeks) vaccination, we report the adenopathy as benign with no further imaging indicated if no nodes are palpable 6 weeks after the last dose. For patients with palpable axillary adenopathy in the setting of ipsilateral recent vaccination, clinical follow-up of the axilla is recommended. In all these scenarios, axillary ultrasound is recommended if clinical concern persists 6 weeks after vaccination. In patients with a recent breast cancer diagnosis in the pre- or peritreatment setting, prompt recommended imaging is encouraged as well as vaccination (in the thigh or contralateral arm). Our recommendations align with the ACR BI-RADS Atlas and aim to reduce patient anxiety, provider burden, and costs of unnecessary evaluation of enlarged nodes in the setting of recent vaccinations and, also, to avoid further delays in vaccinations and breast cancer screening during the pandemic.

Shear-Wave Elastography of the Breast: Impact of Technical Image Quality Parameters on Diagnostic Accuracy.

OBJECTIVE. The purpose of this study is to determine the impact of shear-wave elastography (SWE) image quality parameters on the diagnostic performance of elasticity measurements in classifying breast lesions. MATERIALS AND METHODS. This retrospective study included 281 breast lesions that underwent SWE and ultrasound-guided biopsy performed between October 1, 2017, and August 31, 2018. Three readers who were blinded to pathologic outcomes independently scored the image quality of each SWE image (with low quality denoted by a score of 0 and high quality indicated by a score of 1) on the basis of five parameters: B-mode visualization of the lesion on a dual-panel display, SWE red pattern (denoting high stiffness) in the near field of the FOV, appearance of the surrounding tissue, FOV placement, and ROI placement for the maximum (Emax), minimum (Emin), mean (Emean), and SD (ESD) of Young modulus elasticity measurements. Using ROC analysis, we compared the performance of Emax, Emean, and ESD in diagnosing malignancy on low- and high-quality images on the basis of consensus (i.e., majority) scores for each individual quality parameter as well as two models combining a few of the quality parameters. RESULTS. Three quality parameters (B-mode visualization of the lesion, presence of a near-field red pattern, and the appearance of the surrounding tissue) showed moderate-to-substantial interobserver agreement. SWE images were considered high quality (n = 167) if both B-mode visualization and near-field red pattern received a consensus score of 1, and they were considered low quality (n = 114) if either parameter received a consensus score of 0. High-quality images had a statistically higher AUC value than low-quality images when Emax (p < .001), Emean (p = .002), and ESD (p < .001) were used as classifiers of malignancy. CONCLUSION. Quality parameters can support radiologists who are performing and interpreting breast SWE images. These quality parameters have the potential to improve the accuracy of SWE in differentiating malignant from benign breast lesions.

Retrospective Review of Preoperative Radiofrequency Tag Localization of Breast Lesions in 848 Patients.

BACKGROUND. Advantages of radiofrequency tags for preoperative breast lesion localization include decoupling of tag placement from surgical schedules and improved patient comfort. OBJECTIVE. The purpose of this study was to evaluate the feasibility of a preoperative localization radiofrequency tag system for breast lesions requiring surgical excision. METHODS. The cohort for this retrospective study included consecutive patients who underwent image-guided needle localization with radiofrequency tags before surgical excision from July 12, 2018, to July 31, 2019. Images and medical records were reviewed to evaluate the pathologic diagnoses serving as indications for tag placement, imaging guidance for tag placement, number of tags placed, and target lesion type. Tag placement technical accuracy rate (defined as deployment of the tag within 1 cm of the edge of the target), success (defined as technical accuracy without complication), and surgical margin and reexcision status were evaluated. RESULTS. A total of 1013 tags were placed under imaging guidance in 848 patients (mean age, 60 years; range, 23-96 years) and 847 subsequently underwent surgical excision. Tags were most commonly placed for invasive carcinoma (537/1013, 53.0%), ductal carcinoma in situ (138/1013, 13.6%), and high-risk lesions (289/1013, 28.5%). A total of 673 (66.4%) tags were deployed under mammographic guidance, whereas 340 (33.6%) were placed under sonographic guidance. Two or more tags were placed in 149 of 848 patients (17.6%). Targeted lesion types primarily included masses (448/1013, 44.2%), biopsy clip markers (331/1013, 32.7%), and calcifications (155/1013, 15.3%). Technical accuracy of placement was achieved in 1004 (99.1%) tags. Of the nine inaccurate tag placements, seven (77.8%) required an additional tag or wire placement. Seven (0.7%) biopsy clip markers were displaced within the breast or removed by the tag device during placement. No complications were reported intraoperatively. Therefore, success was achieved in 997 (98.4%) tags. Tags were successfully retrieved in all 847 patients who underwent surgery. Of the 568 patients with a preoperative diagnosis of carcinoma, 86 (15.1%) had positive or close surgical margins requiring surgical reexcision. CONCLUSION. Preoperative image-guided localization with radiofrequency tags is a safe and feasible technique for breast lesions requiring surgery. CLINICAL IMPACT. Radiofrequency tag localization is an acceptable alternative to needle or wire localization, offering the potential for improved patient workflow and experience.

Breast Cancer Screening with Digital Breast Tomosynthesis: Are Initial Benefits Sustained?

Background Performance metrics with digital breast tomosynthesis (DBT) are based on early experiences. There is limited research on whether the benefits of DBT are sustained. Purpose To determine whether improved screening performance metrics with DBT are sustained over time at the population level and after the first screening round at the individual level. Materials and Methods A retrospective review was conducted of screening mammograms that had been obtained before DBT implementation (March 2008 to February 2011, two-dimensional digital mammography [DM] group) and for 5 years after implementation (January 2013 to December 2017, DBT1-DBT5 groups, respectively). Patients who underwent DBT were also categorized according to the number of previous DBT examinations they had undergone. Performance metrics were compared between DM and DBT groups and between patients with no previous DBT examinations and those with at least one prior DBT examination by using multivariable logistic regression models. Results The DM group consisted of 99 582 DM examinations in 55 086 women (mean age, 57.3 years ± 11.6 [standard deviation]). The DBT group consisted of 205 048 examinations in 76 276 women (mean age, 58.2 years ± 11.2). There were no differences in the cancer detection rate (CDR) between DM and DBT groups (4.6-5.8 per 1000 examinations, P = .08 to P = .95). The highest CDR was observed with a woman's first DBT examination (6.1 per 1000 examinations vs 4.4-5.7 per 1000 examinations with at least one prior DBT examination, P = .001 to P = .054). Compared with the DM group, the DBT1 group had a lower abnormal interpretation rate (AIR) (adjusted odds ratio [AOR], 0.85; P < .001), which remained reduced in the DBT2, DBT3, and DBT5 groups (P < .001 to P = .02). The reduction in AIR was also sustained after the first examination (P < .001 to P = .002). Compared with the DM group, the DBT1 group had a higher specificity (AOR, 1.20; P < .001), which remained increased in DBT2, DBT3, and DBT5 groups (P < .001 to P = .004). The increase in specificity was also sustained after the first examination (P < .001 to P = .01). Conclusion The benefits of reduced false-positive examinations and higher specificity with screening tomosynthesis were sustained after the first screening round at the individual level. © RSNA, 2020 See also the editorial by Taourel in this issue.

Do Eligibility Criteria for Ductal Carcinoma In Situ (DCIS) Active Surveillance Trials Identify Patients at Low Risk for Upgrade to Invasive Carcinoma?

BACKGROUND: Clinical trials are currently ongoing to determine the safety and efficacy of active surveillance (AS) versus usual care (surgical and radiation treatment) for women with ductal carcinoma in situ (DCIS). This study aimed to determine upgrade rates of DCIS at needle biopsy to invasive carcinoma at surgery among women who meet the eligibility criteria for AS trials. METHODS: A retrospective review was performed of consecutive women at an academic medical center with a diagnosis of DCIS at needle biopsy from 2007 to 2016. Medical records were reviewed for mode of presentation, imaging findings, biopsy pathology results, and surgical outcomes. Each patient with DCIS was evaluated for AS trial eligibility based on published criteria for the COMET, LORD, and LORIS trials. RESULTS: During a 10-year period, DCIS was diagnosed in 858 women (mean age 58 years; range 28-89 years). Of the 858 women, 498 (58%) were eligible for the COMET trial, 101 (11.8%) for the LORD trial, and 343 (40%) for the LORIS trial. The rates of upgrade to invasive carcinoma were 12% (60/498) for the COMET trial, 5% (5/101) for the LORD trial, and 11.1% (38/343) for the LORIS trial. The invasive carcinomas ranged from 0.2 to 20 mm, and all were node-negative. CONCLUSIONS: Women who meet the eligibility criteria for DCIS AS trials remain at risk for occult invasive carcinoma at presentation, with upgrade rates ranging from 5 to 12%. These findings suggest that more precise criteria are needed to ensure that women with invasive carcinoma are excluded from AS trials.

Frequency and Cancer Yield of BI-RADS Category 3 Lesions Detected at High-Risk Screening Breast MRI.

OBJECTIVE. The purpose of this study was to evaluate the frequency and cancer yield of BI-RADS category 3 lesions in baseline versus nonbaseline (those with at least one prior) MRI screening examinations. MATERIALS AND METHODS. Consecutive MRI screening examinations performed from 2011 through 2015 were reviewed. Pearson and Wilcoxon tests were used to examine differences in age, breast density, screening indication, background parenchymal enhancement, and cancer yield between baseline and nonbaseline MRI BI-RADS category 3 assessments. Multivariate logistic regression models based on generalized estimating equations were used to assess the odds of receiving a BI-RADS 3 assessment as a function of the variables. RESULTS. Of 6672 MRI screening examinations of 3214 patients, 202 examinations (3%) were assessed BI-RADS category 3. Among baseline examinations, 8% (82/983) were assessed BI-RADS 3, compared with 2% (120/5689) of nonbaseline examinations (p < 0.001). Among the total BI-RADS 3 examinations, 6% (13/202) yielded malignancy of the lesion that had been assessed BI-RADS 3; 12 of 13 cancers were stage 0 or I at diagnosis. The cancer yield of BI-RADS 3 at baseline examinations was 2% (2/82), compared with 9% (11/120) for nonbaseline examinations (p = 0.056). Ten of 13 examinations were upgraded at or before 6-month follow-up MRI. CONCLUSION. Baseline screening breast MRI examinations are associated with a significantly higher rate of BI-RADS category 3 assessments than are nonbaseline examinations. Most cancers diagnosed at follow-up of BI-RADS 3 lesions are in an early stage and are diagnosed at or before the 6-month follow-up examination. When used judiciously, short-interval follow-up MRI is an appropriate method for identifying early-stage breast cancer while avoiding unnecessary biopsies with benign findings.

Obesity and breast cancer screening: Cross-sectional survey results from the behavioral risk factor surveillance system.

BACKGROUND: Postmenopausal obese women demonstrate an elevated breast cancer risk and experience increased breast cancer morbidity and mortality compared with women with a normal body mass index (BMI). However, to the authors' knowledge, prior studies have yielded inconclusive results regarding the effects of obesity on mammography screening adherence. Using national cross-sectional survey data, the objective of the current study was to assess the current association between increasing BMI and use of mammography screening. METHODS: Cross-sectional survey data from the 2016 Behavioral Risk Factor Surveillance System, a state-based national telephone survey of noninstitutionalized adults in the United States, was used to identify the association between mammography screening use and increasing incremental BMI categories, including normal (18.5-24.9 kg/m2 ), overweight (25-29.9 kg/m2 ), obese class I (30-34.9 kg/m2 ), obese class II (35-39.9 kg/m2 ), and obese class III (>40 kg/m2 ), with adjustments for potential confounders. A multivariable logistic regression model was used to evaluate the effect of each BMI category on self-reported mammography use, using unadjusted and adjusted odds ratios. Effect modification by race/ethnicity was determined by testing interaction terms using Wald tests. RESULTS: Of 116,343 survey respondents, 33.5% (38,984 respondents) had a normal BMI, 32.6% (37,969 respondents) were overweight, 19.3% (22,416 respondents) were classified as obese class I, 8.4% (9791 respondents) were classified as obese class II, and 6.2% (7183 respondents) were classified as obese class III. There was no statistically significant difference (P < .05) observed with regard to mammography use between women with a normal BMI and obese women from each obese class (classes I-III) when compared individually. There also was no evidence of effect modification by race (P = .53). CONCLUSIONS: In contrast to prior reports, the results of the current study demonstrated no association between obesity and adherence to screening mammography. These findings may relate to the increasing social acceptance of obesity among women from all racial/ethnic groups and the removal of weight-related facility-level barriers over time.