OBJECTIVE: To evaluate the effects of the Enhancing Quality Using the Inspection Program (EQUIP) on quality control (QC) and quality assurance (QA) at an academic medical center.
METHODS: EQUIP audit logs for technologist image quality review as well as mammography unit QA and QC formed the basis for study data. One randomly selected screening mammogram was evaluated by the lead interpreting physician (LIP) using EQUIP criteria for each technologist for each imaging site worked, initially semiannually and then monthly. One randomly selected screening mammogram interpreted by each interpreting physician (IP) for each imaging site was evaluated on a semiannual basis. Quarterly, the LIP reviewed QA and QC logs for each mammography unit with deficiencies further investigated.
RESULTS: Of 214 965 eligible screening mammograms performed, 5955 (2.8%) underwent EQUIP image quality review. Five were found to be technically inadequate (0.08%, 5955/214 965). The LIP identified 20 significant interpretive differences compared with the clinical interpretation resulting in 10 biopsies and 7 previously undetected malignancies, with supplemental cancer detection rate of 1.2/1000 cases reviewed. Two hundred ninety mammography unit QA/QC reviews identified 31 potential deficiencies, 29 of which were due to human documentation error (93.4%).
CONCLUSIONS: EQUIP review of both IP and technologists\' quality and mammography unit QA/QC logs as performed identified few deficiencies. EQUIP policies should be evaluated at each institution and modified to best utilize resources and provide opportunities for meaningful quality improvement. Although not an EQUIP focus, supplemental cancer detection was observed as might be expected with double reading.

Early detection decreases deaths from breast cancer. Yet, there are conflicting recommendations about screening mammography by major professional medical organizations, including the age and frequency with which women should be screened. The controversy over breast cancer screening is centered on 3 main points: the impact on mortality, overdiagnosis, and false positive results. Some studies claim that adverse psychological effects such as anxiety or distress are caused by screening mammography. The purpose of this article is to address negative breast cancer screening concerns including overdiagnosis and overtreatment, effect on mortality, false positive results, mammography-related anxiety, and fear of radiation.

OBJECTIVE: To characterize the patient population using weekend and evening appointments for screening mammography versus standard appointment times across four outpatient facilities in our academic health system.
METHODS: In this institutional review board-approved retrospective cohort study, there were 203,101 screening mammograms from 67,323 patients who had a screening mammogram performed at outpatient centers at a multisite academic institution from January 1, 2015, to December 31, 2022. Screening appointments were defined as \"standard appointment time\" (between 8 am and 5 pm on Monday through Friday) or \"weekend or evening appointment time\" (scheduled after 5 pm on Monday through Friday or at any time on a Saturday or Sunday). Associations between appointment group and patient characteristics were analyzed using univariate and multivariate logistic regression.
RESULTS: Most screening mammograms (n = 185,436, 91.3%) were performed at standard times. The remainder (n = 17,665, 8.7%) were performed during weekends or evenings. As we created additional weekend and evening appointments after the coronavirus disease 2019 pandemic, the annual percentage of all screening mammograms performed on evenings and weekends increased. On multivariate analysis, when compared with standard appointment times, we found that patients who were younger than age 50 (P < .001), a race other than non-Hispanic White (P < .001), non-English speakers (P < .001), and from less advantaged zip codes (P < .03) were more likely to use weekend and evening appointment times compared with those aged 70 and above, non-Hispanic White patients, English speakers, and those from the most advantaged zip codes.
CONCLUSIONS: Weekend and evening appointment availability for screening mammograms might improve screening access for all patients, particularly for those younger than age 50, those of races other than non-Hispanic White, and those from less advantaged zip codes.

Purpose To investigate the issues of generalizability and replication of deep learning models by assessing performance of a screening mammography deep learning system developed at New York University (NYU) on a local Australian dataset. Materials and Methods In this retrospective study, all individuals with biopsy or surgical pathology-proven lesions and age-matched controls were identified from a South Australian public mammography screening program (January 2010 to December 2016). The primary outcome was deep learning system performance-measured with area under the receiver operating characteristic curve (AUC)-in classifying invasive breast cancer or ductal carcinoma in situ (n = 425) versus no malignancy (n = 490) or benign lesions (n = 44). The NYU system, including models without (NYU1) and with (NYU2) heatmaps, was tested in its original form, after training from scratch (without transfer learning), and after retraining with transfer learning. Results The local test set comprised 959 individuals (mean age, 62.5 years ± 8.5 [SD]; all female). The original AUCs for the NYU1 and NYU2 models were 0.83 (95% CI: 0.82, 0.84) and 0.89 (95% CI: 0.88, 0.89), respectively. When NYU1 and NYU2 were applied in their original form to the local test set, the AUCs were 0.76 (95% CI: 0.73, 0.79) and 0.84 (95% CI: 0.82, 0.87), respectively. After local training without transfer learning, the AUCs were 0.66 (95% CI: 0.62, 0.69) and 0.86 (95% CI: 0.84, 0.88). After retraining with transfer learning, the AUCs were 0.82 (95% CI: 0.80, 0.85) and 0.86 (95% CI: 0.84, 0.88). Conclusion A deep learning system developed using a U.S. dataset showed reduced performance when applied \"out of the box\" to an Australian dataset. Local retraining with transfer learning using available model weights improved model performance. Keywords: Screening Mammography, Convolutional Neural Network (CNN), Deep Learning Algorithms, Breast Cancer Supplemental material is available for this article. © RSNA, 2024 See also commentary by Cadrin-Chênevert in this issue.

OBJECTIVE: To determine cancer visualization utility and radiation dose for non-implant-displaced (ID) views using standard protocol with digital breast tomosynthesis (DBT) vs alternative protocol with 2D only when screening women with implant augmentation.
METHODS: This retrospective cohort study identified women with implants who underwent screening DBT examinations that had abnormal findings from July 28, 2014, to December 31, 2021. Three fellowship-trained breast radiologists independently reviewed examinations retrospectively to determine if the initially identified abnormalities could be visualized on standard protocol (DBT with synthesized 2D (S2D) for ID and non-ID views) and alternate protocol (DBT with S2D for ID and only the S2D images for non-ID views). Estimated exam average glandular dose (AGD) and associations between cancer visualization with patient and implant characteristics for both protocols were evaluated.
RESULTS: The study included 195 patients (mean age 55 years ± 10) with 223 abnormal findings. Subsequent biopsy was performed for 86 abnormalities: 59 (69%) benign, 8 (9%) high risk, and 19 (22%) malignant. There was no significant difference in malignancy visualization rate between standard (19/223, 8.5%) and alternate (18/223, 8.1%) protocols (P = .92), but inclusion of the DBT for non-ID views found one additional malignancy. Total examination AGD using standard protocol (21.9 mGy ± 5.0) was significantly higher than it would be for estimated alternate protocol (12.6 mGy ± 5.0, P <.001). This remained true when stratified by breast thickness: 6.0-7.9 cm, 8.0-9.9 cm, >10.0 cm (all P <.001).
CONCLUSIONS: The inclusion of DBT for non-ID views did not significantly increase the cancer visualization rate but did significantly increase overall examination AGD.

Purpose: Breast cancer (BC) incidence is increasing globally. Age-specific BC incidence trend analyses are lacking for women under age 50 in Canada. In this study, we evaluate the incidence trends in breast cancer in women under age 50 in Canada and compare them with corresponding trends among women 50 to 54. Methods: BC case counts were obtained from the National Cancer Incidence Reporting System (1984-1991) and the Canadian Cancer Registry (1992-2019) both housed at Statistics Canada. Population data were also obtained from Statistics Canada. Annual female BC age-specific incidence rates from 1984 to 2019 were derived for the following age groups: 20 to 29, 30 to 39, 40 to 49, 40 to 44, 45 to 49, and 50 to 54. Changes in trends in age-specific BC incidence rates, if any, and annual percent changes (APCs) for each identified trend, were determined using JoinPoint. Results: Statistically significant increasing trends in BC incidence rates were noted for almost all age groups: since 2001 for 20 to 29 (APC = 3.06%, P < .001); since 2009 for 30 to 39 (APC = 1.25%, P = .007); since 1984 for both 40 to 49 (APC = 0.26%, P < .001) and 40 to 44 (APC = 0.19%, P = .011), increased since 2015 for 40 to 49 (APC = 0.77%, P = .047); and since 2005 for 50 to 54 (APC = 0.38%, P = .022). Among women 45 to 49 there was a non-significant increase since 2005 (APC = 0.24, P = .058). Statistically significant average annualized increases in BC incidence rates were observed for each age group studied. Conclusions: Examining age-specific incidence rates formed a more complete picture of BC time trends with significant increasing trends in the incidence of BC among women in their 20s, 30s, 40s, and early 50s. A greater awareness regarding the increasing number of cases of BC in women younger than 50 is critical to allow for earlier diagnosis with its resultant reduced mortality and morbidity.

OBJECTIVE: Nationally legislated dense breast notification (DBN) informs women of their breast density (BD) and the impact of BD on breast cancer risk and detection, but consequences for screening participation are unclear. We evaluated the association of DBN in New York State (NYS) with subsequent screening mammography in a largely Hispanic/Latina cohort.
METHODS: Women aged 40-60 were surveyed in their preferred language (33% English, 67% Spanish) during screening mammography from 2016 to 2018. We used clinical BD classification from mammography records from 2013 (NYS DBN enactment) through enrollment (baseline) to create a 6-category variable capturing prior and new DBN receipt (sent only after clinically dense mammograms). We used this variable to compare the number of subsequent mammograms (0, 1, ≥ 2) from 10 to 30 months after baseline using ordinal logistic regression.
RESULTS: In a sample of 728 women (78% foreign-born, 72% Hispanic, 46% high school education or less), first-time screeners and women who received DBN for the first time after prior non-dense mammograms had significantly fewer screening mammograms within 30 months of baseline (Odds Ratios range: 0.33 (95% Confidence Interval (CI) 0.12-0.85) to 0.38 (95% CI 0.17-0.82)) compared to women with prior mammography but no DBN. There were no differences in subsequent mammogram frequency between women with multiple DBN and those who never received DBN. Findings were consistent across age, language, health literacy, and education groups.
CONCLUSIONS: Women receiving their first DBN after previous non-dense mammograms have lower mammography participation within 2.5 years. DBN has limited influence on screening participation of first-time screeners and those with persistent dense mammograms.

OBJECTIVE: Patients who miss screening mammogram appointments without notifying the health care system (no-show) risk care delays. We investigate sociodemographic characteristics of patients who experience screening mammogram no-shows at a community health center and whether and when the missed examinations are completed.
METHODS: We included patients with screening mammogram appointments at a community health center between January 1, 2021, and December 31, 2021. Language, race, ethnicity, insurance type, residential ZIP code tabulation area (ZCTA) poverty, appointment outcome (no-show, same-day cancelation, completed), and dates of completed screening mammograms after no-show appointments with ≥1-year follow-up were collected. Multivariable analyses were used to assess associations between patient characteristics and appointment outcomes.
RESULTS: Of 6,159 patients, 12.1% (743 of 6,159) experienced no-shows. The no-show group differed from the completed group by language, race and ethnicity, insurance type, and poverty level (all P < .05). Patients with no-shows more often had: primary language other than English (32.0% [238 of 743] versus 26.7% [1,265 of 4,741]), race and ethnicity other than White non-Hispanic (42.3% [314 of 743] versus 33.6% [1,595 of 4,742]), Medicaid or means-tested insurance (62.0% [461 of 743] versus 34.4% [1,629 of 4,742]), and residential ZCTAs with ≥20% poverty (19.5% [145 of 743] versus 14.1% [670 of 4,742]). Independent predictors of no-shows were Black non-Hispanic race and ethnicity (adjusted odds ratio [aOR], 1.52; 95% confidence interval [CI], 1.12-2.07; P = .007), Medicaid or other means-tested insurance (aOR, 2.75; 95% CI, 2.29-3.30; P < .001), and ZCTAs with ≥20% poverty (aOR, 1.76; 95% CI, 1.14-2.72; P = .011). At 1-year follow-up, 40.6% (302 of 743) of patients with no-shows had not completed screening mammogram.
CONCLUSIONS: Screening mammogram no-shows is a health equity issue in which socio-economically disadvantaged and racially and ethnically minoritized patients are more likely to experience missed appointments and continued delays in screening mammogram completion.

OBJECTIVE: To determine the incidence, timing, and long-term outcomes of unilateral axillary lymphadenopathy ipsilateral to vaccine site (UIAL) on screening mammography after COVID-19 vaccination.
METHODS: This retrospective, multisite study included consecutive patients undergoing screening mammography February 8, 2021, to January 31, 2022, with at least 1 year of follow-up. UIAL was typically considered benign (BI-RADS 1 or 2) in the setting of recent (≤6 weeks) vaccination or BI-RADS 0 (ultrasound recommended) when accompanied by a breast finding or identified >6 weeks postvaccination. Vaccination status and manufacturer were obtained from regional registries. Lymphadenopathy rates in vaccinated patients with and without UIAL were compared using Pearson\'s χ2 test.
RESULTS: There were 44,473 female patients (mean age 60.4 ± 11.4 years) who underwent screening mammography at five sites, and 40,029 (90.0%) received at least one vaccine dose. Ninety-four (0.2%) presented with UIAL, 1 to 191 days postvaccination (median 13.5 [interquartile range: 5.0-31.0]). Incidence declined from 2.1% to 0.9% to ≤0.5% after 1, 2, and 3 weeks and persisted up to 36 weeks (P < .001). UIAL did not vary across manufacturer (P = .15). Of 94, 77 (81.9%) were BI-RADS 1 or 2 at screening. None were diagnosed with malignancy at 1-year follow-up. Seventeen (18.1%) were BI-RADS 0 at screening. At diagnostic workup, 13 (76.5%) were BI-RADS 1 or 2, 2 (11.8%) were BI-RADS 3, and 2 (11.8%) were BI-RADS 4. Both BI-RADS 4 patients had malignant status and ipsilateral breast malignancies. Of BI-RADS 3 patients, at follow-up, one was biopsied yielding benign etiology, and one was downgraded to BI-RADS 2.
CONCLUSIONS: Isolated UIAL on screening mammography performed within 6 months of COVID-19 vaccination can be safely assessed as benign.

This article describes radiation doses and cancer risks of digital breast imaging technologies used for breast cancer detection. These include digital mammography (DM), digital breast tomosynthesis (DBT), and newer technologies such as contrast-enhanced digital or spectral mammography (CEM), whole-breast computed tomography, breast-specific gamma imaging (BSGI), molecular breast imaging (MBI), and positron emission mammography (PEM). This article describes the basis for radiation risk estimates, compares radiation doses and risks, and provides benefit-to-radiation-risk ratios for different breast imaging modalities that use ionizing radiation. Current x-ray-based screening modalities such as DM and DBT have small to negligible risks of causing radiation-induced cancers in women of normal screening age. Possible new screening modalities such as CEM have similar small cancer risks. Potential screening modalities that involve radionuclide injection such as BSGI, MBI, and PEM have significantly higher cancer risks unless efficient detection systems and reduced administered doses are used. Benefit-to-radiation-risk estimates are highly favorable for screening with DM and other modalities having comparable (or higher) cancer detection rates and comparably low radiation doses.