Identifying women with dense breasts at high risk for interval cancer: a cohort study

Breast Cancer Screening Using Mammography, Digital Breast Tomosynthesis, and Magnetic Resonance Imaging by Breast Density

Importance

Information on long-term benefits and harms of screening with digital breast tomosynthesis (DBT) with or without supplemental breast magnetic resonance imaging (MRI) is needed for clinical and policy discussions, particularly for patients with dense breasts.

Objective

To project long-term population-based outcomes for breast cancer mammography screening strategies (DBT or digital mammography) with or without supplemental MRI by breast density.

Design, Setting, and Participants

Collaborative modeling using 3 Cancer Intervention and Surveillance Modeling Network (CISNET) breast cancer simulation models informed by US Breast Cancer Surveillance Consortium data. Simulated women born in 1980 with average breast cancer risk were included. Modeling analyses were conducted from January 2020 to December 2023.

Intervention

Annual or biennial mammography screening with or without supplemental MRI by breast density starting at ages 40, 45, or 50 years through age 74 years.

Main outcomes and Measures

Lifetime breast cancer deaths averted, false-positive recall and false-positive biopsy recommendations per 1000 simulated women followed-up from age 40 years to death summarized as means and ranges across models.

Results

Biennial DBT screening for all simulated women started at age 50 vs 40 years averted 7.4 vs 8.5 breast cancer deaths, respectively, and led to 884 vs 1392 false-positive recalls and 151 vs 221 false-positive biopsy recommendations, respectively. Biennial digital mammography had similar deaths averted and slightly more false-positive test results than DBT screening. Adding MRI for women with extremely dense breasts to biennial DBT screening for women aged 50 to 74 years increased deaths averted (7.6 vs 7.4), false-positive recalls (919 vs 884), and false-positive biopsy recommendations (180 vs 151). Extending supplemental MRI to women with heterogeneously or extremely dense breasts further increased deaths averted (8.0 vs 7.4), false-positive recalls (1088 vs 884), and false-positive biopsy recommendations (343 vs 151). The same strategy for women aged 40 to 74 years averted 9.5 deaths but led to 1850 false-positive recalls and 628 false-positive biopsy recommendations. Annual screening modestly increased estimated deaths averted but markedly increased estimated false-positive results.

Conclusions and relevance

In this model-based comparative effectiveness analysis, supplemental MRI for women with dense breasts added to DBT screening led to greater benefits and increased harms. The balance of this trade-off for supplemental MRI use was more favorable when MRI was targeted to women with extremely dense breasts who comprise approximately 10% of the population.

Clinical Significance of Combined Density and Deep-Learning-Based Texture Analysis for Stratifying the Risk of Short-Term and Long-Term Breast Cancer in Screening

Assessing a woman's risk of breast cancer is important for personalized screening. Mammographic density is a strong risk factor for breast cancer, but parenchymal texture patterns offer additional information which cannot be captured by density. We aimed to combine BI-RADS density score 4th Edition and a deep-learning-based texture score to stratify women in screening and compare rates among the combinations. This retrospective study cohort study included 216,564 women from a Danish populations-based screening program. Baseline mammograms were evaluated using BI-RADS density scores (1-4) and a deep-learning texture risk model, with scores categorized into four quartiles (1-4). The incidence rate ratio (IRR) for screen-detected, interval, and long-term cancer were adjusted for age, year of screening and screening clinic. Compared with subgroup B1-T1, the highest IRR for screen-detected cancer were within the T4 category (3.44 (95% CI: 2.43-4.82)-4.57 (95% CI: 3.66-5.76)). IRR for interval cancer was highest in the BI-RADS 4 category (95% CI: 5.36 (1.77-13.45)-16.94 (95% CI: 9.93-30.15)). IRR for long-term cancer increased both with increasing BI-RADS and increasing texture reaching 5.15 (4.31-6.16) for the combination of B4-T4 compared with B1-T1. Deep-learning-based texture analysis combined with BI-RADS density categories can reveal subgroups with increased rates beyond what density alone can ascertain, suggesting the potential of combining texture and density to improve risk stratification in breast cancer screening.

Performance of Supplemental US Screening in Women with Dense Breasts and Varying Breast Cancer Risk: Results from the Breast Cancer Surveillance Consortium

Background It is unclear whether breast US screening outcomes for women with dense breasts vary with levels of breast cancer risk. Purpose To evaluate US screening outcomes for female patients with dense breasts and different estimated breast cancer risk levels. Materials and Methods This retrospective observational study used data from US screening examinations in female patients with heterogeneously or extremely dense breasts conducted from January 2014 to October 2020 at 24 radiology facilities within three Breast Cancer Surveillance Consortium (BCSC) registries. The primary outcomes were the cancer detection rate, false-positive biopsy recommendation rate, and positive predictive value of biopsies performed (PPV3). Risk classification of participants was performed using established BCSC risk prediction models of estimated 6-year advanced breast cancer risk and 5-year invasive breast cancer risk. Differences in high- versus low- or average-risk categories were assessed using a generalized linear model. Results In total, 34 791 US screening examinations from 26 489 female patients (mean age at screening, 53.9 years ± 9.0 [SD]) were included. The overall cancer detection rate per 1000 examinations was 2.0 (95% CI: 1.6, 2.4) and was higher in patients with high versus low or average risk of 6-year advanced breast cancer (5.5 [95% CI: 3.5, 8.6] vs 1.3 [95% CI: 1.0, 1.8], respectively; P = .003). The overall false-positive biopsy recommendation rate per 1000 examinations was 29.6 (95% CI: 22.6, 38.6) and was higher in patients with high versus low or average 6-year advanced breast cancer risk (37.0 [95% CI: 28.2, 48.4] vs 28.1 [95% CI: 20.9, 37.8], respectively; P = .04). The overall PPV3 was 6.9% (67 of 975; 95% CI: 5.3, 8.9) and was higher in patients with high versus low or average 6-year advanced cancer risk (15.0% [15 of 100; 95% CI: 9.9, 22.2] vs 4.9% [30 of 615; 95% CI: 3.3, 7.2]; P = .01). Similar patterns in outcomes were observed by 5-year invasive breast cancer risk. Conclusion The cancer detection rate and PPV3 of supplemental US screening increased with the estimated risk of advanced and invasive breast cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Helbich and Kapetas in this issue.

Radiation exposure and screening yield by digital breast tomosynthesis compared to mammography: results of the TOSYMA Trial breast density related

OBJECTIVES

The randomized TOmosynthesis plus SYnthesized MAmmography (TOSYMA) screening trial has shown that digital breast tomosynthesis plus synthesized mammography (DBT + SM) is superior to digital mammography (DM) in invasive breast cancer detection varying with breast density. On the other hand, the overall average glandular dose (AGD) of DBT is higher than that of DM. Comparing the DBT + SM and DM trial arm, we analyzed here the mean AGD and their determinants per breast density category and related them to the respective invasive cancer detection rates (iCDR).

METHODS

TOSYMA screened 99,689 women aged 50 to 69 years. Compression force, resulting breast thickness, the calculated AGD obtained from each mammography device, and previously published iCDR were used for comparisons across breast density categories in the two trial arms.

RESULTS

There were 196,622 exposures of 49,227 women (DBT + SM) and 197,037 exposures of 49,132 women (DM) available for analyses. Mean breast thicknesses declined from breast density category A (fatty) to D (extremely dense) in both trial arms. However, while the mean AGD in the DBT + SM arm declined concomitantly from category A (2.41 mGy) to D (1.89 mGy), it remained almost unchanged in the DM arm (1.46 and 1.51 mGy, respectively). In relative terms, the AGD elevation in the DBT + SM arm (64.4% (A), by 44.5% (B), 27.8% (C), and 26.0% (D)) was lowest in dense breasts where, however, the highest iCDR were observed.

CONCLUSION

Women with dense breasts may specifically benefit from DBT + SM screening as high cancer detection is achieved with only moderate AGD elevations.

CLINICAL RELEVANCE STATEMENT

TOSYMA suggests a favorable constellation for screening with digital breast tomosynthesis plus synthesized mammography (DBT + SM) in dense breasts when weighing average glandular dose elevation against raised invasive breast cancer detection rates. There is potential for density-, i.e., risk-adapted population-wide breast cancer screening with DBT + SM.

KEY POINTS

Breast thickness declines with visually increasing density in digital mammography (DM) and digital breast tomosynthesis (DBT). Average glandular doses of DBT decrease with increasing density; digital mammography shows lower and more constant values. With the smallest average glandular dose difference in dense breasts, DBT plus SM had the highest difference in invasive breast cancer detection rates.

Relative Timing of Mammography and MRI for Breast Cancer Screening: Impact on Performance Evaluation

OBJECTIVE

Mammography and MRI screening typically occur in combination or in alternating sequence. We compared multimodality screening performance accounting for the relative timing of mammography and MRI and overlapping follow-up periods.

METHODS

We identified 8,260 screening mammograms performed 2005 to 2017 in the Breast Cancer Surveillance Consortium, paired with screening MRIs within ±90 days (combined screening) or 91 to 270 days (alternating screening). Performance for combined screening (cancer detection rate [CDR] per 1,000 examinations and sensitivity) was calculated with 1-year follow-up for each modality, and with a single follow-up period treating the two tests as a single test. Alternating screening performance was calculated with 1-year follow-up for each modality and also with follow-up ending at the next screen if within 1 year (truncated follow-up).

RESULTS

For 3,810 combined screening pairs, CDR per 1,000 screens was 6.8 (95% confidence interval [CI]: 4.6-10.0) for mammography and 12.3 (95% CI: 9.3-16.4) for MRI as separate tests compared with 13.1 (95% CI: 10.0-17.3) as a single combined test. Sensitivity of each test was 48.1% (35.0%-61.5%) for mammography and 79.7% (95% CI: 67.7%-88.0%) for MRI compared with 96.2% (95% CI: 85.9%-99.0%) for combined screening. For 4,450 alternating screening pairs, mammography CDR per 1,000 screens changed from 3.6 (95% CI: 2.2-5.9) to zero with truncated follow-up; sensitivity was incalculable (denominator = 0). MRI CDR per 1,000 screens changed from 12.1 (95% CI 9.3-15.8) to 11.7 (95% CI: 8.9-15.3) with truncated follow-up; sensitivity changed from 75.0% (95% CI 63.8%-83.6%) to 86.7% (95% CI 75.5%-93.2%).

DISCUSSION

Updating auditing approaches to account for combined and alternating screening sequencing and to address outcome attribution issues arising from overlapping follow-up periods can improve the accuracy of multimodality screening performance evaluation.

Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening Cohort

Purpose To develop an artificial intelligence (AI) deep learning tool capable of predicting future breast cancer risk from a current negative screening mammographic examination and to evaluate the model on data from the UK National Health Service Breast Screening Program. Materials and Methods The OPTIMAM Mammography Imaging Database contains screening data, including mammograms and information on interval cancers, for more than 300 000 female patients who attended screening at three different sites in the United Kingdom from 2012 onward. Cancer-free screening examinations from women aged 50-70 years were performed and classified as risk-positive or risk-negative based on the occurrence of cancer within 3 years of the original examination. Examinations with confirmed cancer and images containing implants were excluded. From the resulting 5264 risk-positive and 191 488 risk-negative examinations, training (n = 89 285), validation (n = 2106), and test (n = 39 351) datasets were produced for model development and evaluation. The AI model was trained to predict future cancer occurrence based on screening mammograms and patient age. Performance was evaluated on the test dataset using the area under the receiver operating characteristic curve (AUC) and compared across subpopulations to assess potential biases. Interpretability of the model was explored, including with saliency maps. Results On the hold-out test set, the AI model achieved an overall AUC of 0.70 (95% CI: 0.69, 0.72). There was no evidence of a difference in performance across the three sites, between patient ethnicities, or across age groups. Visualization of saliency maps and sample images provided insights into the mammographic features associated with AI-predicted cancer risk. Conclusion The developed AI tool showed good performance on a multisite, United Kingdom-specific dataset. Keywords: Deep Learning, Artificial Intelligence, Breast Cancer, Screening, Risk Prediction Supplemental material is available for this article. ©RSNA, 2024.

Imaging the dense breast

The sensitivity of mammography reduces as breast density increases, which impacts breast screening and locoregional staging in breast cancer. Supplementary imaging with other modalities can offer improved cancer detection, but this often comes at the cost of more false positives. Magnetic resonance imaging and contrast-enhanced mammography, which assess tumour enhancement following contrast administration, are more sensitive than digital breast tomosynthesis and ultrasound, which predominantly rely on the assessment of tumour morphology.

Breast Density: Where Are We Now?

Breast density refers to the amount of fibroglandular tissue relative to fat on mammography and is determined either qualitatively through visual assessment or quantitatively. It is a heritable and dynamic trait associated with age, race/ethnicity, body mass index, and hormonal factors. Increased breast density has important clinical implications including the potential to mask malignancy and as an independent risk factor for the development of breast cancer. Breast density has been incorporated into breast cancer risk models. Given the impact of dense breasts on the interpretation of mammography, supplemental screening may be indicated.

Screening for Breast Cancer: US Preventive Services Task Force Recommendation Statement

Importance

Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast cancer. Non-Hispanic White women have the highest incidence of breast cancer and non-Hispanic Black women have the highest mortality rate.

Objective

The USPSTF commissioned a systematic review to evaluate the comparative effectiveness of different mammography-based breast cancer screening strategies by age to start and stop screening, screening interval, modality, use of supplemental imaging, or personalization of screening for breast cancer on the incidence of and progression to advanced breast cancer, breast cancer morbidity, and breast cancer-specific or all-cause mortality, and collaborative modeling studies to complement the evidence from the review.

Population

Cisgender women and all other persons assigned female at birth aged 40 years or older at average risk of breast cancer.

Evidence Assessment

The USPSTF concludes with moderate certainty that biennial screening mammography in women aged 40 to 74 years has a moderate net benefit. The USPSTF concludes that the evidence is insufficient to determine the balance of benefits and harms of screening mammography in women 75 years or older and the balance of benefits and harms of supplemental screening for breast cancer with breast ultrasound or magnetic resonance imaging (MRI), regardless of breast density.

Recommendation

The USPSTF recommends biennial screening mammography for women aged 40 to 74 years. (B recommendation) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening mammography in women 75 years or older. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of supplemental screening for breast cancer using breast ultrasonography or MRI in women identified to have dense breasts on an otherwise negative screening mammogram. (I statement).

The distribution of breast density in women aged 18 years and older

PURPOSE

Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI.

METHODS

Breast density measures were estimated for 1,961 Australian women aged 18-97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI.

RESULTS

The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI.

CONCLUSION

This unique study describes the distribution of breast density measures for women aged 18-97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.

A bimodal nomogram as an adjunct tool to reduce unnecessary breast biopsy following discordant ultrasonic and mammographic BI-RADS assessment

OBJECTIVE

To develop a bimodal nomogram to reduce unnecessary biopsies in breast lesions with discordant ultrasound (US) and mammography (MG) Breast Imaging Reporting and Data System (BI-RADS) assessments.

METHODS

This retrospective study enrolled 706 women following opportunistic screening or diagnosis with discordant US and MG BI-RADS assessments (where one assessed a lesion as BI-RADS 4 or 5, while the other assessed the same lesion as BI-RADS 0, 2, or 3) from two medical centres between June 2019 and June 2021. Univariable and multivariable logistic regression analyses were used to develop the nomogram. DeLong's and McNemar's tests were used to assess the model's performance.

RESULTS

Age, MG features (margin, shape, and density in masses, suspicious calcifications, and architectural distortion), and US features (margin and shape in masses as well as calcifications) were independent risk factors for breast cancer. The nomogram obtained an area under the curve of 0.87 (95% confidence interval (CI), 0.83-0.91), 0.91 (95% CI, 0.87 - 0.96), and 0.92 (95% CI, 0.86-0.98) in the training, internal validation, and external testing samples, respectively, and demonstrated consistency in calibration curves. Coupling the nomogram with US reduced unnecessary biopsies from 74 to 44% and the missed malignancies rate from 13 to 2%. Similarly, coupling with MG reduced missed malignancies from 20 to 6%, and 63% of patients avoided unnecessary biopsies. Interobserver agreement between US and MG increased from - 0.708 (poor agreement) to 0.700 (substantial agreement) with the nomogram.

CONCLUSION

When US and MG BI-RADS assessments are discordant, incorporating the nomogram may improve the diagnostic accuracy, avoid unnecessary breast biopsies, and minimise missed diagnoses.

CLINICAL RELEVANCE STATEMENT

The nomogram developed in this study could be used as a computer program to assist radiologists with detecting breast cancer and ensuring more precise management and improved treatment decisions for breast lesions with discordant assessments in clinical practice.

KEY POINTS

• Coupling the nomogram with US and mammography improves the detection of breast cancers without the risk of unnecessary biopsy or missed malignancies. • The nomogram increases mammography and US interobserver agreement and enhances the consistency of decision-making. • The nomogram has the potential to be a computer program to assist radiologists in identifying breast cancer and making optimal decisions.

Breast Radiologists' Perceptions on the Detection and Management of Invasive Lobular Carcinoma: Most Agree Imaging Beyond Mammography Is Warranted

OBJECTIVE

To determine breast radiologists' confidence in detecting invasive lobular carcinoma (ILC) on mammography and the perceived need for additional imaging in screening and preoperative settings.

METHODS

A 16-item anonymized survey was developed, and IRB exemption obtained, by the Society of Breast Imaging (SBI) Patient Care and Delivery Committee and the Lobular Breast Cancer Alliance. The survey was emailed to 2946 radiologist SBI members on February 15, 2023. The survey recorded demographics, perceived modality-specific sensitivity for ILC to the nearest decile, and opinions on diagnosing ILC in screening and staging imaging. Five-point Likert scales were used (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree).

RESULTS

Response rate was 12.4% (366/2946). Perceived median (interquartile range) modality-specific sensitivities for ILC were MRI 90% (80-90), contrast-enhanced mammography 80% (70-90), molecular breast imaging 80% (60-90), digital breast tomosynthesis 70% (60-80), US 60% (50-80), and 2D mammography 50% (30-60). Only 25% (85/340) respondents were confident in detecting ILC on screening mammography in dense breasts, while 67% (229/343) were confident if breasts were nondense. Most agreed that supplemental screening is needed to detect ILC in women with dense breasts (272/344, 79%) or a personal history of ILC (248/341, 73%), with 34% (118/334) indicating that supplemental screening would also benefit women with nondense breasts. Most agreed that additional imaging is needed to evaluate extent of disease in women with newly diagnosed ILC, regardless of breast density (dense 320/329, 97%; nondense 263/329, 80%).

CONCLUSION

Most breast radiologists felt that additional imaging beyond mammography is needed to more confidently screen for and stage ILC.

Surgical and Radiology Trainees' Proficiency in Reading Mammograms: the Importance of Education for Cancer Localisation

Medical imaging with mammography plays a very important role in screening and diagnosis of breast cancer, Australia's most common female cancer. The visualisation of cancers on mammograms often forms a diagnosis and guidance for radiologists and breast surgeons, and education platforms that provide real cases in a simulated testing environment have been shown to improve observer performance for radiologists. This study reports on the performance of surgical and radiology trainees in locating breast cancers. An enriched test set of 20 mammography cases (6 cancer and 14 cancer free) was created, and 18 surgical trainees and 32 radiology trainees reviewed the cases via the Breast Screen Reader Assessment Strategy (BREAST) platform and marked any lesions identifiable. Further analysis of performance with high- and low-density cases was undertaken, and standard metrics including sensitivity and specificity. Radiology trainees performed significantly better than surgical trainees in terms of specificity (0.72 vs. 0.35; P < 0.01). No significant differences were observed between the surgical and radiology trainees in sensitivity or lesion sensitivity. Mixed results were obtained with participants regarding breast density, with higher density cases generally having lower performance. The higher specificity of the radiology trainees compared to the surgical trainees likely represents less exposure to negative mammography cases. The use of high-fidelity simulated self-test environments like BREAST is able to benchmark, understand and build strategies for improving cancer education in a safe environment, including identifying challenging scenarios like breast density for enhanced training.

Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study

Mammographic screening has contributed to a significant reduction in breast cancer mortality. Several studies have highlighted the correlation between breast density, as detected through mammography, and a higher likelihood of developing breast cancer. A polygenic risk score (PRS) is a numerical score that is calculated based on an individual's genetic information. This study aims to explore the potential roles of PRS as candidate markers for breast cancer development and investigate the genetic profiles associated with clinical characteristics in Asian females with dense breasts. This is a retrospective cohort study integrated breast cancer screening, population genotyping, and cancer registry database. The PRSs of the study cohort were estimated using genotyping data of 77 single nucleotide polymorphisms based on the PGS000001 Catalog. A subgroup analysis was conducted for females without breast symptoms. Breast cancer patients constituted a higher proportion of individuals in PRS Q4 (37.8% vs. 24.8% in controls). Among dense breast patients with no symptoms, the high PRS group (Q4) consistently showed a significantly elevated breast cancer risk compared to the low PRS group (Q1-Q3) in both univariate (OR = 2.25, 95% CI 1.43-3.50, P < 0.001) and multivariate analyses (OR: 2.23; 95% CI 1.41-3.48, P < 0.001). The study was extended to predict breast cancer risk using common low-penetrance risk variants in a PRS model, which could be integrated into personalized screening strategies for Taiwanese females with dense breasts without prominent symptoms.

Breast Cancer Detection Using a Low-Dose Positron Emission Digital Mammography System

Purpose To investigate the feasibility of low-dose positron emission mammography (PEM) concurrently to MRI to identify breast cancer and determine its local extent. Materials and Methods In this research ethics board-approved prospective study, participants newly diagnosed with breast cancer with concurrent breast MRI acquisitions were assigned independently of breast density, tumor size, and histopathologic cancer subtype to undergo low-dose PEM with up to 185 MBq of fluorine 18-labeled fluorodeoxyglucose (18F-FDG). Two breast radiologists, unaware of the cancer location, reviewed PEM images taken 1 and 4 hours following 18F-FDG injection. Findings were correlated with histopathologic results. Detection accuracy and participant details were examined using logistic regression and summary statistics, and a comparative analysis assessed the efficacy of PEM and MRI additional lesions detection (ClinicalTrials.gov: NCT03520218). Results Twenty-five female participants (median age, 52 years; range, 32-85 years) comprised the cohort. Twenty-four of 25 (96%) cancers (19 invasive cancers and five in situ diseases) were identified with PEM from 100 sets of bilateral images, showcasing comparable performance even after 3 hours of radiotracer uptake. The median invasive cancer size was 31 mm (range, 10-120). Three additional in situ grade 2 lesions were missed at PEM. While not significant, PEM detected fewer false-positive additional lesions compared with MRI (one of six [16%] vs eight of 13 [62%]; P = .14). Conclusion This study suggests the feasibility of a low-dose PEM system in helping to detect invasive breast cancer. Though large-scale clinical trials are essential to confirm these preliminary results, this study underscores the potential of this low-dose PEM system as a promising imaging tool in breast cancer diagnosis. ClinicalTrials.gov registration no. NCT03520218 Keywords: Positron Emission Digital Mammography, Invasive Breast Cancer, Oncology, MRI Supplemental material is available for this article. © RSNA, 2024 See also commentary by Barreto and Rapelyea in this issue.

Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density

BACKGROUND

Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts.

METHODS

We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy.

RESULTS

Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone.

CONCLUSION

MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.

Automated Breast Ultrasound Provides Comparable Diagnostic Performance in Opportunistic Screening and Diagnostic Assessment

OBJECTIVE

The aim of the work described here was to assess the performance of automated breast ultrasound (ABUS) as an adjunct to digital breast tomosynthesis (DBT) in the screening and diagnostic setting.

METHODS

This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.

RESULTS

A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.

CONCLUSION

ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.

Strategies enhancing the patient experience in mammography: A scoping review

INTRODUCTION

A positive experience in mammography is essential for increasing patient attendance and reattendance at these examinations, whether conducted for diagnostic or screening purposes. Mammograms indeed facilitate early disease detection, enhance the potential for cure, and consequently reduce breast cancer mortality. The main objective of this review was to identify and map the strategies aiming to improve the patient experience in diagnostic and screening mammography.

METHODS

This scoping review was performed following the JBI methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Searches were performed through databases of MEDLINE, Embase.com, CINAHL, APA PsycINFO, Cochrane Central Register of Controlled Trials, Web of Science, ProQuest Dissertation and Theses, and three clinical trial registries. This review considered studies evaluating the effect of interventions, occurring within the mammography department, on the patient experience.

RESULTS

The literature search yielded 8113 citations of which 60, matching the inclusion criteria, were included. The strategies were classified into eight categories. The most represented one was breast compression and positioning, followed by relaxation techniques and analgesic care, communication and information, screening equipment, examination procedures, patient-related factors, physical environment, and finally staff characteristics. The studied outcomes related to patient experience were mainly pain, anxiety, comfort, and satisfaction. Other types of outcomes were also considered in the studies such as image quality, technical parameters, or radiation dose. Most studies were conducted by radiographers, on female patients, and none mentioned the inclusion of male or transgender patients.

CONCLUSION

This review outlined a diversity of strategies to improve patient experience, although technique-based interventions were predominant. Further research is warranted, notably on psychological strategies, and on men and transgender people.

IMPLICATIONS FOR PRACTICE

This scoping review provides guidance to healthcare providers and services for better patient/client-centered care.

Supplemental Screening as an Adjunct to Mammography for Breast Cancer Screening in People With Dense Breasts: A Health Technology Assessment

Background

Screening with mammography aims to detect breast cancer before clinical symptoms appear. Among people with dense breasts, some cancers may be missed using mammography alone. The addition of supplemental imaging as an adjunct to screening mammography has been suggested to detect breast cancers missed on mammography, potentially reducing the number of deaths associated with the disease. We conducted a health technology assessment of supplemental screening with contrast-enhanced mammography, ultrasound, digital breast tomosynthesis (DBT), or magnetic resonance imaging (MRI) as an adjunct to mammography for people with dense breasts, which included an evaluation of effectiveness, harms, cost-effectiveness, the budget impact of publicly funding supplemental screening, the preferences and values of patients and health care providers, and ethical issues.

Methods

We performed a systematic literature search of the clinical evidence published from January 2015 to October 2021. We assessed the risk of bias of each included study using the Cochrane Risk of Bias or RoBANS tools, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature review and conducted cost-effectiveness analyses with a lifetime horizon from a public payer perspective. We also analyzed the budget impact of publicly funding supplemental screening as an adjunct to mammography for people with dense breasts in Ontario. To contextualize the potential value of supplemental screening for dense breasts, we spoke with people with dense breasts who had undergone supplemental screening; performed a rapid review of the qualitative literature; and conducted an ethical analysis of supplemental screening as an adjunct to mammography.

Results

We included eight primary studies in the clinical evidence review. No studies evaluated contrast-enhanced mammography. Nonrandomized and randomized evidence (GRADE: Very low to Moderate) suggests that mammography plus ultrasound was more sensitive and less specific, and detected more cancers compared to mammography alone. Fewer interval cancers occurred after mammography plus ultrasound (GRADE: Very low to Low), but recall rates were nearly double that of mammography alone (GRADE: Very low to Moderate). Evidence of Low to Very low quality suggested that compared with supplemental DBT, supplemental ultrasound was more sensitive, detected more cancers, and led to more recalls. Among people with extremely dense breasts, fewer interval cancers occurred after mammography plus supplemental MRI compared to mammography alone (GRADE: High). Supplemental MRI after negative mammography was highly accurate in people with extremely dense breasts and heterogeneously dense breasts in nonrandomized and randomized studies (GRADE: Very Low and Moderate). In people with extremely dense breasts, MRI after negative mammography detected 16.5 cancers per 1,000 screens (GRADE: Moderate), and up to 9.5% of all people screened were recalled (GRADE: Moderate). Contrast-related adverse events were infrequent (GRADE: Moderate). No study reported psychological impacts, breast cancer-specific mortality, or overall mortality.We included nine studies in the economic evidence, but none of the study findings was directly applicable to the Ontario context. Our lifetime cost-effectiveness analyses showed that supplemental screening with ultrasound, MRI, or DBT found more screen-detected cancers, decreased the number of interval cancers, had small gains in life-years or quality-adjusted life-years (QALYs), and was associated with savings in cancer management costs. However, supplemental screening also increased imaging costs and the number of false-positive cases. Compared to mammography alone, the incremental cost-effectiveness ratios (ICERs) for supplemental screening with handheld ultrasound, MRI, or DBT for people with dense breasts were $119,943, $314,170, and $212,707 per QALY gained, respectively. The ICERs for people with extremely dense breasts were $83,529, $101,813, and $142,730 per QALY gained, respectively. In sensitivity analyses, the diagnostic test sensitivity of mammography alone and of mammography plus supplemental screening had the greatest effect on ICER estimates. The total budget impact of publicly funding supplemental screening with handheld ultrasound, MRI, or DBT for people with dense breasts over the next 5 years is estimated at $15 million, $41 million, or $33 million, respectively. The corresponding total budget impact for people with extremely dense breasts is $4 million, $10 million, or $9 million.We engaged directly with 70 people via interviews and an online survey. The participants provided diverse perspectives on broad access to supplemental screening for people with dense breasts in Ontario. Themes discussed in the interviews included self-advocacy, patient-doctor partnership, preventive care, and a shared preference for broad access to screening modalities that are clinically effective in detecting breast cancer in people with dense breasts.We included 10 studies in the qualitative evidence rapid review. Thematic synthesis of these reports yielded three analytical themes: coming to know and understand breast density, which included introductions to and making sense of breast density; experiences of vulnerability, which influenced or were influenced by understandings and misunderstandings of breast density and responses to breast density; and choosing supplemental screening, which was influenced by knowledge and perception of the risks and benefits of supplemental screening, and the availability of resources.The ethics review determined that the main harms of supplemental screening for people with dense breasts are false-positives and overdiagnosis, both of which lead to unnecessary and burdensome health care treatments. Screening programs raise inherent tensions between individual- and population-level interests; they may yield population-level benefit, but are statistically of very little benefit to individuals. Entrenched cultural beliefs about the value of breast cancer screening, combined with uncertainty about the effects of supplemental screening on some outcomes and the discomfort of many health care providers in discussing screening options for people with dense breasts suggest that it may be difficult to ensure that patients can provide informed consent to engage in supplemental screening. Funding supplemental screening for people with dense breasts may lead to improved equity in the effectiveness of identifying cancers in people with dense breasts (compared to mammography alone), but it is not clear whether it would lead to equity in terms of improved survival and decreased morbidity.

Conclusions

Supplemental screening with ultrasound, DBT, or MRI as an adjunct to mammography detected more cancers and increased the number of recalls and biopsies, including false-positive results. Fewer interval cancers tended to occur after supplemental screening compared to mammography alone. It is unclear whether supplemental screening as an adjunct to mammography would reduce breast cancer-related or overall mortality among people with dense breasts.Supplemental screening with ultrasound, DBT, or MRI as an adjunct to mammography in people aged 50 to 74 years improved cancer detection but increased costs. Depending on the type of imaging modality, publicly funding supplemental screening in Ontario over the next 5 years would require additional total costs between $15 million and $41 million for people with dense breasts, and between $4 million and $10 million for people with extremely dense breasts.The people we engaged with directly valued the potential clinical benefits of supplemental screening and emphasized that patient education and equitable access should be a requirement for implementation in Ontario. Our review of the qualitative literature found that the concept of breast density is poorly understood, both by people with dense breasts and by some general practitioners. People with dense breasts who receive routine mammography (especially those who receive health care in their nonpreferred language or are perceived to have lower economic status or health literacy) and their general practitioners may not have the awareness or knowledge to make informed decisions about supplemental screening. Some people with dense breasts experienced emotional distress from barriers to accessing supplemental screening, and many wanted to engage in supplemental screening, even when educated about its potential harms, including false-positives and overdiagnosis.Given an overall lack of robust evidence about morbidity and mortality associated with supplemental screening for people with dense breasts, it is not possible to determine whether funding supplemental screening for dense breasts delivers on the ethical duties to maximize benefits and minimize harms for populations and individuals. It is likely that existing inequities in access to breast screening and cancer treatment will persist, even if supplemental screening for dense breasts is funded. Continued efforts to address these inequities by removing barriers to screening might mitigate this concern. It will be important to identify and minimize sources of uncertainty related to benefits and risks of supplemental screening for dense breasts to optimize the capacity for everyone involved to live up to their ethical obligations. Some of these may be resolved with further evidence related to the outcomes of supplemental screening for dense breasts.

Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act

Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.

Prediction of breast cancer risk for sisters of women attending screening

BACKGROUND

Risk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters.

METHODS

We included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively.

RESULTS

A higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively.

CONCLUSION

A woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.

Psychosocial outcomes and health service use after notifying women participating in population breast screening when they have dense breasts: a BreastScreen Queensland randomised controlled trial

BACKGROUND

Robust evidence regarding the benefits and harms of notifying Australian women when routine breast screening identifies that they have dense breasts is needed for informing future mammography population screening practice and policy.

OBJECTIVES

To assess the psychosocial and health services use effects of notifying women participating in population-based breast cancer screening that they have dense breasts; to examine whether the mode of communicating this information about its implications (print, online formats) influences these effects.

METHODS AND ANALYSIS

The study population comprises women aged 40 years or older who attend BreastScreen Queensland Sunshine Coast services for mammographic screening and are found to have dense breasts (BI-RADS density C or D). The randomised controlled trial includes three arms (952 women each): standard BreastScreen care (no notification of breast density; control arm); notification of dense breasts in screening results letter and print health literacy-sensitive information (intervention arm 1) or a link or QR code to online video-based health literacy-sensitive information (intervention arm 2). Baseline demographic data will be obtained from BreastScreen Queensland. Outcomes data will be collected in questionnaires at baseline and eight weeks, twelve months, and 27 months after breast screening. Primary outcomes will be psychological outcomes and health service use; secondary outcomes will be supplemental screening outcomes, cancer worry, perceived breast cancer risk, knowledge about breast density, future mammographic screening intentions, and acceptability of notification about dense breasts.

ETHICS APPROVAL

Gold Coast Hospital and Health Service Ethics Committee (HREC/2023/QGC/89770); Sunshine Coast Hospital and Health Service Research Governance and Development (SSA/2023/QSC/89770).

DISSEMINATION OF FINDINGS

Findings will be reported in peer-reviewed journals and at national and international conferences. They will also be reported to BreastScreen Queensland, BreastScreen Australia, Cancer Australia, and other bodies involved in cancer care and screening, including patient and support organisations.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12623000001695p (prospective: 9 January 2023).

Impact of Mammography Screening Frequency on Breast Cancer Mortality Rates

The frequency of mammography screening remains a topic of ongoing debate. This meta-analysis aimed to investigate the impact of annual vs. biennial mammography screenings on breast cancer mortality rates. A comprehensive search of relevant literature published up to 2021 was performed, with the primary outcome being the difference in breast cancer mortality rates between annual and biennial screenings. The extracted data included relative risks and 95% confidence intervals (CIs), with studies selected based on predetermined inclusion and exclusion criteria, emphasizing the quality of methodology and minimization of bias. Of the included studies, thirteen met the criteria, covering diverse demographic cohorts and screening frequencies. The synthesized data revealed a pattern of lower relative risk in annual screenings compared to biennial screenings across all studies. Notably, subgroup analyses indicated that age and racial background might modulate the effectiveness of screening frequency. In conclusion, this meta-analysis offers strong evidence suggesting that annual mammography screenings could be more effective than biennial screenings in reducing breast cancer mortality rates, especially in certain high-risk demographics. The results emphasize the importance of personalized, evidence-based approaches to mammography, with a call for future research to validate these findings and delve deeper into optimizing breast cancer screening strategies.

Impact of BMI on Prevalence of Dense Breasts by Race and Ethnicity

BACKGROUND

Density notification laws require notifying women of dense breasts with dense breast prevalence varying by race/ethnicity. We evaluated whether differences in body mass index (BMI) account for differences in dense breasts prevalence by race/ethnicity.

METHODS

Prevalence of dense breasts (heterogeneously or extremely dense) according to Breast Imaging Reporting and Data System and obesity (BMI > 30 kg/m2) were estimated from 2,667,207 mammography examinations among 866,033 women in the Breast Cancer Surveillance Consortium (BCSC) from January 2005 through April 2021. Prevalence ratios (PR) for dense breasts relative to overall prevalence by race/ethnicity were estimated by standardizing race/ethnicity prevalence in the BCSC to the 2020 U.S. population, and adjusting for age, menopausal status, and BMI using logistic regression.

RESULTS

Dense breasts were most prevalent among Asian women (66.0%) followed by non-Hispanic/Latina (NH) White (45.5%), Hispanic/Latina (45.3%), and NH Black (37.0%) women. Obesity was most prevalent in Black women (58.4%) followed by Hispanic/Latina (39.3%), NH White (30.6%), and Asian (8.5%) women. The adjusted prevalence of dense breasts was 19% higher [PR = 1.19; 95% confidence interval (CI), 1.19-1.20] in Asian women, 8% higher (PR = 1.08; 95% CI, 1.07-1.08) in Black women, the same in Hispanic/Latina women (PR = 1.00; 95% CI, 0.99-1.01), and 4% lower (PR = 0.96; 95% CI, 0.96-0.97) in NH White women relative to the overall prevalence.

CONCLUSIONS

Clinically important differences in breast density prevalence are present across racial/ethnic groups after accounting for age, menopausal status, and BMI.

IMPACT

If breast density is the sole criterion used to notify women of dense breasts and discuss supplemental screening it may result in implementing inequitable screening strategies across racial/ethnic groups. See related In the Spotlight, p. 1479.

Strategies for Mitigating Consequences of Federal Breast Density Notifications

This Viewpoint describes new federal updates to screening mammography rules and recommends strategies for mitigating potential consequences of the rules.

Breast cancer risk characteristics of women undergoing whole-breast ultrasound screening versus mammography alone

BACKGROUND

There are no consensus guidelines for supplemental breast cancer screening with whole-breast ultrasound. However, criteria for women at high risk of mammography screening failures (interval invasive cancer or advanced cancer) have been identified. Mammography screening failure risk was evaluated among women undergoing supplemental ultrasound screening in clinical practice compared with women undergoing mammography alone.

METHODS

A total of 38,166 screening ultrasounds and 825,360 screening mammograms without supplemental screening were identified during 2014-2020 within three Breast Cancer Surveillance Consortium (BCSC) registries. Risk of interval invasive cancer and advanced cancer were determined using BCSC prediction models. High interval invasive breast cancer risk was defined as heterogeneously dense breasts and BCSC 5-year breast cancer risk ≥2.5% or extremely dense breasts and BCSC 5-year breast cancer risk ≥1.67%. Intermediate/high advanced cancer risk was defined as BCSC 6-year advanced breast cancer risk ≥0.38%.

RESULTS

A total of 95.3% of 38,166 ultrasounds were among women with heterogeneously or extremely dense breasts, compared with 41.8% of 825,360 screening mammograms without supplemental screening (p < .0001). Among women with dense breasts, high interval invasive breast cancer risk was prevalent in 23.7% of screening ultrasounds compared with 18.5% of screening mammograms without supplemental imaging (adjusted odds ratio, 1.35; 95% CI, 1.30-1.39); intermediate/high advanced cancer risk was prevalent in 32.0% of screening ultrasounds versus 30.5% of screening mammograms without supplemental screening (adjusted odds ratio, 0.91; 95% CI, 0.89-0.94).

CONCLUSIONS

Ultrasound screening was highly targeted to women with dense breasts, but only a modest proportion were at high mammography screening failure risk. A clinically significant proportion of women undergoing mammography screening alone were at high mammography screening failure risk.

Mammography using low-frequency electromagnetic fields with deep learning

In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining images of the breast, low-frequency electromagnetic fields are leveraged. To capture breast impressions, a metasurface, which can be thought of as analogous to X-rays film, has been employed. To achieve deep and sufficient penetration within the breast tissues, the source of excitation is a simple narrow-band dipole antenna operating at 200 MHz. The metasurface is designed to operate at the same frequency. The detection mechanism is based on comparing the impressions obtained from the breast under examination to the reference case (healthy breasts) using machine learning techniques. Using this system, not only would it be possible to detect tumors (benign or malignant), but one can also determine the location and size of the tumors. Remarkably, deep learning models were found to achieve very high classification accuracy.

Analytic Hierarchy Process Analysis of Patient Preferences for Contrast-Enhanced Mammography Versus MRI as Supplemental Screening Options for Breast Cancer

OBJECTIVE

To guide implementation of supplemental breast screening by assessing patient preferences for contrast-enhanced mammography (CEM) versus MRI using analytic hierarchy process (AHP) methodology.

METHODS

In an institutional review board-approved, HIPAA-compliant protocol, from March 23 to June 3, 2022, we contacted 579 women who had both CEM screening and MRI. Women were e-mailed an invitation to complete an online survey developed using an AHP-based model to elicit preferences for CEM or MRI. Methods for categorical data analysis were used to evaluate factors affecting preferences, under the Bonferroni correction for multiplicity.

RESULTS

Complete responses were received from 222 (38.3%) women; the 189 women with a personal history of breast cancer had a mean age 61.8 years, and the 34 women without a personal history of breast cancer had a mean age of 53.6 years. Of 222 respondents, 157 (70.7%, confidence interval [CI]: 64.7-76.7) were determined to prefer CEM to MRI. Breast positioning was the most important criterion for 74 of 222 (33.3%) respondents, with claustrophobia, intravenous line placement, and overall stress most important for 38, 37, and 39 women (17.1%, 16.7%, and 17.6%), respectively, and noise level, contrast injection, and indifference being emphasized least frequently (by 10 [4.5%], 11 [5.0%], and 13 [5.9%] women, respectively). CEM preference was most prevalent (MRI least prevalent) for respondents emphasizing claustrophobia (37 of 38 [97%], CI: 86.2-99.9); CEM preference was least prevalent (MRI most prevalent) for respondents emphasizing breast positioning (40 of 74 [54%], CI: 42.1-65.7).

CONCLUSIONS

AHP-based modeling reveals strong patient preferences for CEM over MRI, with claustrophobia favoring preference for CEM and breast positioning relatively favoring preference for MRI. Our results should help guide implementation of screening CEM and MRI.

Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer

PURPOSE

Artificial intelligence (AI) algorithms improve breast cancer detection on mammography, but their contribution to long-term risk prediction for advanced and interval cancers is unknown.

METHODS

We identified 2,412 women with invasive breast cancer and 4,995 controls matched on age, race, and date of mammogram, from two US mammography cohorts, who had two-dimensional full-field digital mammograms performed 2-5.5 years before cancer diagnosis. We assessed Breast Imaging Reporting and Data System density, an AI malignancy score (1-10), and volumetric density measures. We used conditional logistic regression to estimate odds ratios (ORs), 95% CIs, adjusted for age and BMI, and C-statistics (AUC) to describe the association of AI score with invasive cancer and its contribution to models with breast density measures. Likelihood ratio tests (LRTs) and bootstrapping methods were used to compare model performance.

RESULTS

On mammograms between 2-5.5 years prior to cancer, a one unit increase in AI score was associated with 20% greater odds of invasive breast cancer (OR, 1.20; 95% CI, 1.17 to 1.22; AUC, 0.63; 95% CI, 0.62 to 0.64) and was similarly predictive of interval (OR, 1.20; 95% CI, 1.13 to 1.27; AUC, 0.63) and advanced cancers (OR, 1.23; 95% CI, 1.16 to 1.31; AUC, 0.64) and in dense (OR, 1.18; 95% CI, 1.15 to 1.22; AUC, 0.66) breasts. AI score improved prediction of all cancer types in models with density measures (PLRT values < .001); discrimination improved for advanced cancer (ie, AUC for dense volume increased from 0.624 to 0.679, Δ AUC 0.065, P = .01) but did not reach statistical significance for interval cancer.

CONCLUSION

AI imaging algorithms coupled with breast density independently contribute to long-term risk prediction of invasive breast cancers, in particular, advanced cancer.

Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study

Background Although several clinical breast cancer risk models are used to guide screening and prevention, they have only moderate discrimination. Purpose To compare selected existing mammography artificial intelligence (AI) algorithms and the Breast Cancer Surveillance Consortium (BCSC) risk model for prediction of 5-year risk. Materials and Methods This retrospective case-cohort study included data in women with a negative screening mammographic examination (no visible evidence of cancer) in 2016, who were followed until 2021 at Kaiser Permanente Northern California. Women with prior breast cancer or a highly penetrant gene mutation were excluded. Of the 324 009 eligible women, a random subcohort was selected, regardless of cancer status, to which all additional patients with breast cancer were added. The index screening mammographic examination was used as input for five AI algorithms to generate continuous scores that were compared with the BCSC clinical risk score. Risk estimates for incident breast cancer 0 to 5 years after the initial mammographic examination were calculated using a time-dependent area under the receiver operating characteristic curve (AUC). Results The subcohort included 13 628 patients, of whom 193 had incident cancer. Incident cancers in eligible patients (additional 4391 of 324 009) were also included. For incident cancers at 0 to 5 years, the time-dependent AUC for BCSC was 0.61 (95% CI: 0.60, 0.62). AI algorithms had higher time-dependent AUCs than did BCSC, ranging from 0.63 to 0.67 (Bonferroni-adjusted P < .0016). Time-dependent AUCs for combined BCSC and AI models were slightly higher than AI alone (AI with BCSC time-dependent AUC range, 0.66-0.68; Bonferroni-adjusted P < .0016). Conclusion When using a negative screening examination, AI algorithms performed better than the BCSC risk model for predicting breast cancer risk at 0 to 5 years. Combined AI and BCSC models further improved prediction. © RSNA, 2023 Supplemental material is available for this article.

Prospective Multicenter Diagnostic Performance of Technologist-Performed Screening Breast Ultrasound After Tomosynthesis in Women With Dense Breasts (the DBTUST)

PURPOSE

To assess diagnostic performance of digital breast tomosynthesis (DBT) alone or combined with technologist-performed handheld screening ultrasound (US) in women with dense breasts.

METHODS

In an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant multicenter protocol in western Pennsylvania, 6,179 women consented to three rounds of annual screening, interpreted by two radiologist observers, and had appropriate follow-up. Primary analysis was based on first observer results.

RESULTS

Mean participant age was 54.8 years (range, 40-75 years). Across 17,552 screens, there were 126 cancer events in 125 women (7.2/1,000; 95% CI, 5.9 to 8.4). In year 1, DBT-alone cancer yield was 5.0/1,000, and of DBT+US, 6.3/1,000, difference 1.3/1,000 (95% CI, 0.3 to 2.1; P = .005). In years 2 + 3, DBT cancer yield was 4.9/1,000, and of DBT+US, 5.9/1,000, difference 1.0/1,000 (95% CI, 0.4 to 1.5; P < .001). False-positive rate increased from 7.0% for DBT in year 1 to 11.5% for DBT+US and from 5.9% for DBT in year 2 + 3 to 9.7% for DBT+US (P < .001 for both). Nine cancers were seen only by double reading DBT and one by double reading US. Ten interval cancers (0.6/1,000 [95% CI, 0.2 to 0.9]) were identified. Despite reduction in specificity, addition of US improved receiver operating characteristic curves, with area under receiver operating characteristic curve increasing from 0.83 for DBT alone to 0.92 for DBT+US in year 1 (P = .01), with smaller improvements in subsequent years. Of 6,179 women, across all 3 years, 172/6,179 (2.8%) unique women had a false-positive biopsy because of DBT as did another 230/6,179 (3.7%) women because of US (P < .001).

CONCLUSION

Overall added cancer detection rate of US screening after DBT was modest at 19/17,552 (1.1/1,000; CI, 0.5- to 1.6) screens but potentially overcomes substantial increases in false-positive recalls and benign biopsies.

Breast Digital Tomosynthesis versus Contrast-Enhanced Mammography: Comparison of Diagnostic Application and Radiation Dose in a Screening Setting

This study aims to evaluate the Average Glandular Dose (AGD) and diagnostic performance of CEM versus Digital Mammography (DM) as well as versus DM plus one-view Digital Breast Tomosynthesis (DBT), which were performed in the same patients at short intervals of time. A preventive screening examination in high-risk asymptomatic patients between 2020 and 2022 was performed with two-view Digital Mammography (DM) projections (Cranio Caudal and Medio Lateral) plus one Digital Breast Tomosynthesis (DBT) projection (mediolateral oblique, MLO) in a single session examination. For all patients in whom we found a suspicious lesion by using DM + DBT, we performed (within two weeks) a CEM examination. AGD and compression force were compared between the diagnostic methods. All lesions identified by DM + DBT were biopsied; then, we assessed whether lesions found by DBT were also highlighted by DM alone and/or by CEM. We enrolled 49 patients with 49 lesions in the study. The median AGD was lower for DM alone than for CEM (3.41 mGy vs. 4.24 mGy, p = 0.015). The AGD for CEM was significantly lower than for the DM plus one single projection DBT protocol (4.24 mGy vs. 5.55 mGy, p < 0.001). We did not find a statistically significant difference in the median compression force between the CEM and DM + DBT. DM + DBT allows the identification of one more invasive neoplasm one in situ lesion and two high-risk lesions, compared to DM alone. The CEM, compared to DM + DBT, failed to identify only one of the high-risk lesions. According to these results, CEM could be used in the screening of asymptomatic high-risk patients.

Performance of Supplemental Imaging Modalities for Breast Cancer in Women With Dense Breasts: Findings From an Umbrella Review and Primary Studies Analysis

Breast cancer screening performance of supplemental imaging modalities by breast density and breast cancer risk has not been widely studied, and the optimal choice of modality for women with dense breasts remains unclear in clinical practice and guidelines. This systematic review aimed to assess breast cancer screening performance of supplemental imaging modalities for women with dense breasts, by breast cancer risk. Systematic reviews (SRs) in 2000 to 2021, and primary studies in 2019 to 2021, on outcomes of supplemental screening modalities (digital breast tomography [DBT], MRI (full/abbreviated protocol), contrast enhanced mammography (CEM), ultrasound (hand-held [HHUS]/automated [ABUS]) in women with dense breasts (BI-RADS C&D) were identified. None of the SRs analyzed outcomes by cancer risk. Meta-analysis of the primary studies was not feasible due to lack of studies (MRI, CEM, DBT) or methodological heterogeneity (ultrasound); therefore, findings were summarized narratively. For average risk, a single MRI trial reported a superior screening performance (higher cancer detection rate [CDR] and lower interval cancer rate [ICR]) compared to HHUS, ABUS and DBT. For intermediate risk, ultrasound was the only modality assessed, but accuracy estimates ranged widely. For mixed risk, a single CEM study reported the highest CDR, but included a high proportion of women with intermediate risk. This systematic review does not allow a complete comparison of supplemental screening modalities for dense breast populations by breast cancer risk. However, the data suggest that MRI and CEM might generally offer superior screening performance versus other modalities. Further studies of screening modalities are urgently required.

Mammography in combination with breast ultrasonography versus mammography for breast cancer screening in women at average risk

BACKGROUND

Screening mammography can detect breast cancer at an early stage. Supporters of adding ultrasonography to the screening regimen consider it a safe and inexpensive approach to reduce false-negative rates during screening. However, those opposed to it argue that performing supplemental ultrasonography will also increase the rate of false-positive findings and can lead to unnecessary biopsies and treatments.

OBJECTIVES

To assess the comparative effectiveness and safety of mammography in combination with breast ultrasonography versus mammography alone for breast cancer screening for women at average risk of breast cancer.

SEARCH METHODS

We searched the Cochrane Breast Cancer Group's Specialised Register, CENTRAL, MEDLINE, Embase, the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP), and ClinicalTrials.gov up until 3 May 2021.

SELECTION CRITERIA

For efficacy and harms, we considered randomised controlled trials (RCTs) and controlled non-randomised studies enrolling at least 500 women at average risk for breast cancer between the ages of 40 and 75. We also included studies where 80% of the population met our age and breast cancer risk inclusion criteria.

DATA COLLECTION AND ANALYSIS

Two review authors screened abstracts and full texts, assessed risk of bias, and applied the GRADE approach. We calculated the risk ratio (RR) with 95% confidence intervals (CI) based on available event rates. We conducted a random-effects meta-analysis.

MAIN RESULTS

We included eight studies: one RCT, two prospective cohort studies, and five retrospective cohort studies, enrolling 209,207 women with a follow-up duration from one to three years. The proportion of women with dense breasts ranged from 48% to 100%. Five studies used digital mammography; one study used breast tomosynthesis; and two studies used automated breast ultrasonography (ABUS) in addition to mammography screening. One study used digital mammography alone or in combination with breast tomosynthesis and ABUS or handheld ultrasonography. Six of the eight studies evaluated the rate of cancer cases detected after one screening round, whilst two studies screened women once, twice, or more. None of the studies assessed whether mammography screening in combination with ultrasonography led to lower mortality from breast cancer or all-cause mortality. High certainty evidence from one trial showed that screening with a combination of mammography and ultrasonography detects more breast cancer than mammography alone. The J-START (Japan Strategic Anti-cancer Randomised Trial), enrolling 72,717 asymptomatic women, had a low risk of bias and found that two additional breast cancers per 1000 women were detected over two years with one additional ultrasonography than with mammography alone (5 versus 3 per 1000; RR 1.54, 95% CI 1.22 to 1.94). Low certainty evidence showed that the percentage of invasive tumours was similar, with no statistically significant difference between the two groups (69.6% (128 of 184) versus 73.5% (86 of 117); RR 0.95, 95% CI 0.82 to 1.09). However, positive lymph node status was detected less frequently in women with invasive cancer who underwent mammography screening in combination with ultrasonography than in women who underwent mammography alone (18% (23 of 128) versus 34% (29 of 86); RR 0.53, 95% CI 0.33 to 0.86; moderate certainty evidence). Further, interval carcinomas occurred less frequently in the group screened by mammography and ultrasonography compared with mammography alone (5 versus 10 in 10,000 women; RR 0.50, 95% CI 0.29 to 0.89; 72,717 participants; high certainty evidence). False-negative results were less common when ultrasonography was used in addition to mammography than with mammography alone: 9% (18 of 202) versus 23% (35 of 152; RR 0.39, 95% CI 0.23 to 0.66; moderate certainty evidence). However, the number of false-positive results and necessary biopsies were higher in the group with additional ultrasonography screening. Amongst 1000 women who do not have cancer, 37 more received a false-positive result when they participated in screening with a combination of mammography and ultrasonography than with mammography alone (RR 1.43, 95% CI 1.37 to 1.50; high certainty evidence). Compared to mammography alone, for every 1000 women participating in screening with a combination of mammography and ultrasonography, 27 more women will have a biopsy (RR 2.49, 95% CI 2.28 to 2.72; high certainty evidence). Results from cohort studies with methodological limitations confirmed these findings. A secondary analysis of the J-START provided results from 19,213 women with dense and non-dense breasts. In women with dense breasts, the combination of mammography and ultrasonography detected three more cancer cases (0 fewer to 7 more) per 1000 women screened than mammography alone (RR 1.65, 95% CI 1.0 to 2.72; 11,390 participants; high certainty evidence). A meta-analysis of three cohort studies with data from 50,327 women with dense breasts supported this finding, showing that mammography and ultrasonography combined led to statistically significantly more diagnosed cancer cases compared to mammography alone (RR 1.78, 95% CI 1.23 to 2.56; 50,327 participants; moderate certainty evidence). For women with non-dense breasts, the secondary analysis of the J-START study demonstrated that more cancer cases were detected when adding ultrasound to mammography screening compared to mammography alone (RR 1.93, 95% CI 1.01 to 3.68; 7823 participants; moderate certainty evidence), whilst two cohort studies with data from 40,636 women found no statistically significant difference between the two screening methods (RR 1.13, 95% CI 0.85 to 1.49; low certainty evidence).

AUTHORS' CONCLUSIONS

Based on one study in women at average risk of breast cancer, ultrasonography in addition to mammography leads to more screening-detected breast cancer cases. For women with dense breasts, cohort studies more in line with real-life clinical practice confirmed this finding, whilst cohort studies for women with non-dense breasts showed no statistically significant difference between the two screening interventions. However, the number of false-positive results and biopsy rates were higher in women receiving additional ultrasonography for breast cancer screening. None of the included studies analysed whether the higher number of screen-detected cancers in the intervention group resulted in a lower mortality rate compared to mammography alone. Randomised controlled trials or prospective cohort studies with a longer observation period are needed to assess the effects of the two screening interventions on morbidity and mortality.

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

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

Breast Density and Breast Cancer Screening with Digital Breast Tomosynthesis: A TOSYMA Trial Subanalysis

Background Digital breast tomosynthesis (DBT) plus synthesized mammography (SM) reduces the diagnostic pitfalls of tissue superimposition, which is a limitation of digital mammography (DM). Purpose To compare the invasive breast cancer detection rate (iCDR) of DBT plus SM versus DM screening for different breast density categories. Materials and Methods An exploratory subanalysis of the TOmosynthesis plus SYnthesized MAmmography (TOSYMA) study, a randomized, controlled, multicenter, parallel-group trial recruited within the German mammography screening program from July 2018 to December 2020. Women aged 50-69 years were randomly assigned (1:1) to DBT plus SM or DM screening examination. Breast density categories A-D were visually assessed according to the Breast Imaging Reporting and Data System Atlas. Exploratory analyses were performed of the iCDR in both study arms and stratified by breast density, and odds ratios and 95% CIs were determined. Results A total of 49 762 women allocated to DBT plus SM and 49 796 allocated to DM (median age, 57 years [IQR, 53-62 years]) were included. In the DM arm, the iCDR was 3.6 per 1000 screening examinations in category A (almost entirely fatty) (16 of 4475 screenings), 4.3 in category B (102 of 23 534 screenings), 6.1 in category C (116 of 19 051 screenings), and 2.3 in category D (extremely dense breasts) (six of 2629 screenings). The iCDR in the DBT plus SM arm was 2.7 per 1000 screening examinations in category A (12 of 4439 screenings), 6.9 in category B (154 of 22 328 screenings), 8.3 in category C (156 of 18 772 screenings), and 8.1 in category D (32 of 3940 screenings). The odds ratio for DM versus DBT plus SM in category D was 3.8 (95% CI: 1.5, 11.1). The invasive cancers detected with DBT plus SM were most often grade 2 tumors; in category C, it was 58% (91 of 156 invasive cancers), and in category D, it was 47% (15 of 32 invasive cancers). Conclusion The TOmosynthesis plus SYnthesized MAmmography trial revealed higher invasive cancer detection rates with digital breast tomosynthesis plus synthesized mammography than digital mammography in dense breasts, relatively and absolutely most marked among women with extremely dense breasts. ClinicalTrials.gov registration no.: NCT03377036 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Lee and Moy in this issue.

High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection

Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance since dense tissues can mask or even simulate masses. Therefore, the sensitivity of mammography for breast cancer detection can be reduced by more than 20% in dense breasts. Additionally, extremely dense cases reported an increased risk of cancer compared to low-density breasts. This study aims to improve the mass detection performance in high-density breasts using synthetic high-density full-field digital mammograms (FFDM) as data augmentation during breast mass detection model training. To this end, a total of five cycle-consistent GAN (CycleGAN) models using three FFDM datasets were trained for low-to-high-density image translation in high-resolution mammograms. The training images were split by breast density BI-RADS categories, being BI-RADS A almost entirely fatty and BI-RADS D extremely dense breasts. Our results showed that the proposed data augmentation technique improved the sensitivity and precision of mass detection in models trained with small datasets and improved the domain generalization of the models trained with large databases. In addition, the clinical realism of the synthetic images was evaluated in a reader study involving two expert radiologists and one surgical oncologist.

Feasibility Study and Clinical Impact of Incorporating Breast Tissue Density in High-Risk Breast Cancer Screening Assessment

Breast tissue density (BTD) is known to increase the risk of breast cancer but is not routinely used in the risk assessment of the population-based High-Risk Ontario Breast Screening Program (HROBSP). This prospective, IRB-approved study assessed the feasibility and impact of incorporating breast tissue density (BTD) into the risk assessment of women referred to HROBSP who were not genetic mutation carriers. All consecutive women aged 40-69 years who met criteria for HROBSP assessment and referred to Genetics from 1 December 2020 to 31 July 2021 had their lifetime risk calculated with and without BTD using Tyrer-Cuzick model version 8 (IBISv8) to gauge overall impact. McNemar's test was performed to compare eligibility with and without density. 140 women were referred, and 1 was excluded (BRCA gene mutation carrier and automatically eligible). Eight of 139 (5.8%) never had a mammogram, while 17/131 (13%) did not have BTD reported on their mammogram and required radiologist review. Of 131 patients, 22 (16.8%) were clinically impacted by incorporation of BTD: 9/131 (6.9%) became eligible for HROBSP, while 13/131 (9.9%) became ineligible (p = 0.394). It was feasible for the Genetics clinic to incorporate BTD for better risk stratification of eligible women. This did not significantly impact the number of eligible women while optimizing the use of high-risk supplemental MRI screening.

Opinions on the Assessment of Breast Density Among Members of the Society of Breast Imaging

OBJECTIVE

Dense breast decreases the sensitivity and specificity of mammography and is associated with an increased risk of breast cancer. We conducted a survey to assess the opinions of Society of Breast Imaging (SBI) members regarding density assessment.

METHODS

An online survey was sent to SBI members twice in September 2020. The survey included active members who were practicing radiologists, residents, and fellows. Mammograms from three patients were presented for density assessment based on routine clinical practice and BI-RADS fourth and fifth editions. Dense breasts were defined as heterogeneously or extremely dense. Frequencies were calculated for each survey response. Pearson's correlation coefficient was used to evaluate the correlation of density assessments by different definitions.

RESULTS

The survey response rate was 12.4% (357/2875). For density assessments, the Pearson correlation coefficients between routine clinical practice and BI-RADS fourth edition were 0.05, 0.43, and 0.12 for patients 1, 2, and 3, respectively; these increased to 0.65, 0.65, and 0.66 between routine clinical practice and BI-RADS fifth edition for patients 1, 2, and 3, respectively. For future density grading, 79.0% (282/357) of respondents thought it should reflect both potential for masking and overall dense tissue for risk assessment. Additionally, 47.1% (168/357) of respondents thought quantitative methods were of use.

CONCLUSION

Density assessment varied based on routine clinical practice and BI-RADS fourth and fifth editions. Most breast radiologists agreed that density assessment should capture both masking and overall density. Moreover, almost half of respondents believed computer or artificial intelligence-assisted quantitative methods may help refine density assessment.

External Validation of a Mammography-Derived AI-Based Risk Model in a U.S. Breast Cancer Screening Cohort of White and Black Women

Despite the demonstrated potential of artificial intelligence (AI) in breast cancer risk assessment for personalizing screening recommendations, further validation is required regarding AI model bias and generalizability. We performed external validation on a U.S. screening cohort of a mammography-derived AI breast cancer risk model originally developed for European screening cohorts. We retrospectively identified 176 breast cancers with exams 3 months to 2 years prior to cancer diagnosis and a random sample of 4963 controls from women with at least one-year negative follow-up. A risk score for each woman was calculated via the AI risk model. Age-adjusted areas under the ROC curves (AUCs) were estimated for the entire cohort and separately for White and Black women. The Gail 5-year risk model was also evaluated for comparison. The overall AUC was 0.68 (95% CIs 0.64−0.72) for all women, 0.67 (0.61−0.72) for White women, and 0.70 (0.65−0.76) for Black women. The AI risk model significantly outperformed the Gail risk model for all women p < 0.01 and for Black women p < 0.01, but not for White women p = 0.38. The performance of the mammography-derived AI risk model was comparable to previously reported European validation results; non-significantly different when comparing White and Black women; and overall, significantly higher than that of the Gail model.

Addressing Misinformation About the Canadian Breast Screening Guidelines

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

Breast Cancer in Asia: Incidence, Mortality, Early Detection, Mammography Programs, and Risk-Based Screening Initiatives

Close to half (45.4%) of the 2.3 million breast cancers (BC) diagnosed in 2020 were from Asia. While the burden of breast cancer has been examined at the level of broad geographic regions, literature on more in-depth coverage of the individual countries and subregions of the Asian continent is lacking. This narrative review examines the breast cancer burden in 47 Asian countries. Breast cancer screening guidelines and risk-based screening initiatives are discussed.

Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications

Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.

Australian General Practitioners' Current Knowledge, Understanding, and Feelings Regarding Breast Density Information and Notification: A Cross-Sectional Study

BACKGROUND

There is a lack of evidence around Australian general practitioners' (GPs) views of issues surrounding breast density. The current study aimed to quantitatively assess GPs' current knowledge, understanding, and feelings around breast density information and notification.

METHODS

This study involved a cross-sectional survey using an online platform to collect quantitative data from Australian GPs. Survey data were analysed with descriptive statistics.

RESULTS

A total 60 responses from GPs were analysed. Most (n = 58; 97%) had heard or read about breast density and nearly 90% (n = 52; 87%) have had discussions about breast density with patients. Three-quarters (n = 45; 75%) were supportive of making breast density notification mandatory for patients with dense tissue and a similar proportion (n = 45/58; 78%) felt they need or want more education on breast density.

CONCLUSIONS

There is strong support for notifying patients of breast density, and interest in further education and training among the surveyed GPs. As GPs play a central role in cancer prevention and control, their involvement in discussions related to breast density notification, evaluation and appraisal of evidence, development of communication strategies, and participation in ongoing research on the topic will be indispensable.

Association of Screening With Digital Breast Tomosynthesis vs Digital Mammography With Risk of Interval Invasive and Advanced Breast Cancer

Importance

Digital breast tomosynthesis (DBT) was developed with the expectation of improving cancer detection in women with dense breasts. Studies are needed to evaluate interval invasive and advanced breast cancer rates, intermediary outcomes related to breast cancer mortality, by breast density and breast cancer risk.

Objective

To evaluate whether DBT screening is associated with a lower likelihood of interval invasive cancer and advanced breast cancer compared with digital mammography by extent of breast density and breast cancer risk.

Design, Setting, and Participants

Cohort study of 504 427 women aged 40 to 79 years who underwent 1 003 900 screening digital mammography and 375 189 screening DBT examinations from 2011 through 2018 at 44 US Breast Cancer Surveillance Consortium (BCSC) facilities with follow-up for cancer diagnoses through 2019 by linkage to state or regional cancer registries.

Exposures

Breast Imaging Reporting and Data System (BI-RADS) breast density; BCSC 5-year breast cancer risk.

Main Outcomes and Measures

Rates per 1000 examinations of interval invasive cancer within 12 months of screening mammography and advanced breast cancer (prognostic pathologic stage II or higher) within 12 months of screening mammography, both estimated with inverse probability weighting.

Results

Among 504 427 women in the study population, the median age at time of mammography was 58 years (IQR, 50-65 years). Interval invasive cancer rates per 1000 examinations were not significantly different for DBT vs digital mammography (overall, 0.57 vs 0.61, respectively; difference, -0.04; 95% CI, -0.14 to 0.06; P = .43) or among all the 836 250 examinations with BCSC 5-year risk less than 1.67% (low to average-risk) or all the 413 061 examinations with BCSC 5-year risk of 1.67% or higher (high risk) across breast density categories. Advanced cancer rates were not significantly different for DBT vs digital mammography among women at low to average risk or at high risk with almost entirely fatty, scattered fibroglandular densities, or heterogeneously dense breasts. Advanced cancer rates per 1000 examinations were significantly lower for DBT vs digital mammography for the 3.6% of women with extremely dense breasts and at high risk of breast cancer (13 291 examinations in the DBT group and 31 300 in the digital mammography group; 0.27 vs 0.80 per 1000 examinations; difference, -0.53; 95% CI, -0.97 to -0.10) but not for women at low to average risk (10 611 examinations in the DBT group and 37 796 in the digital mammography group; 0.54 vs 0.42 per 1000 examinations; difference, 0.12; 95% CI, -0.09 to 0.32).

Conclusions and Relevance

Screening with DBT vs digital mammography was not associated with a significant difference in risk of interval invasive cancer and was associated with a significantly lower risk of advanced breast cancer among the 3.6% of women with extremely dense breasts and at high risk of breast cancer. No significant difference was observed in the 96.4% of women with nondense breasts, heterogeneously dense breasts, or with extremely dense breasts not at high risk.

Australian Women's Intentions and Psychological Outcomes Related to Breast Density Notification and Information: A Randomized Clinical Trial

IMPORTANCE

Whether the benefits of notifying women about breast density outweigh the potential harms to inform current and future mammogram screening practice remains unknown.

OBJECTIVE

To assess the effect of mammographic breast density notification and information provision on women's intention to seek supplemental screening and psychological outcomes.

DESIGN, SETTING, AND PARTICIPANTS

A 3-arm online randomized clinical trial was conducted from August 10 to 31, 2021. Data analysis was conducted from September 1 to October 20, 2021. Participants included Australian residents identifying as female, aged between 40 and 74 years, with no history of breast cancer who were residing in jurisdictions without existing breast density notification with screening mammograms.

INTERVENTIONS

Women were randomized to receive 1 of the following hypothetical breast screening test result letters: screening mammogram result letter without breast density messaging (control), screening mammogram result letter with breast density messaging and an existing density information letter taken from a screening service in Australia (intervention 1), and screening mammogram result letter with breast density messaging and a health literacy-sensitive version of the letter adapted for people with lower health literacy (intervention 2).

MAIN OUTCOMES AND MEASURES

Primary outcomes were intention to seek supplemental screening; feeling anxious (uneasy, worried, or nervous), informed, or confused; and having breast cancer worry.

RESULTS

A total of 1420 Australian women were randomized and included in the final analysis. The largest group consisted of 603 women aged 60 to 74 years (42.5%). Compared with the control cohort (n = 480), women who received density notification via intervention 1 (n = 470) and intervention 2 (n = 470) reported a significantly higher intention to seek supplemental screening (0.8% vs 15.6% and 14.2%; P < .001) and feeling anxious (14.2% vs 49.4% and 48.5%; P < .001), confusion (7.8% vs 24.0% and 23.6%; P < .001), and worry about breast cancer (quite/very worried: 6.9% vs 17.2% and 15.5%; P < .001). There were no statistically significant differences in these outcomes between the 2 intervention groups.

CONCLUSIONS AND RELEVANCE

In this randomized clinical trial, breast density notification and information integrated with screening mammogram results increased women's intention to seek supplemental screening and made women feel anxious, confused, or worried about breast cancer. These findings have relevance and implications for mammogram screening services and policy makers considering whether and, if so, how best to implement widespread notification of breast density as part of mammography screening.

TRIAL REGISTRATION

ACTRN12621000253808.