The coronavirus disease 2019 (COVID-19) pandemic led to a near-total cessation of mammography services in the United States in mid-March 2020. It is unclear if screening and diagnostic mammography ...volumes have recovered to prepandemic levels and whether use has varied by women's characteristics.
We collected data on 461 083 screening mammograms and 112 207 diagnostic mammograms conducted during January 2019 through July 2020 at 62 radiology facilities in the Breast Cancer Surveillance Consortium. We compared monthly screening and diagnostic mammography volumes before and during the pandemic stratified by age, race and ethnicity, breast density, and family history of breast cancer.
Screening and diagnostic mammography volumes in April 2020 were 1.1% (95% confidence interval CI = 0.5% to 2.4%) and 21.4% (95% CI = 18.7% to 24.4%) of the April 2019 prepandemic volumes, respectively, but by July 2020 had rebounded to 89.7% (95% CI = 79.6% to 101.1%) and 101.6% (95% CI = 93.8% to 110.1%) of the July 2019 prepandemic volumes, respectively. The year-to-date cumulative volume of screening and diagnostic mammograms performed through July 2020 was 66.2% (95% CI = 60.3% to 72.6%) and 79.9% (95% CI = 75.4% to 84.6%), respectively, of year-to-date volume through July 2019. Screening mammography rebound was similar across age groups and by family history of breast cancer. Monthly screening mammography volume in July 2020 for Black, White, Hispanic, and Asian women reached 96.7% (95% CI = 88.1% to 106.1%), 92.9% (95% CI = 82.9% to 104.0%), 72.7% (95% CI = 56.5% to 93.6%), and 51.3% (95% CI = 39.7% to 66.2%) of the July 2019 prepandemic volume, respectively.
Despite a strong overall rebound in mammography volume by July 2020, the rebound lagged among Asian and Hispanic women, and a substantial cumulative deficit in missed mammograms accumulated, which may have important health consequences.
About half of the United States has legislation requiring radiology facilities to disclose mammographic breast density information to women, often with language recommending discussion of ...supplemental screening options for women with dense breasts.
To examine variation in breast density assessment across radiologists in clinical practice.
Cross-sectional and longitudinal analyses of prospectively collected observational data.
30 radiology facilities within the 3 breast cancer screening research centers of the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium.
Radiologists who interpreted at least 500 screening mammograms during 2011 to 2013 (n = 83). Data on 216 783 screening mammograms from 145 123 women aged 40 to 89 years were included.
Mammographic breast density, as clinically recorded using the 4 Breast Imaging Reporting and Data System categories (heterogeneously dense and extremely dense categories were considered "dense" for analyses), and patient age, race, and body mass index (BMI).
Overall, 36.9% of mammograms were rated as showing dense breasts. Across radiologists, this percentage ranged from 6.3% to 84.5% (median, 38.7% interquartile range, 28.9% to 50.9%), with multivariable adjustment for patient characteristics having little effect (interquartile range, 29.9% to 50.8%). Examination of patient subgroups revealed that variation in density assessment across radiologists was pervasive in all but the most extreme patient age and BMI combinations. Among women with consecutive mammograms interpreted by different radiologists, 17.2% (5909 of 34 271) had discordant assessments of dense versus nondense status.
Quantitative measures of mammographic breast density were not available for comparison.
There is wide variation in density assessment across radiologists that should be carefully considered by providers and policymakers when considering supplemental screening strategies. The likelihood of a woman being told she has dense breasts varies substantially according to which radiologist interprets her mammogram.
National Institutes of Health.
The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, ...visual classification of such changes is subjective and non-quantitative, limiting its diagnostic utility. To gain insights into stromal changes associated with breast cancer, we applied automated machine learning techniques to digital images of 2387 hematoxylin and eosin stained tissue sections of benign and malignant image-guided breast biopsies performed to investigate mammographic abnormalities among 882 patients, ages 40–65 years, that were enrolled in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project. Using deep convolutional neural networks, we trained an algorithm to discriminate between stroma surrounding invasive cancer and stroma from benign biopsies. In test sets (928 whole-slide images from 330 patients), this algorithm could distinguish biopsies diagnosed as invasive cancer from benign biopsies solely based on the stromal characteristics (area under the receiver operator characteristics curve = 0.962). Furthermore, without being trained specifically using ductal carcinoma in situ as an outcome, the algorithm detected tumor-associated stroma in greater amounts and at larger distances from grade 3 versus grade 1 ductal carcinoma in situ. Collectively, these results suggest that algorithms based on deep convolutional neural networks that evaluate only stroma may prove useful to classify breast biopsies and aid in understanding and evaluating the biology of breast lesions.
To evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk.
We ...examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression.
Among 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80%
66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio HR, 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (
= .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05).
BPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.
Breast cancer is the most common cancer and the second most common cause of cancer mortality among women in the United States. Efforts to promote breast cancer control in rural settings face specific ...challenges. Access to breast cancer screening, diagnosis, and treatment services is impaired by shortages of primary care and specialist providers, and geographic distance from medical facilities. Women in rural areas have comparable breast cancer mortality rates compared to women in urban settings, but this is due in large part to lower incidence rates and masks a substantial rural/urban disparity in breast cancer survival among women diagnosed with breast cancer. Mammography screening utilization rates are slightly lower among rural women than their urban counterparts, with a corresponding increase in late stage breast cancer. Differences in breast cancer survival persist after controlling for stage at diagnosis, largely due to disparities in access to treatment. Travel distance to treatment centers is the most substantial barrier to improved breast cancer outcomes in rural areas. While numerous interventions have been demonstrated in controlled studies to be effective in promoting treatment access and adherence, widespread dissemination in public health and clinical practice remains lacking. Efforts to improve breast cancer control in rural areas should focus on implementation strategies for improving access to breast cancer treatments.
•Rural women living have lower incidence of breast cancer compared to women in urban areas.•Rural women have lower use of screening mammography and are more likely to have a late stage breast cancer diagnosis.•Women in rural areas experience substantial barriers to accessing high quality diagnostic care and treatments.•Initiatives to improve access to guideline concordant treatments and survivorship care in rural areas are needed.
Digital breast tomosynthesis (DBT) is emerging as the new standard of care for breast cancer screening based on improved cancer detection coupled with reductions in recall compared to screening with ...digital mammography (DM) alone. However, many prior studies lack follow-up data to assess false negatives examinations. The purpose of this study is to assess if DBT is associated with improved screening outcomes based on follow-up data from tumor registries or pathology. Retrospective analysis of prospective cohort data from three research centers performing DBT screening in the PROSPR consortium from 2011 to 2014 was performed. Recall and biopsy rates were assessed from 198,881 women age 40–74 years undergoing screening (142,883 DM and 55,998 DBT examinations). Cancer, cancer detection, and false negative rates and positive predictive values were assessed on examinations with one year of follow-up. Logistic regression was used to compare DBT to DM adjusting for research center, age, prior breast imaging, and breast density. There was a reduction in recall with DBT compared to DM (8.7 vs. 10.4 %,
p
< 0.0001), with adjusted OR = 0.68 (95 % CI = 0.65–0.71). DBT demonstrated a statistically significant increase in cancer detection over DM (5.9 vs. 4.4/1000 screened, adjusted OR = 1.45, 95 % CI = 1.12–1.88), an improvement in PPV1 (6.4 % for DBT vs. 4.1 % for DM, adjusted OR = 2.02, 95 % CI = 1.54–2.65), and no significant difference in false negative rates for DBT compared to DM (0.46 vs. 0.60/1000 screened,
p
= 0.347). Our data support implementation of DBT screening based on increased cancer detection, reduced recall, and no difference in false negative screening examinations.
Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast ...stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established.
Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm
)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section.
Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p < 0.001) and with local percent mammographic density volume at both the biopsy target (p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p < 0.05).
Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.
Annual surveillance mammography is recommended for breast cancer survivors on the basis of observational studies and meta-analyses showing reduced breast cancer mortality and improved quality of ...life. However, breast cancer survivors are at higher risk of subsequent breast cancer and have a fourfold increased risk of interval breast cancers compared with individuals without a personal history of breast cancer. Supplemental surveillance modalities offer increased cancer detection compared with mammography alone, but utilization is variable, and benefits must be balanced with possible harms of false-positive findings. In this review, we describe the current state of mammographic surveillance, summarize evidence for supplemental surveillance in breast cancer survivors, and explore a risk-based approach to selecting surveillance imaging strategies. Further research identifying predictors associated with increased risk of interval second breast cancers and development of validated risk prediction tools may help physicians and patients weigh the benefits and harms of surveillance breast imaging and decide on a personalized approach to surveillance for improved breast cancer outcomes.
PDF
