Factors Associated with Longitudinal Changes in Mammographic Density in a Multiethnic Breast Screening Cohort of Postmenopausal Women.

Background: Breast density is an important risk factor for breast cancer and is known to be associated with characteristics such as age, race, and hormone levels; however, it is unclear what factors contribute to changes in breast density in postmenopausal women over time. Understanding factors associated with density changes may enable a better understanding of breast cancer risk and facilitate potential strategies for prevention. Methods: This study investigated potential associations between personal factors and changes in mammographic density in a cohort of 3,392 postmenopausal women with no personal history of breast cancer between 2011 and 2017. Self-reported information on demographics, breast and reproductive history, and lifestyle factors, including body mass index (BMI), alcohol intake, smoking, and physical activity, was collected by an electronic intake form, and breast imaging reporting and database system (BI-RADS) mammographic density scores were obtained from electronic medical records. Factors associated with a longitudinal increase or decrease in mammographic density were identified using Fisher's exact test and multivariate conditional logistic regression. Results: 7.9% of women exhibited a longitudinal decrease in mammographic density, 6.7% exhibited an increase, and 85.4% exhibited no change. Longitudinal changes in mammographic density were correlated with age, race/ethnicity, and age at menopause in the univariate analysis. In the multivariate analysis, Asian women were more likely to exhibit a longitudinal increase in mammographic density and less likely to exhibit a decrease compared to White women. On the other hand, obese women were less likely to exhibit an increase and more likely to exhibit a decrease compared to normal weight women. Women who underwent menopause at age 55 years or older were less likely to exhibit a decrease in mammographic density compared to women who underwent menopause at a younger age. Besides obesity, lifestyle factors (alcohol intake, smoking, and physical activity) were not associated with longitudinal changes in mammographic density. Conclusions: The associations we observed between Asian race/obesity and longitudinal changes in BI-RADS density in postmenopausal women are paradoxical in that breast cancer risk is lower in Asian women and higher in obese women. However, the association between later age at menopause and a decreased likelihood of decreasing in BI-RADS density over time is consistent with later age at menopause being a risk factor for breast cancer and suggests a potential relationship between greater cumulative lifetime estrogen exposure and relative stability in breast density after menopause. Our findings support the complexity of the relationships between breast density, BMI, hormone exposure, and breast cancer risk.

Impact of the COVID-19 Pandemic on Breast Imaging Education.

OBJECTIVE: To determine the impact of the COVID-19 pandemic on breast imaging education. METHODS: A 22-item survey addressing four themes during the early pandemic (time on service, structured education, clinical training, future plans) was emailed to Society of Breast Imaging members and members-in-training in July 2020. Responses were compared using McNemar's and Mann-Whitney U tests; a general linear model was used for multivariate analysis. RESULTS: Of 136 responses (136/2824, 4.8%), 96 U.S. responses from radiologists with trainees, residents, and fellows were included. Clinical exposure declined during the early pandemic, with almost no medical students on service (66/67, 99%) and fewer clinical days for residents (78/89, 88%) and fellows (48/68, 71%). Conferences shifted to remote live format (57/78, 73%), with some canceled (15/78, 19%). Compared to pre-pandemic, resident diagnostic (75/78, 96% vs 26/78, 33%) (P < 0.001) and procedural (73/78, 94% vs 21/78, 27%) (P < 0.001) participation fell, as did fellow diagnostic (60/61, 98% vs 47/61, 77%) (P = 0.001) and procedural (60/61, 98% vs 43/61, 70%) (P < 0.001) participation. Most thought that the pandemic negatively influenced resident and fellow screening (64/77, 83% and 43/60, 72%, respectively), diagnostic (66/77, 86% and 37/60, 62%), and procedural (71/77, 92% and 37/61, 61%) education. However, a majority thought that decreased time on service (36/67, 54%) and patient contact (46/79, 58%) would not change residents' pursuit of a breast imaging fellowship. CONCLUSION: The pandemic has had a largely negative impact on breast imaging education, with reduction in exposure to all aspects of breast imaging. However, this may not affect career decisions.

Adaptations of Breast Imaging Centers to the COVID-19 Pandemic: A Survey of California and Texas.

OBJECTIVE: To determine the early impact of the COVID-19 pandemic on breast imaging centers in California and Texas and compare regional differences. METHODS: An 11-item survey was emailed to American College of Radiology accredited breast imaging facilities in California and Texas in August 2020. A question subset addressed March-April government restrictions on elective services ("during the shutdown" and "after reopening"). Comparisons were made between states with chi-square and Fisher's tests, and timeframes with McNemar's and paired t-tests. RESULTS: There were 54 respondents (54/240, 23%, 26 California, 28 Texas). Imaging volumes fell during the shutdown and remained below pre-pandemic levels after reopening, with reduction in screening greatest (ultrasound 12% of baseline, mammography 13%, MRI 23%), followed by diagnostic MRI (43%), procedures (44%), and diagnostics (45%). California reported higher volumes during the shutdown (procedures, MRI) and after reopening (diagnostics, procedures, MRI) versus Texas (P = 0.001-0.02). Most screened patients (52/54, 96% symptoms and 42/54, 78% temperatures), and 100% (53/53) modified check-in and check-out. Reading rooms or physician work were altered for social distancing (31/54, 57%). Physician mask (45/48, 94%), gown (15/48, 31%), eyewear (22/48, 46%), and face shield (22/48, 46%) use during procedures increased after reopening versus pre-pandemic (P < 0.001-0.03). Physician (47/54, 87%) and staff (45/53, 85%) financial impacts were common, but none reported terminations. CONCLUSION: Breast imaging volumes during the early pandemic fell more severely in Texas than in California. Safety measures and financial impacts on physicians and staff were similar in both states.

Evidence of Benefit from Mammography Screening of Average-Risk Women Ages 40-49 Years: Science, Metrics, and Value Judgments.

The majority of randomized control trials and service-based screening studies of women ages 40-49 years demonstrate reductions in mortality of 29%-48% when long-term outcome is assessed. Annual screening is preferable in these younger women due to faster tumor-doubling times. Advances in mammography technique and breast ultrasound may allow even better results in the future.

Can Radiologists Predict the Presence of Ductal Carcinoma In Situ and Invasive Breast Cancer?

OBJECTIVE: We hypothesize that radiologists' estimated percentage likelihood assessments for the presence of ductal carcinoma in situ (DCIS) and invasive cancer may predict histologic outcomes. MATERIALS AND METHODS: Two hundred fifty cases categorized as BI-RADS category 4 or 5 at four University of California Medical Centers were retrospectively reviewed by 10 academic radiologists with a range of 1-39 years in practice. Readers assigned BI-RADS category (1, 2, 3, 4a, 4b, 4c, or 5), estimated percentage likelihood of DCIS or invasive cancer (0-100%), and confidence rating (1 = low, 5 = high) after reviewing screening and diagnostic mammograms and ultrasound images. ROC curves were generated. RESULTS: Sixty-two percent (156/250) of lesions were benign and 38% (94/250) were malignant. There were 26 (10%) DCIS, 20 (8%) invasive cancers, and 48 (19%) cases of DCIS and invasive cancer. AUC values were 0.830-0.907 for invasive cancer and 0.731-0.837 for DCIS alone. Sensitivity of 82% (56/68), specificity of 84% (153/182), positive predictive value (PPV) of 66% (56/85), negative predictive value (NPV) of 93% (153/165), and accuracy of 84% ([56 + 153]/250) were calculated using an estimated percentage likelihood of 20% or higher as the prediction threshold for invasive cancer for the radiologist with the highest AUC (0.907; 95% CI, 0.864-0.951). Every 20% increase in the estimated percentage likelihood of invasive cancer increased the odds of invasive cancer by approximately two times (odds ratio, 2.4). For DCIS, using a threshold of 40% or higher, sensitivity of 81% (21/26), specificity of 79% (178/224), PPV of 31% (21/67), NPV of 97% (178/183), and accuracy of 80% ([21 + 178]/250) were calculated. Similarly, these values were calculated at thresholds of 2% or higher (BI-RADS category 4) and 95% or higher (BI-RADS category 5) to predict the presence of malignancy. CONCLUSION: Using likelihood estimates, radiologists may predict the presence of invasive cancer with fairly high accuracy. Radiologist-assigned estimated percentage likelihood can predict the presence of DCIS, albeit with lower accuracy than that for invasive cancer.

Inter-reader Variability in the Use of BI-RADS Descriptors for Suspicious Findings on Diagnostic Mammography: A Multi-institution Study of 10 Academic Radiologists.

RATIONALE AND OBJECTIVES: The study aimed to determine the inter-observer agreement among academic breast radiologists when using the Breast Imaging Reporting and Data System (BI-RADS) lesion descriptors for suspicious findings on diagnostic mammography. MATERIALS AND METHODS: Ten experienced academic breast radiologists across five medical centers independently reviewed 250 de-identified diagnostic mammographic cases that were previously assessed as BI-RADS 4 or 5 with subsequent pathologic diagnosis by percutaneous or surgical biopsy. Each radiologist assessed the presence of the following suspicious mammographic findings: mass, asymmetry (one view), focal asymmetry (two views), architectural distortion, and calcifications. For any identified calcifications, the radiologist also described the morphology and distribution. Inter-observer agreement was determined with Fleiss kappa statistic. Agreement was also calculated by years of experience. RESULTS: Of the 250 lesions, 156 (62%) were benign and 94 (38%) were malignant. Agreement among the 10 readers was strongest for recognizing the presence of calcifications (k = 0.82). There was substantial agreement among the readers for the identification of a mass (k = 0.67), whereas agreement was fair for the presence of a focal asymmetry (k = 0.21) or architectural distortion (k = 0.28). Agreement for asymmetries (one view) was slight (k = 0.09). Among the categories of calcification morphology and distribution, reader agreement was moderate (k = 0.51 and k = 0.60, respectively). Readers with more experience (10 or more years in clinical practice) did not demonstrate higher levels of agreement compared to those with less experience. CONCLUSIONS: Strength of agreement varies widely for different types of mammographic findings, even among dedicated academic breast radiologists. More subtle findings such as asymmetries and architectural distortion demonstrated the weakest agreement. Studies that seek to evaluate the predictive value of certain mammographic features for malignancy should take into consideration the inherent interpretive variability for these findings.

Impact of Breast Density Legislation on Breast Cancer Risk Assessment and Supplemental Screening: A Survey of 110 Radiology Facilities.

Breast density notification laws, passed in 19 states as of October 2014, mandate that patients be informed of their breast density. The purpose of this study is to assess the impact of this legislation on radiology practices, including performance of breast cancer risk assessment and supplemental screening studies. A 20-question anonymous web-based survey was emailed to radiologists in the Society of Breast Imaging between August 2013 and March 2014. Statistical analysis was performed using Fisher's exact test. Around 121 radiologists from 110 facilities in 34 USA states and 1 Canadian site responded. About 50% (55/110) of facilities had breast density legislation, 36% of facilities (39/109) performed breast cancer risk assessment (one facility did not respond). Risk assessment was performed as a new task in response to density legislation in 40% (6/15) of facilities in states with notification laws. However, there was no significant difference in performing risk assessment between facilities in states with a law and those without (p < 0.831). In anticipation of breast density legislation, 33% (16/48), 6% (3/48), and 6% (3/48) of facilities in states with laws implemented handheld whole breast ultrasound (WBUS), automated WBUS, and tomosynthesis, respectively. The ratio of facilities offering handheld WBUS was significantly higher in states with a law than in states without (p < 0.001). In response to breast density legislation, more than 33% of facilities are offering supplemental screening with WBUS and tomosynthesis, and many are performing formal risk assessment for determining patient management.

Implications of Overdiagnosis: Impact on Screening Mammography Practices.

This review article explores the issue of overdiagnosis in screening mammography. Overdiagnosis is the screen detection of a breast cancer, histologically confirmed, that might not otherwise become clinically apparent during the lifetime of the patient. While screening mammography is an imperfect tool, it remains the best tool we have to diagnose breast cancer early, before a patient is symptomatic and at a time when chances of survival and options for treatment are most favorable. In 2015, an estimated 231,840 new cases of breast cancer (excluding ductal carcinoma in situ) will be diagnosed in the United States, and some 40,290 women will die. Despite these data, screening mammography for women ages 40-69 has contributed to a substantial reduction in breast cancer mortality, and organized screening programs have led to a shift from late-stage diagnosis to early-stage detection. Current estimates of overdiagnosis in screening mammography vary widely, from 0% to upwards of 30% of diagnosed cancers. This range reflects the fact that measuring overdiagnosis is not a straightforward calculation, but usually one based on different sets of assumptions and often biased by methodological flaws. The recent development of tomosynthesis, which creates high-resolution, three-dimensional images, has increased breast cancer detection while reducing false recalls. Because the greatest harm of overdiagnosis is overtreatment, the key goal should not be less diagnosis but better treatment decision tools. (Population Health Management 2015;18:S3-S11).

Overdiagnosis of breast cancer at screening is clinically insignificant.

Long-term follow-up of randomized trials provide the most accurate estimates of overdiagnosis. Estimates from follow-up of service screening studies are almost as accurate if there is sufficient adjustment for lead time and risk status. When properly analyzed data from both of these types of trials indicate that the rate of overdiagnosis at screening mammography is clinically negligible: 0-5%. Population trend studies are a potentially highly inaccurate means to estimate overdiagnosis. Most cases of DCIS detected at screening are medium and high grade with substantial potential to become an invasive disease. To avoid overtreatment, clinicians need to tailor their treatment of DCIS to the histologic and molecular characteristics of each case.

Criteria for identifying radiologists with acceptable screening mammography interpretive performance on basis of multiple performance measures.

OBJECTIVE: Using a combination of performance measures, we updated previously proposed criteria for identifying physicians whose performance interpreting screening mammography may indicate suboptimal interpretation skills. MATERIALS AND METHODS: In this study, six expert breast imagers used a method based on the Angoff approach to update criteria for acceptable mammography performance on the basis of two sets of combined performance measures: set 1, sensitivity and specificity for facilities with complete capture of false-negative cancers; and set 2, cancer detection rate (CDR), recall rate, and positive predictive value of a recall (PPV1) for facilities that cannot capture false-negative cancers but have reliable cancer follow-up information for positive mammography results. Decisions were informed by normative data from the Breast Cancer Surveillance Consortium (BCSC). RESULTS: Updated combined ranges for acceptable sensitivity and specificity of screening mammography are sensitivity≥80% and specificity≥85% or sensitivity 75-79% and specificity 88-97%. Updated ranges for CDR, recall rate, and PPV1 are: CDR≥6 per 1000, recall rate 3-20%, and any PPV1; CDR 4-6 per 1000, recall rate 3-15%, and PPV1≥3%; or CDR 2.5-4.0 per 1000, recall rate 5-12%, and PPV1 3-8%. Using the original criteria, 51% of BCSC radiologists had acceptable sensitivity and specificity; 40% had acceptable CDR, recall rate, and PPV1. Using the combined criteria, 69% had acceptable sensitivity and specificity and 62% had acceptable CDR, recall rate, and PPV1. CONCLUSION: The combined criteria improve previous criteria by considering the interrelationships of multiple performance measures and broaden the acceptable performance ranges compared with previous criteria based on individual measures.

Postmortem validation of breast density using dual-energy mammography.

PURPOSE: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. METHODS: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. RESULTS: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. CONCLUSIONS: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.

Screening mammography benefit controversies: sorting the evidence.

Numerous clinical studies have confirmed that screening women age 40 years and older reduces breast cancer mortality by 30% to 50%. Several factors including faster breast cancer growth rates and lower breast cancer incidence among younger women, as well as shorter life expectancy and more comorbid conditions among older women, should also be considered in screening guidelines. Annual screening beginning at age 40 years and continuing with no upper age limit, as long as a woman has a life expectancy of at least 5 years and no significant comorbid conditions, is currently recommended.

The California breast density information group: a collaborative response to the issues of breast density, breast cancer risk, and breast density notification legislation.

In anticipation of breast density notification legislation in the state of California, which would require notification of women with heterogeneously and extremely dense breast tissue, a working group of breast imagers and breast cancer risk specialists was formed to provide a common response framework. The California Breast Density Information Group identified key elements and implications of the law, researching scientific evidence needed to develop a robust response. In particular, issues of risk associated with dense breast tissue, masking of cancers by dense tissue on mammograms, and the efficacy, benefits, and harms of supplementary screening tests were studied and consensus reached. National guidelines and peer-reviewed published literature were used to recommend that women with dense breast tissue at screening mammography follow supplemental screening guidelines based on breast cancer risk assessment. The goal of developing educational materials for referring clinicians and patients was reached with the construction of an easily accessible Web site that contains information about breast density, breast cancer risk assessment, and supplementary imaging. This multi-institutional, multidisciplinary approach may be useful for organizations to frame responses as similar legislation is passed across the United States. Online supplemental material is available for this article.

Pitfalls in accurate estimation of overdiagnosis: implications for screening policy and compliance.

Stories in the public media that 30 to 50% of screen-detected breast cancers are overdiagnosed dissuade women from being screened because overdiagnosed cancers would never result in death if undetected yet do result in unnecessary treatment. However, such concerns are unwarranted because the frequency of overdiagnosis, when properly calculated, is only 0 to 5%. In the previous issue of Breast Cancer Research, Duffy and Parmar report that accurate estimation of the rate of overdiagnosis recognizes the effect of lead time on detection rates and the consequent requirement for an adequate number of years of follow-up. These indispensable elements were absent from highly publicized studies that overestimated the frequency of overdiagnosis.