Effect of Mammographic Screening Modality on Breast Density Assessment: Digital Mammography versus Digital Breast Tomosynthesis

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1 ORIGINAL RESEARCH BREAST IMAGING Effect of Mammographic Screening Modality on Breast Density Assessment: Digital Mammography versus Digital Breast Tomosynthesis Aimilia Gastounioti, PhD Anne Marie McCarthy, PhD Lauren Pantalone, BS Marie Synnestvedt, PhD Despina Kontos, PhD Emily F. Conant, MD From the Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3710 Hamilton Walk, Room G601E Goddard Building, Philadelphia, PA (A.G., L.P., M.S., D.K., E.F.C.); and Department of Medicine, Massachusetts General Hospital, Boston, Mass (A.M.M.). Received August 1, 2018; revision requested September 24; revision received January 24, 2019; accepted January 28. Address correspondence to A.G. ( Study supported by Susan G. Komen for the Cure (PDF ) and the National Cancer Institute (NCI)-funded Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium (U54CA163313). Conflicts of interest are listed at the end of this article. See also the editorial by Philpotts in this issue. Radiology 2019; 00:1 8 Content code: Background: Breast Imaging Reporting and Data System (BI-RADS) breast density categories assigned by interpreting radiologists often influence decisions surrounding supplemental breast cancer screening and risk assessment. The landscape of mammographic screening continuously evolves, and different mammographic screening modalities may result in different perception of density, reflected in different assignment of BI-RADS density categories. Purpose: To investigate the effect of screening mammography modality on BI-RADS breast density assessments. Materials and Methods: Data were retrospectively analyzed from individual women (42.3% [ of ] white women, 57.7% [ of ] black women; mean age, 56.3 years; age range, years) who underwent from one to seven mammographic screening examinations from September 2010 through February 2017 ( examinations). Three screening modalities were used: digital mammography alone (8935 examinations); digital mammography with digital breast tomosynthesis (DBT; examinations); and synthetic mammography with DBT ( examinations). Random-effects logistic regression analysis was performed to estimate the likelihood of assignment to high versus low BI-RADS density category according to each modality, adjusted for ethnicity, age, body mass index (BMI), and radiologist. The interactions of modality with ethnicity and BMI on density categorization were also tested with the model. Results: Women screened with DBT versus digital mammography alone had lower likelihood regarding categorization of high density breasts (digital mammography and DBT vs digital mammography: odds ratio, 0.69 [95% confidence interval: 0.61, 0.80], P,.001; synthetic mammography and DBT vs digital mammography: odds ratio, 0.43 [95% confidence interval: 0.37, 0.50], P,.001). Lower likelihood of high density was also observed at synthetic mammography and DBT compared with digital mammography and DBT (odds ratio, 0.62; 95% confidence interval: 0.56, 0.69; P,.001). There were interactions of modality with ethnicity (P =.007) and BMI (P =.003) on breast density assessment, with greater differences in density categorization according to modality observed for black women than for white women and groups with higher BMI. Conclusion: Breast density categorization may vary by screening mammographic modality, and this effect appears to vary by ethnicity and body mass index. RSNA, 2019 Online supplemental material is available for this article. ammographic breast density reflects the relative Mamounts of fat versus fibroglandular tissues in the breast (1) and is an established risk factor for breast cancer (2). Women with the highest level of breast density have four to six times the risk for breast cancer compared with women with the lowest levels of density (3), and high density is associated with larger and more aggressive tumors (4). Moreover, breast density can affect the sensitivity of mammography because of masking of tumors (5). As of December 2018, over 70% of states in the United States passed legislation mandating that women be notified of their breast density. In some states, women with high breast density are advised to both discuss the implication of their density with their health care provider and consider supplemental screening methods (6). The most commonly used breast density assessment is the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) (1). The BI-RADS system includes four categories of breast density (a, almost entirely fatty; b, scattered areas of fibroglandular density; c, hetereogeneously dense; and, d, extremely dense). According to most state notification laws, women assigned the latter two breast density categories are considered to have dense breasts whereas the first two density categories are considered nondense. In many states, having dense breast parenchyma prompts supplemental screening, most often with breast US. Studies show a strong relationship of high BI-RADS breast density categories to cancer risk (2), risk of masking (5), and high-risk benign breast disease (7). This copy is for personal use only. To order printed copies, contact reprints@rsna.org

2 Effect of Mammographic Screening Modality on Breast Density Assessment Abbreviations BI-RADS = Breast Imaging Reporting and Data System, BMI = body mass index, DBT = digital breast tomosynthesis Summary Breast density assignments may vary greatly by screening mammographic modality (digital mammography alone; digital mammography with digital breast tomosynthesis, and synthetic mammography with digital breast tomosynthesis) and this effect appears to vary by ethnicity and body mass index. Key Points nn nn nn Our data shows an overall trend of downgrading breast density when imaging is performed with either digital mammography with digital breast tomosynthesis (DBT) or synthetic mammography with DBT compared with digital mammography alone (likelihood of high density was reduced by 31% and 57%, respectively). We found lower likelihood of high breast density assignments after the replacement of digital mammography by synthetic mammography (likelihood of high density was reduced by 38%). Changes in breast density assignments because of different screening mammographic modalities were greater for black women than for white women and for groups with higher body mass index. Although planar digital mammography is the foundation of breast cancer screening, the landscape of mammographic screening is continuously evolving with the implementation of the quasi-three-dimensional digital breast tomosynthesis (DBT) in breast clinics (8) and with synthetic mammography increasingly replacing digital mammography as a dose-reduction approach in DBT screening (9). Our hypothesis is that these different mammographic screening modalities may result in different perception of density, reflected in different assignment of BI-RADS density categories. The majority of outcome data regarding the effect of mammographic density on screening outcomes and breast cancer risk assessment has been on the basis of two-dimensional imaging techniques. Therefore, changes in density assessments with tomosynthesis modalities may affect clinical decisions surrounding supplemental screening and risk assessment before adequate outcome data are available. The purpose of our study was to investigate the effect of screening mammographic modality on clinical breast density assessment by comparing BI-RADS density assignments after screening with digital mammography, digital mammography and DBT, and synthetic mammography and DBT, by accounting for ethnicity, age, body mass index (BMI), and interpreting radiologist. Materials and Methods This retrospective study was Health Insurance Portability and Accountability Act compliant and approved by the institutional review board of our institution, and a waiver of written informed consent was granted for this review of existing clinical data. Cross-sectional Sample of Screening Population From September 1, 2010, through February 28, 2017, women underwent one to seven mammographic screening examinations at the Hospital of the University of Pennsylvania. In total, women (57.5%) had repeated mammographic screening examinations ( examinations). BI-RADS density categories, assigned to each screening examination by the reviewing radiologist, were extracted from archived screening reports. Age at screening and ethnicity were available for all examinations in electronic medical records. BMI at the time of each screening examination was extracted from the electronic medical record on the screening date, if available, and if not, it was extracted from the woman s closest screening examination for which BMI was available (median time from screening date to BMI measurement, 1.4 years). Additional risk factor data (eg, parity and history of previous breast biopsy) at the time of each screening examination was also retrieved from the electronic medical record, if available. For the purposes of our study, we retrospectively selected all examinations of women age years (ie, the main age range in breast cancer screening) (10), who were self-identified as white or black/african American ( of ; 84.3%) toward ensuring sufficient sample size to account for racial differences in density. We excluded examinations that were missing BI-RADS breast density (115 of ; 0.2%), BMI (2073 of ; 3.3%) or both (five of ;,0.1%). This resulted in a final crosssectional sample of examinations (Fig 1) corresponding to individual women (mean age, 56 years; age range, years). Subsets of screening examinations acquired at the Hospital of the University of Pennsylvania from September 2010 to June 2015 (n = [11]; n = [12,13]; n = [14]; n = [15]; n = [16]) were previously reported to compare outcomes of screening mammographic modalities. Our study analyzed the entire screening population for more than 6 continuous years and focused on the effect of screening mammographic modality on the perception of breast density. Moreover, 9498 digital mammography with DBT examinations from September 2012 to August 2013 were previously used to compare breast density measures for black and white women (17); as part of our study, ethnicity was considered to account for ethnic differences in the modality effect on density assignments. Mammographic Screening Modalities At the Hospital of the University of Pennsylvania, digital mammography (Selenia; Hologic, Bedford, Mass) was the standard of care for all routine breast cancer screening by On September 19, 2011, DBT was implemented for all screening examinations (Selenia Dimensions; Hologic) with the U.S. Food and Drug Administration approved dual-modality protocol, digital mammography with DBT. Starting on January 7, 2015, full-field digital mammography was fully replaced by synthetic mammography (C-View; Hologic), and synthetic mammography with DBT has since been used for routine breast cancer screening. Therefore, we evaluated three periods in our study population by using three different mammographic screening modalities: period 1, digital mammography alone; period 2, digital mammography with DBT; and period 3, synthetic mammography with DBT. 2 radiology.rsna.org n Radiology: Volume 00: Number

3 Gastounioti et al on the screening date to investigate potential changes in our results by retrieving BMI from the woman s closest screening examination at which BMI was available. Last, we investigated potential differences in dense versus nondense BI- RADS breast density distributions by screening modality, separately according to ethnicity and BMI groups by using Pearson x 2 tests applied within each BMI group of white and black women. All statistical analyses were performed by using software (Stata 13; StataCorp, College Station, Tex) and a P value of.05 or less indicated statistical significance. Because of the large sample size, we had substantial power to detect differences in breast density according to screening modality, ethnicity, and BMI. We had at least 80% power to detect a 2% difference in the proportion of women with dense breasts between screening modalities within their ethnicity and BMI groups. Figure 1: Flowchart shows inclusion and exclusion criteria for crosssectional screening sample analyzed in our study. BI-RADS = Breast Imaging Reporting and Data System, BMI = body mass index. Breast Density Assessment The screening examinations of our data set were interpreted by one of 10 board-certified and fellowship-trained radiologists who specialized in breast imaging and who had 29 years (two radiologists), 20 years (three radiologists), 18 years (one radiologist), years (one radiologist), 5 10 years (two radiologists), and 1 5 years (one radiologist) of experience (14.5% [8795 of ] of the examinations were interpreted by E.F.C., with 29 years of experience). For the purposes of our analyses, breast density assessments were dichotomized as nondense (BI-RADS density category a or b) or dense (BI-RADS density category c or d). Statistical Analysis Random-effects logistic regression (panel variable, individual woman) was performed to estimate the likelihood of being assigned to dense versus nondense BI-RADS density category by each screening modality, adjusted for ethnicity, age, and BMI, which are the main confounders of breast density differences (17 19). To account for interreader variability in breast density assessments (20), the model was additionally adjusted for each interpreting radiologist. The interactions of screening modality with ethnicity and BMI group (,25 kg/m 2, kg/m 2, and 30kg/m 2 ) and their effect on density were also tested in the model with the inclusion of two cross-product terms for the modality and ethnicity and modality and BMI interactions. Statistical significance was evaluated with likelihood-ratio tests. Moreover, to study the effect at the individual woman level, the intrawoman correlation of BI-RADS breast density across successive screening examinations was calculated from our model. Furthermore, we performed a sensitivity analysis among screening examinations with complete BMI data available Results Our study sample consisted of 14.7% digital mammography (8935 of ), 50.7% digital mammography and DBT ( of ), and 34.6% synthetic mammography and DBT ( of ) screening examinations (Table 1). The distribution of age and parity differed during the three periods (P,.001), whereas the proportion of white versus black women was slightly higher at synthetic mammography and DBT (P =.004). Similar BMI distributions were observed for all periods (P =.81). No comparison was performed on history of prior breast biopsy because of missing data at digital mammography and digital mammography and DBT periods. After accounting for ethnicity, age, BMI, and radiologist, there were differences according to screening modality in the likelihood of high breast density according to BI-RADS standards (Table 2). In the logistic regression model, women screened with DBT had lower likelihood of high density compared with those screened with digital mammography alone (digital mammography and DBT vs digital mammography: odds ratio, 0.69, P,.001; synthetic mammography and DBT vs digital mammography: odds ratio, 0.43, P,.001). Lower likelihood of high density was also observed at synthetic mammography and DBT screening compared with digital mammography and DBT (odds ratio, 0.62; P,.001). The interactions of screening modality and ethnicity and screening modality and BMI group were both statistically significant (likelihood ratio test: P =.007 and P =.003, respectively), and linear combinations of the model parameters were estimated to evaluate the modality effects by ethnicity and BMI groups (Table E1 [online]). In the stratified results (Table 3), substantial density differences by screening modality were observed, with lower odds ratios for black women than for white women, and for groups of women with higher BMI. The intrawoman correlation of BI-RADS breast density, reflecting the correlation of breast density across all screening examinations of each woman, was equal to The results of our sensitivity analysis on examinations with complete BMI data available on the screening date (sample size reduced by 4611 screening examinations) showed similar results (Tables E2, E3 [online]), thereby Radiology: Volume 00: Number n radiology.rsna.org 3

4 Effect of Mammographic Screening Modality on Breast Density Assessment Table 1: Study Sample Characteristics by Modality Parameter Digital Mammography (n = 8935) Digital Mammography and DBT (n = ) Synthetic Mammography and DBT (n = ) Ethnicity White women 4031 (45.1) (45.5) 9851 (46.8) Black women 4904 (54.9) (54.5) (53.2) Age (y) (14.1) 4368 (14.2) 2498 (11.9) (15.3) 4673 (15.2) 2942 (14.0) (18.2) 5286 (17.2) 3459 (16.4) (18.6) 5650 (18.4) 3770 (17.9) (15.6) 4798 (15.6) 3587 (17.0) (10.7) 3646 (11.8) 2943 (14.0) (7.5) 2358 (7.6) 1853 (8.8) BMI,18.5 kg/m (1.1) 394 (1.3) 268 (1.3) kg/m (28.2) 8707 (28.3) 6043 (28.7) kg/m (27.9) 8479 (27.5) 5816 (27.6) 30 kg/m (42.7) (42.9) 8925 (42.4) Parity Never 1989 (22.2) 6885 (22.4) 4026 (19.1) At least one 6178 (69.1) (65.8) (66.1) Unknown 768 (8.6) 3633 (11.8) 3106 (14.7) Previous breast biopsy Never 667 (7.5) 2577 (8.4) (65.4) Ever 1323 (14.8) 4778 (15.5) 3541 (16.8) Unknown 6945 (77.7) (76.1) 3736 (17.7) Note. Data in parentheses are percentages. BMI = body mass index, DBT = digital breast tomosynthesis. Table 2: Random-Effects Logistic Regression of Assignment to Dense Versus Nondense Breast Imaging Reporting and Data System Breast Density Category Parameter Odds Ratio P Value LRT P Value Age 0.79 (0.78, 0.80),.001 NA BMI,25 kg/m 2 Reference NA, kg/m (0.35, 0.55), kg/m (0.38, 0.78).001 Ethnicity Black versus white 0.31 (0.25, 0.38),.001 NA Modality Digital mammography and DBT versus digital mammography Synthetic mammography and DBT versus digital mammography Synthetic mammography and DBT versus digital mammography and DBT 0.69 (0.61, 0.80),.001, (0.37, 0.50), (0.56, 0.69),.001 Note. Data in parentheses are 95% confidence intervals. Data were additionally adjusted for radiologist and continuous body mass index. BMI = body mass index, DBT = digital breast tomosynthesis, LRT = likelihood ratio test, NA = not applicable. suggesting minor changes to our findings by our approach to obtain BMI for examinations with BMI values that were not available on the screening date. Differences according to screening modality were also found when BI-RADS density distributions in different ethnic and BMI groups were compared (Fig 2, Table E4 [online]). Overall, across all BMI groups, more women tended to be assigned lower BI-RADS density categories when they underwent screening with digital mammography and DBT and synthetic mammography and DBT compared with digital mammography alone (Pearson x 2, P,.05). Moreover, the modality effect seemed to be greater for groups with higher BMI. For example, among white women with BMI lower than 25 kg/m 2, screening with synthetic mammography and DBT gave a reduction of 4.3% in the proportion of examinations that classified breasts as dense compared with digital mammography screening (from 59.6% to 55.3%); among white women who according to BMI were overweight (BMI, kg/m 2 ) and obese (BMI, 30 kg/m 2 ), the corresponding reduction was 5.3% (from 33.5% to 28.3%) and 6.0% (from 17.8% to 11.8%), respectively. Among women with repeated screening examinations, 30.2% (4559 of ) were downgraded and 14.0% ( radiology.rsna.org n Radiology: Volume 00: Number

5 Gastounioti et al Table 3: Random-Effects Logistic Regression Analysis of Assignment to Dense Versus Nondense Breast Imaging Reporting and Data System Breast Density Category by Screening Modality, Body Mass Index, and Ethnicity Parameter No. of Patients Odds Ratio P Value BMI,25 kg/m 2 White women Digital mammography and DBT versus digital mammography 0.72 (0.57, 0.91).006 Synthetic mammography and DBT versus digital mammography 0.58 (0.45, 0.75),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.81 (0.68, 0.96).02 Black women 4526 Digital mammography and DBT versus digital mammography 0.78 (0.57, 1.08).13 Synthetic mammography and DBT versus digital mammography 0.51 (0.36, 0.73),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.66 (0.52, 0.84).001 BMI kg/m 2 White women 7963 Digital mammography and DBT versus digital mammography 0.67 (0.50, 0.88).004 Synthetic mammography and DBT versus digital mammography 0.45 (0.33, 0.61),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.67 (0.54, 0.83),.001 Black women 8823 Digital mammography and DBT versus digital mammography 0.73 (0.55, 0.96).03 Synthetic mammography and DBT versus digital mammography 0.40 (0.29, 0.54),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.54 (0.44, 0.67),.001 BMI 30 kg/m 2 White women 6402 Digital mammography and DBT versus digital mammography 0.62 (0.45, 0.85).003 Synthetic mammography and DBT versus digital mammography 0.32 (0.23, 0.47),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.52 (0.40, 0.68),.001 Black women Digital mammography and DBT versus digital mammography 0.68 (0.53, 0.88).003 Synthetic mammography and DBT versus digital mammography 0.29 (0.21, 0.39),.001 Synthetic mammography and DBT versus digital mammography and DBT 0.42 (0.34, 0.53),.001 Note. Data in parentheses are 95% confidence intervals. Data were additionally adjusted for age, continuous body mass index, and radiologist. BMI = body mass index, DBT = digital breast tomosynthesis. Figure 2: Histograms of Breast Imaging Reporting and Data System density categorization across different body mass index groups according to screening mammographic modality and ethnicity (black women and white women). BMI = body mass index, DBT = digital breast tomosynthesis, DM = digital mammography, SM = synthetic mammography. Radiology: Volume 00: Number n radiology.rsna.org 5

6 Effect of Mammographic Screening Modality on Breast Density Assessment Figure 3: Craniocaudal (left) and mediolateral-oblique (right) consecutive digital mammography (DM) digital breast tomosynthesis (DBT) images (top) and, 1.1 years later, the synthetic mammography (SM) and DBT screening images (bottom) of the same postmenopausal white woman interpreted by the same radiologist. The DM and DBT screening examination was assigned Breast Imaging Reporting and Data System (BI-RADS) density category c (ie, dense), whereas the synthetic mammography and DBT screening examination was assigned BI-RADS density category b (ie, nondense). BMI = body mass index. of ) were upgraded in breast density categories across successive screening examinations with different modalities. Figure 3 shows an example of a postmenopausal white woman who was screened with digital mammography and DBT and was assigned BI-RADS density category c (dense); 1 year later the same woman was screened with synthetic mammography and DBT, and her examination was interpreted by the same radiologist who this time assigned breast density category b (nondense). Figure 4 shows a similar example in a postmenopausal black woman whose consecutive digital mammography and DBT, and synthetic mammography and DBT, were interpreted by the same radiologist; breast density was downgraded from category c to breast density category b. Discussion By using a large urban screening population, our study showed that the type of screening mammographic modality may change the assignment of women to BI-RADS breast density categories. We observed an overall trend of downgrading density when imaging was performed with either digital mammography and DBT or synthetic mammography and DBT compared with digital mammography alone (odds of high density was 0.69 and 0.43, respectively). This may be because of the perception of less fibroglandular tissue in the volumetric display of DBT imaging compared with that of planar, area-based density in digital mammography alone. Moreover, we found lower likelihood of high density assignments after the replacement of digital mammography by synthetic mammography. This may have been because of differences in the glandular and fatty tissue of the breast at reconstructed, synthetic mammography (9,21). Our data also suggests that changes in density assignments because of different screening mammographic modalities are more prominent in black versus white women and in groups with higher BMI. A trend toward downgrading BI-RADS density at screening with synthetic mammography versus digital mammography was reported in two recent retrospective studies of outcomes of synthetic mammography and DBT screening (15,22). Also, two retrospective studies (23,24) with 200 and 309 women reported comparable breast density assignments by using digital mammography and synthetic mammography images. To our knowledge, ours is the first large-scale study to evaluate the effect of mammographic screening modality on breast density readings in actual clinical practice where digital mammography and synthetic mammography images are read together with the quasithree-dimensional DBT volume since DBT is acquired. Because our institution adopted key advancements in mammographic screening, we were able to include three major mammographic screening modalities. Moreover, over half of our study population was black, which allowed us to investigate racial differences in the modality effect. Our study had limitations. We performed an observational retrospective study with women who were sequentially screened with different screening mammographic modalities at different points; the ideal study design would require simultaneous acquisition of all modalities at the same time, which was not feasible in the actual clinical practice. Moreover, the screening period of our study included the point when BI-RADS density definitions were revised, which might have affected breast density classifications by radiologists. 6 radiology.rsna.org n Radiology: Volume 00: Number

7 Figure 4: Craniocaudal (left) and mediolateral-oblique (right) images from consecutive digital mammography (DM) and digital breast tomosynthesis (DBT) images (top) and 2.1 years later the synthetic mammography (SM) and DBT screening images (bottom) of the same postmenopausal black woman interpreted by the same radiologist. The digital mammography and DBT screening examination (top) was assigned Breast Imaging Reporting and Data System (BI-RADS) density category c (ie, dense), whereas the synthetic mammography and DBT screening examination was assigned BI-RADS density category b (ie, nondense). BMI = body mass index. Initially, density categories were on the basis of approximate area percentage values of the fibroglandular tissue in relation to the whole breast area (BI-RADS fourth edition, 2003), whereas in the latest revision (BI-RADS fifth edition, 2013), there was emphasis on the masking effect of the dense tissue. However, preliminary comparisons of BI-RADS density Gastounioti et al readings by using both editions of BI-RADS suggested that there are 2% 10% more assessments rated as dense by using the fifth edition, and that individual radiologists show a variable adaptation to guidelines depending on years of experience (25,26). Our data show a reduction in the amount of examinations that rated breasts as dense with the transition from digital mammography to digital mammography and DBT, and then to synthetic mammography and DBT. It could therefore be assumed that our reduction in the amount of images of breasts rated as dense associated with the evolution in mammographic screening might be larger than that shown in our data. We acknowledge the occurrence of subjectivity in BI-RADS breast density readings. To address this limitation, we aim to expand this analysis to automated breast density metrics, which allow for reproducible, quantitative breast density assessment metrics (27,28), to show potential effects of mammographic screening modality on breast density evaluation. In our future analyses, we also aim to concentrate on screening examinations with complete BMI data available on the screening date, and also account for additional demographic and clinical risk factors (eg, parity, menopausal status, and use of hormone replacement therapy) that may affect density (29,30), as well as factors such as breast thickness and size, which may account for ethnic differences contributing to the observed variation in the screening modality effects on breast density assessment according to ethnicity (31). If our results are validated by other practices and on a larger scale, and by readers studies with digital mammography, digital mammography and DBT, and synthetic mammography and DBT, the clinical implications may be important. For instance, when screening is performed with DBT, which in our study was associated with lower likelihood of high density compared with digital mammography alone, fewer women may be classified as having dense breasts and therefore they would be identified as possibly benefiting from supplemental screening on the basis of a mammographic density assessment. Because studies (32 34) have consistently shown that additional cancers may be depicted in dense breasts by using supplemental MRI or US screening after either digital mammography or DBT screening negative for cancer, the effect of screening modality on breast density assessment shown in our results might ultimately affect the number of women who are offered supplemental screening and, therefore, the chance of detecting additional mammographically occult cancers. It is important to note that, to our knowledge, no studies have shown a statistically significant reduction in Radiology: Volume 00: Number n radiology.rsna.org 7

8 Effect of Mammographic Screening Modality on Breast Density Assessment DBT screening with false-negative findings. Therefore, supplemental screening may be warranted in women screened with DBT but may require thresholds on the basis of additional outcome data with longer follow-up. In summary, our study showed that screening mammographic modality affects BI-RADS breast density assignments with an overall trend of lower density classification when screening with DBT and synthetic mammography and DBT compared with digital mammography alone. Furthermore, this effect seems to be more prominent in black women than in white women and in groups with higher BMI. Our findings may have direct implications for personalized screening because breast density assignments, which often drive recommendations for supplemental screening, may vary according to modality, ethnicity, and BMI. Author contributions: Guarantor of integrity of entire study, E.F.C.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; agrees to ensure any questions related to the work are appropriately resolved, all authors; literature research, A.G., E.F.C.; clinical studies, L.P., E.F.C.; experimental studies, A.G.; statistical analysis, A.G., A.M.M., M.S., D.K.; and manuscript editing, A.G., A.M.M., D.K., E.F.C. Disclosures of Conflicts of Interest: A.G. disclosed no relevant relationships. A.M.M. disclosed no relevant relationships. L.P. disclosed no relevant relationships. M.S. disclosed no relevant relationships. D.K. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed patent issued that is broadly relevant but not licensed to any entity and author does not receive any royalties. Other relationships: disclosed no relevant relationships. E.F.C. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author s institution for grant from Hologic and icad; disclosed money to author s institution for payment for lectures including service on speaker bureaus from Hologic. Other relationships: disclosed no relevant relationships. References 1. D Orsi CJ. ACR BI-RADS Atlas: Breast Imaging Reporting and Data System. Reston, Va: American College of Radiology, McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006;15(6): Boyd NF, Rommens JM, Vogt K, et al. 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