scholarly journals Breast density in multiethnic women presenting for screening mammography

2017 ◽  
Vol 24 (3) ◽  
pp. 334-338 ◽  
Author(s):  
Bridget A. Oppong ◽  
Chiranjeev Dash ◽  
Suzanne O'Neill ◽  
Yinan Li ◽  
Kepher Makambi ◽  
...  
2018 ◽  
Vol 171 (3) ◽  
pp. 767-776 ◽  
Author(s):  
My von Euler-Chelpin ◽  
Martin Lillholm ◽  
George Napolitano ◽  
Ilse Vejborg ◽  
Mads Nielsen ◽  
...  

2004 ◽  
Vol 39 (1) ◽  
pp. 48-55 ◽  
Author(s):  
Patricia A Carney ◽  
Claudia J Kasales ◽  
Anna N.A Tosteson ◽  
Julia E Weiss ◽  
Martha E Goodrich ◽  
...  

2016 ◽  
Vol 8 (2) ◽  
pp. 55-62 ◽  
Author(s):  
Stephanie Lynn Chau ◽  
Amy Alabaster ◽  
Karin Luikart ◽  
Leslie Manace Brenman ◽  
Laurel A. Habel

Purpose: Half of US states mandate women be notified if they have dense breasts on their mammogram, yet guidelines and data on supplemental screening modalities are limited. Breast density (BD) refers to the extent that breast tissue appears radiographically dense on mammograms. High BD reduces the sensitivity of screening mammography and increases breast cancer risk. The aim of this study was to determine the potential impact of California’s 2013 BD notification legislation on breast cancer screening patterns. Methods: We conducted a cohort study of women aged 40 to 74 years who were members of a large Northern California integrated health plan (approximately 3.9 million members) in 2011-2015. We calculated pre- and post-legislation rates of screening mammography and magnetic resonance imaging (MRI). We also examined whether women with dense breasts (defined as BI-RADS density c or d) had higher MRI rates than women with nondense breasts (defined as BI-RADS density a or b). Results: After adjustment for race/ethnicity, age, body mass index, medical facility, neighborhood median income, and cancer history, there was a relative 6.6% decrease (relative risk [RR] 0.934, confidence interval [CI] 0.92-0.95) in the rate of screening mammography, largely driven by a decrease among women <50 years. While infrequent, there was a relative 16% increase (RR 1.16, CI 1.07-1.25) in the rate of screening MRI, with the greatest increase among the youngest women. In the postlegislation period, women with extremely dense breasts (BI-RADS d) had 2.77 times (CI 1.93-3.95) the odds of a MRI within 9 months of a screening mammogram compared with women with nondense breasts (BI-RADS b). Conclusions: In this setting, MRI rates increased in the postlegislation period. In addition, women with higher BD were more likely to have supplementary MRI. The decrease in mammography rates seen primarily among younger women may have been due to changes in national screening guidelines.


2017 ◽  
Vol 162 (3) ◽  
pp. 541-548 ◽  
Author(s):  
Katharina Holland ◽  
Carla H. van Gils ◽  
Ritse M. Mann ◽  
Nico Karssemeijer

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
My von Euler-Chelpin ◽  
Martin Lillholm ◽  
Ilse Vejborg ◽  
Mads Nielsen ◽  
Elsebeth Lynge

Abstract Background Screening mammography works better in fatty than in dense breast tissue. Computerized assessment of parenchymal texture is a non-subjective method to obtain a refined description of breast tissue, potentially valuable in addition to breast density scoring for the identification of women in need of supplementary imaging. We studied the sensitivity of screening mammography by a combination of radiologist-assessed Breast Imaging Reporting and Data System (BI-RADS) density score and computer-assessed parenchymal texture marker, mammography texture resemblance (MTR), in a population-based screening program. Methods Breast density was coded according to the fourth edition of the BI-RADS density code, and MTR marker was divided into quartiles from 1 to 4. Screening data were followed up for the identification of screen-detected and interval cancers. We calculated sensitivity and specificity with 95% confidence intervals (CI) by BI-RADS density score, MTR marker, and combination hereof. Results Density and texture were strongly correlated, but the combination led to the identification of subgroups with different sensitivity. Sensitivity was high, about 80%, in women with BI-RADS density score 1 and MTR markers 1 or 2. Sensitivity was low, 67%, in women with BI-RADS density score 2 and MTR marker 4. For women with BI-RADS density scores 3 and 4, the already low sensitivity was further decreased for women with MTR marker 4. Specificity was 97–99% in all subgroups. Conclusion Our study showed that women with low density constituted a heterogenous group. Classifying women for extra imaging based on density only might be a too crude approach. Screening sensitivity was systematically high in women with fatty and homogenous breast tissue.


2016 ◽  
Vol 162 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Johanna O. P. Wanders ◽  
Katharina Holland ◽  
Wouter B. Veldhuis ◽  
Ritse M. Mann ◽  
Ruud M. Pijnappel ◽  
...  

2017 ◽  
Vol 59 (2) ◽  
pp. 154-160 ◽  
Author(s):  
Nataliia Moshina ◽  
Marta Roman ◽  
Sofie Sebuødegård ◽  
Gunvor G Waade ◽  
Giske Ursin ◽  
...  

Background Breast radiologists of the Norwegian Breast Cancer Screening Program subjectively classified mammographic density using a three-point scale between 1996 and 2012 and changed into the fourth edition of the BI-RADS classification since 2013. In 2015, an automated volumetric breast density assessment software was installed at two screening units. Purpose To compare volumetric breast density measurements from the automated method with two subjective methods: the three-point scale and the BI-RADS density classification. Material and Methods Information on subjective and automated density assessment was obtained from screening examinations of 3635 women recalled for further assessment due to positive screening mammography between 2007 and 2015. The score of the three-point scale (I = fatty; II = medium dense; III = dense) was available for 2310 women. The BI-RADS density score was provided for 1325 women. Mean volumetric breast density was estimated for each category of the subjective classifications. The automated software assigned volumetric breast density to four categories. The agreement between BI-RADS and volumetric breast density categories was assessed using weighted kappa (kw). Results Mean volumetric breast density was 4.5%, 7.5%, and 13.4% for categories I, II, and III of the three-point scale, respectively, and 4.4%, 7.5%, 9.9%, and 13.9% for the BI-RADS density categories, respectively ( P for trend < 0.001 for both subjective classifications). The agreement between BI-RADS and volumetric breast density categories was kw = 0.5 (95% CI = 0.47–0.53; P < 0.001). Conclusion Mean values of volumetric breast density increased with increasing density category of the subjective classifications. The agreement between BI-RADS and volumetric breast density categories was moderate.


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