TY - JOUR
T1 - Fully automated volumetric breast density estimation from digital breast tomosynthesis
AU - Gastounioti, Aimilia
AU - Pantalone, Lauren
AU - Scott, Christopher G.
AU - Cohen, Eric A.
AU - Wu, Fang F.
AU - Winham, Stacey J.
AU - Jensen, Matthew R.
AU - Maidment, Andrew D.A.
AU - Vachon, Celine M.
AU - Conant, Emily F.
AU - Kontos, Despina
N1 - Publisher Copyright:
© 2021 Radiological Society of North America Inc.. All rights reserved.
PY - 2021/12
Y1 - 2021/12
N2 - Background: While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose: To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods: This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results: A total of 132 women diagnosed with breast cancer (mean age 6 standard deviation [SD], 60 years 6 11) and 528 controls (mean age, 60 years 6 11) were included. Moderate correlations between DBT and DM density measures (r = 0.32-0.75; all P , .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%DBT) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [P , .001] and 1.7 [95% CI: 1.2, 2.3] [P = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [P = .01] and 1.7 [95% CI: 1.2, 2.6] [P = .04] per SD for Volpara and Quantra, respectively). Conclusion: The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography.
AB - Background: While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose: To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods: This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results: A total of 132 women diagnosed with breast cancer (mean age 6 standard deviation [SD], 60 years 6 11) and 528 controls (mean age, 60 years 6 11) were included. Moderate correlations between DBT and DM density measures (r = 0.32-0.75; all P , .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%DBT) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [P , .001] and 1.7 [95% CI: 1.2, 2.3] [P = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [P = .01] and 1.7 [95% CI: 1.2, 2.6] [P = .04] per SD for Volpara and Quantra, respectively). Conclusion: The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography.
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U2 - 10.1148/radiol.2021210190
DO - 10.1148/radiol.2021210190
M3 - Article
C2 - 34519572
AN - SCOPUS:85120172295
SN - 0033-8419
VL - 301
SP - 561
EP - 568
JO - Radiology
JF - Radiology
IS - 3
ER -