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 - Funding Information:
Disclosures of Conflicts of Interest: A.G. disclosed no relevant relationships. L.P. disclosed no relevant relationships. C.G.S. disclosed no relevant relationships. E.A.C. disclosed no relevant relationships. F.F.W. disclosed no relevant relationships. S.J.W. disclosed no relevant relationships. M.R.J. disclosed no relevant relationships. A.D.A.M. disclosed compensation as a scientific board member of Real Time Tomography; received compensation for expert testimony on patent infringement lawsuits from Williams and Connolly and from Jones Day Arnold & Porter; received or will receive grants from the National Institutes of Health, Department of Defense, Susan G. Komen Breast Cancer Foundation, and Burroughs Wellcome Fund; has patents pending; has stocks or stock options in Real Time Tomography and Daimroc; received funds to cover travel and meeting expenses from KTH Sweden. C.M.V. institution received grant from GRAIL for liquid biopsy marker research. E.F.C. disclosed compensation as a member of the iCAD advisory panel; institution received or will receive grants from Hologic, OM1, and iCAD; received speaker fees from AuntMinnie.com. D.K. institution received or will receive a research grant from Hologic.
Funding Information:
Supported by the Susan G. Komen for the Cure Breast Cancer Foundation (grant PDF17479714), National Cancer Institute of the National Institutes of Health (R01 Research Projects 2R01CA161749-05 and R01CA177150), and a Resource-Related Research Project–Cooperative Agreement (grant 1U24CA189523-01A1). Conflicts of interest are listed at the end of this article.
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.
UR - http://www.scopus.com/inward/record.url?scp=85120172295&partnerID=8YFLogxK
U2 - 10.1148/radiol.2021210190
DO - 10.1148/radiol.2021210190
M3 - Article
C2 - 34519572
AN - SCOPUS:85120172295
VL - 301
SP - 561
EP - 568
JO - Radiology
JF - Radiology
SN - 0033-8419
IS - 3
ER -