Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment.

Abstract

INTRODUCTION Mammographic density is a strong risk factor for breast cancer and an important determinant of screening sensitivity, but its clinical utility is hampered due to the lack of objective and automated measures. We evaluated the performance of a fully automated volumetric method (Volpara). METHODS A prospective cohort study included 41,102 women attending mammography screening, of whom 206 were diagnosed with breast cancer after a median follow-up of 15.2 months. Percent and absolute dense volumes were estimated from raw digital mammograms. Genotyping was performed in a subset of the cohort (N = 2,122). We examined the agreement by side and view and compared density distributions across different mammography systems. We also studied associations with established density determinants and breast cancer risk. RESULTS The method showed good agreement by side and view, and distributions of percent and absolute dense volume were similar across mammography systems. Volumetric density was positively associated with nulliparity, age at first birth, hormone use, benign breast disease, and family history of breast cancer, and negatively with age and postmenopausal status. Associations were also observed with rs10995190 in the ZNF365 gene (P < 1.0 × 10(-6)) and breast cancer risk [HR for the highest vs. lowest quartile, 2.93; 95% confidence interval, 1.73-4.96 and 1.63 (1.10-2.42) for percent and absolute dense volume, respectively]. CONCLUSIONS In a high-throughput setting, Volpara performs well and in accordance with the behavior of established density measures. IMPACT Automated measurement of volumetric mammographic density is a promising tool for widespread breast cancer risk assessment.

DOI: 10.1158/1055-9965.EPI-13-1219

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@article{Brand2014AutomatedMO, title={Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment.}, author={Judith Brand and Kamila Czene and John A. Shepherd and Karin Leifland and Boel Heddson and Ann Sundbom and Mikael Eriksson and Jingmei Li and Keith Humphreys and Per Hall}, journal={Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology}, year={2014}, volume={23 9}, pages={1764-72} }