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

Judith S Brand, Kamila Czene, John A Shepherd, Karin Leifland, Boel Heddson, Ann Sundbom, Mikael Eriksson, Jingmei Li, Keith Humphreys, Per Hall

Research output: Contribution to journalArticle (Academic Journal)peer-review

48 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1764-72
Number of pages9
JournalCancer Epidemiology, Biomarkers and Prevention
Volume23
Issue number9
DOIs
Publication statusPublished - Sep 2014

Keywords

  • Aged
  • Automation
  • Breast Density
  • Breast Neoplasms
  • Cohort Studies
  • Early Detection of Cancer
  • Female
  • Genotype
  • Humans
  • Mammary Glands, Human
  • Mammography
  • Middle Aged
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Surveys and Questionnaires
  • Sweden
  • Journal Article
  • Research Support, Non-U.S. Gov't

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