title: High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer.
abstract: BACKGROUND
  Mammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.
  
  
  METHODS
  We randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). The Pearson product-moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.
  
  
  RESULTS
  We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884; 95% CI, 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002).
  
  
  CONCLUSIONS
  Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.
authors: Jingmei
authors: J
authors: Li
authors: Laszlo
authors: L
authors: Szekely
authors: Louise
authors: L
authors: Eriksson
authors: Boel
authors: B
authors: Heddson
authors: Ann
authors: A
authors: Sundbom
authors: Kamila
authors: K
authors: Czene
authors: Per
authors: P
authors: Hall
authors: Keith
authors: K
authors: Humphreys
mesh_terms: D000368:Aged; D019540:Area Under Curve; D001185:Artificial Intelligence; D000071060:Breast Density; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D016022:Case-Control Studies; D055088:Early Detection of Cancer / Q000379:methods; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D042361:Mammary Glands, Human / Q000002:abnormalities*; D008327:Mammography / Q000379:methods / Q000592:standards; D008875:Middle Aged; D018570:Risk Assessment; D012307:Risk Factors