title: Improvements of an objective model of compressed breasts undergoing mammography: Generation and characterization of breast shapes.
abstract: OBJECTIVE
  To develop a set of accurate 2D models of compressed breasts undergoing mammography or breast tomosynthesis, based on objective analysis, to accurately characterize mammograms with few linearly independent parameters, and to generate novel clinically realistic paired cranio-caudal (CC) and medio-lateral oblique (MLO) views of the breast.
  
  
  METHODS
  We seek to improve on an existing model of compressed breasts by overcoming detector size bias, removing the nipple and non-mammary tissue, pairing the CC and MLO views from a single breast, and incorporating the pectoralis major muscle contour into the model. The outer breast shapes in 931 paired CC and MLO mammograms were automatically detected with an in-house developed segmentation algorithm. From these shapes three generic models (CC-only, MLO-only, and joint CC/MLO) with linearly independent components were constructed via principal component analysis (PCA). The ability of the models to represent mammograms not used for PCA was tested via leave-one-out cross-validation, by measuring the average distance error (ADE).
  
  
  RESULTS
  The individual models based on six components were found to depict breast shapes with accuracy (mean ADE-CC = 0.81 mm, ADE-MLO = 1.64 mm, ADE-Pectoralis = 1.61 mm), outperforming the joint CC/MLO model (P ≤ 0.001). The joint model based on 12 principal components contains 99.5% of the total variance of the data, and can be used to generate new clinically realistic paired CC and MLO breast shapes. This is achieved by generating random sets of 12 principal components, following the Gaussian distributions of the histograms of each component, which were obtained from the component values determined from the images in the mammography database used.
  
  
  CONCLUSIONS
  Our joint CC/MLO model can successfully generate paired CC and MLO view shapes of the same simulated breast, while the individual models can be used to represent with high accuracy clinical acquired mammograms with a small set of parameters. This is the first step toward objective 3D compressed breast models, useful for dosimetry and scatter correction research, among other applications.
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Rodríguez-Ruiz
authors.affiliation: Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, GA, 30322, USA.
authors.forename: Steve Si Jia
authors.initials: SSJ
authors.lastname: Feng
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.
authors.forename: Jan
authors.initials: J
authors.lastname: van Zelst
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.
authors.forename: Suzan
authors.initials: S
authors.lastname: Vreemann
authors.affiliation: Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA.
authors.forename: Jessica Rice
authors.initials: JR
authors.lastname: Mann
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University, 1701 Uppergate Drive Northeast, Suite 5018, Atlanta, GA, 30322, USA.
authors.forename: Carl Joseph
authors.initials: CJ
authors.lastname: D'Orsi
authors.affiliation: Department of Radiology and Nuclear Medicine, Radboud University Medical Centre, Geert Grooteplein 10, 6525, GA, Nijmegen, The Netherlands.|Dutch Reference Centre for Screening (LRCB), Wijchenseweg 101, 6538, SW, Nijmegen, The Netherlands.
authors.forename: Ioannis
authors.initials: I
authors.lastname: Sechopoulos
mesh_terms: D000465:Algorithms; D001940:Breast; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography; D010369:Pectoralis Muscles; D025341:Principal Component Analysis
keywords: breast modeling; breast phantoms; image segmentation; mammography; tomosynthesis