title: Analysing breast tissue composition with MRI using currently available short, simple sequences.
abstract: OBJECTIVE
  To determine the most robust commonly available magnetic resonance imaging (MRI) sequence to quantify breast tissue composition at 1.5 T.
  
  
  METHODS
  Two-dimensional (2D) T1-weighted, Dixon fat, Dixon water and SPAIR images were obtained from five participants and a breast phantom using a 1.5 T Siemens Aera MRI system. Manual segmentation of the breasts was performed, and an in-house computer program was used to generate signal intensity histograms. Relative trough depth and relative peak separation were used to determine the robustness of the images for quantifying the two breast tissues. Total breast volumes and percentage breast densities calculated using the four sequences were compared.
  
  
  RESULTS
  Dixon fat histograms had consistently low relative trough depth and relative peak separation compared to those obtained using other sequences. There was no significant difference in total breast volumes and percentage breast densities of the participants or breast phantom using Dixon fat and 2D T1-weighted histograms. Dixon water and SPAIR histograms were not suitable for quantifying breast tissue composition.
  
  
  CONCLUSIONS
  Dixon fat images are the most robust for the quantification of breast tissue composition using a signal intensity histogram.
authors.affiliation: Department of Medical Radiation Science, Curtin University, Bentley Campus, WA 6101, Australia. Electronic address: anson.chau@curtin.edu.au.
authors.forename: A C M
authors.initials: AC
authors.lastname: Chau
authors.affiliation: Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, WA 6001, Australia.
authors.forename: J
authors.initials: J
authors.lastname: Hua
authors.affiliation: Department of Diagnostic and Interventional Radiology, Royal Perth Hospital, Perth, WA 6001, Australia; School of Surgery, University of Western Australia, Crawley, WA 6009, Australia.
authors.forename: D B
authors.initials: DB
authors.lastname: Taylor
mesh_terms: D000328:Adult; D001940:Breast / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging