title: Quantitative breast MRI: 2D histogram analysis of diffusion tensor parameters in normal tissue.
abstract: OBJECTIVE
  Diffusion tensor imaging (DTI) of the breast may provide a powerful new approach for the detection of intraductal processes. The aim of this investigation was to characterize the relation between diffusion tensor parameters [fractional anisotropy (FA), mean diffusivity (MD)] in normal breast tissue to obtain information on the microenvironment of the diffusing water molecules and to provide a systematic approach for DTI analysis.
  
  
  METHODS
  Seven female, healthy volunteers underwent prospective double-spin-echo prepared echo-planar diffusion-weighted sequence (TR/TE 8,250 ms/74 ms, b values 0 and 500 s/mm (2), six encoding directions, 12 averages, 35 slices) in 4 consecutive weeks (3.0 T). Quantitative maps of diffusion tensor parameters were computed offline with custom routines. The interdependence of MD and FA in different voxels was analysed by linear and exponential regression.
  
  
  RESULTS
  All MD and FA maps were of excellent quality. A consistent pattern was observed in that lower fractional anisotropy values were more likely associated with higher mean diffusivity values. The dependence exhibited an exponential behavior with a correlation coefficient R = 0.60 (R linear = 0.57).
  
  
  CONCLUSIONS
  The likelihood with which FA and MD values are observed in a voxel within normal breast tissue is characterized by a specific pattern, which can be described by an exponential model. Moreover, we could show that the proposed technique does not depend on the menstrual cycle.
authors.affiliation: Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Raemistr. 100, 8091, Zurich, Switzerland, julia.wiederer@usz.ch.
authors.forename: Julia
authors.initials: J
authors.lastname: Wiederer
authors.forename: Shila
authors.initials: S
authors.lastname: Pazahr
authors.forename: Cornelia
authors.initials: C
authors.lastname: Leo
authors.forename: Daniel
authors.initials: D
authors.lastname: Nanz
authors.forename: Andreas
authors.initials: A
authors.lastname: Boss
mesh_terms: D000328:Adult; D000465:Algorithms; D001940:Breast / Q000033:anatomy & histology* / Q000502:physiology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008597:Menstrual Cycle / Q000502:physiology*; D009716:Numerical Analysis, Computer-Assisted; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult