title: Optimized diffusion gradient orientation schemes for corrupted clinical DTI data sets.
abstract: OBJECTIVE
  A method is proposed for generating schemes of diffusion gradient orientations which allow the diffusion tensor to be reconstructed from partial data sets in clinical DT-MRI, should the acquisition be corrupted or terminated before completion because of patient motion.
  
  
  METHODS
  A general energy-minimization electrostatic model was developed in which the interactions between orientations are weighted according to their temporal order during acquisition. In this report, two corruption scenarios were specifically considered for generating relatively uniform schemes of 18 and 60 orientations, with useful subsets of 6 and 15 orientations. The sets and subsets were compared to conventional sets through their energy, condition number and rotational invariance. Schemes of 18 orientations were tested on a volunteer.
  
  
  RESULTS
  The optimized sets were similar to uniform sets in terms of energy, condition number and rotational invariance, whether the complete set or only a subset was considered. Diffusion maps obtained in vivo were close to those for uniform sets whatever the acquisition time was. This was not the case with conventional schemes, whose subset uniformity was insufficient.
  
  
  CONCLUSIONS
  With the proposed approach, sets of orientations responding to several corruption scenarios can be generated, which is potentially useful for imaging uncooperative patients or infants.
authors.affiliation: Service Hospitalier Frédéric Joliot, CEA, Orsay, France. Jessica.Dubois@medecine.unige.ch
authors.forename: J
authors.initials: J
authors.lastname: Dubois
authors.forename: C
authors.initials: C
authors.lastname: Poupon
authors.forename: F
authors.initials: F
authors.lastname: Lethimonnier
authors.forename: D
authors.initials: D
authors.lastname: Le Bihan
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D016208:Databases, Factual; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009068:Movement; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity