title: DTI parameter optimisation for acquisition at 1.5T: SNR analysis and clinical application.
abstract: BACKGROUND
  Magnetic Resonance (MR) diffusion tensor imaging (DTI) is able to quantify in vivo tissue microstructure properties and to detect disease related pathology of the central nervous system. Nevertheless, DTI is limited by low spatial resolution associated with its low signal-to-noise-ratio (SNR).
  
  
  OBJECTIVE
  The aim is to select a DTI sequence for brain clinical studies, optimizing SNR and resolution.
  
  
  RESULTS
  We applied 6 methods for SNR computation in 26 DTI sequences with different parameters using 4 healthy volunteers (HV). We choosed two DTI sequences for their high SNR, they differed by voxel size and b-value. Subsequently, the two selected sequences were acquired from 30 multiple sclerosis (MS) patients with different disability and lesion load and 18 age matched HV. We observed high concordance between mean diffusivity (MD) and fractional anysotropy (FA), nonetheless the DTI sequence with smaller voxel size displayed a better correlation with disease progression, despite a slightly lower SNR. The reliability of corpus callosum (CC) fiber tracking with the chosen DTI sequences was also tested.
  
  
  CONCLUSIONS
  The sensitivity of DTI-derived indices to MS-related tissue abnormalities indicates that the optimized sequence may be a powerful tool in studies aimed at monitoring the disease course and severity.
authors.affiliation: Polo Tecnologico, Fondazione Don Gnocchi ONLUS, IRCCS S. Maria Nascente, 20148 Milano, Italy.
authors.forename: M
authors.initials: M
authors.lastname: Laganà
authors.forename: M
authors.initials: M
authors.lastname: Rovaris
authors.forename: A
authors.initials: A
authors.lastname: Ceccarelli
authors.forename: C
authors.initials: C
authors.lastname: Venturelli
authors.forename: S
authors.initials: S
authors.lastname: Marini
authors.forename: G
authors.initials: G
authors.lastname: Baselli
mesh_terms: D000328:Adult; D000465:Algorithms; D016880:Anisotropy; D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology*; D003337:Corpus Callosum / Q000033:anatomy & histology / Q000473:pathology; D056324:Diffusion Tensor Imaging / Q000295:instrumentation* / Q000379:methods*; D004185:Disability Evaluation; D018450:Disease Progression; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000473:pathology*; D020528:Multiple Sclerosis, Chronic Progressive / Q000473:pathology; D020529:Multiple Sclerosis, Relapsing-Remitting / Q000473:pathology; D009434:Neural Pathways / Q000033:anatomy & histology / Q000473:pathology; D015203:Reproducibility of Results; D055815:Young Adult