title: Inter-sequence and inter-imaging unit variability of diffusion tensor MR imaging histogram-derived metrics of the brain in healthy volunteers.
abstract: OBJECTIVE
  Diffusion tensor MR imaging has the potential to improve our ability to monitor several neurologic conditions. As a preliminary step to the assessment of the role of diffusion tensor MR imaging in the context of longitudinal and multicenter studies, we evaluated the effect of sequence-, imaging unit-, and imaging-reimaging-induced variations on diffusion tensor MR imaging quantities derived from histogram analysis of a large portion of the central brain of healthy volunteers.
  
  
  METHODS
  Each of eight healthy volunteers underwent imaging on two MR imaging units using three different pulsed gradient spin-echo single shot echo-planar pulse sequences (each of them having a different diffusion gradient scheme). Four additional healthy participants underwent imaging twice on the same imaging unit to assess imaging-reimaging variability.
  
  
  RESULTS
  For mean diffusivity histograms, the differences between inter-sequence and inter-imaging unit coefficients of variation were significant for all the considered quantities with P values ranging from.003 to <.001. Also, the inter-imaging unit coefficient of variation for average fractional anisotropy was significantly higher than the corresponding inter-sequence coefficient of variation (P =.002). In general, inter-sequence mean diffusivity histogram-derived metrics (coefficients of variation ranging from 1.72% to 5.56%) were more reproducible than were fractional anisotropy histogram-derived metrics (coefficients of variation ranging from 5.45% to 7.34%). Imaging-reimaging variability was found to fall in the range of inter-sequence coefficients of variation for all the considered quantities.
  
  
  CONCLUSIONS
  This study shows that inter-sequence, imaging-reimaging, and inter-imaging unit variabilities of diffusion tensor MR imaging-derived measurements are relatively low, suggesting that diffusion tensor MR imaging might provide additional measures of outcome with which to assess the evolution of brain structural damage in large scale studies of various neurologic conditions.
authors.affiliation: Neuroimaging Research Unit, Department of Neuroscience, Scientific Institute, Milan, Italy.
authors.forename: Mara
authors.initials: M
authors.lastname: Cercignani
authors.forename: Roland
authors.initials: R
authors.lastname: Bammer
authors.forename: Maria P
authors.initials: MP
authors.lastname: Sormani
authors.forename: Franz
authors.initials: F
authors.lastname: Fazekas
authors.forename: Massimo
authors.initials: M
authors.lastname: Filippi
mesh_terms: D000704:Analysis of Variance; D001921:Brain / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation / Q000592:standards*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000592:standards*; D008137:Longitudinal Studies; D015337:Multicenter Studies as Topic; D012015:Reference Standards; D015203:Reproducibility of Results