title: Comparison of generalized autocalibrating partially parallel acquisitions and modified sensitivity encoding for diffusion tensor imaging.
abstract: OBJECTIVE
  Diffusion tensor magnetic resonance imaging (DTI) of the brain is usually acquired with single-shot echo-planar imaging, which is associated with localized signal loss, geometric distortions, and blurring. Parallel imaging can lessen these artifacts by shortening the length of the echo-train acquisition. The self-calibrating parallel acquisition techniques, image domain-based modified sensitivity encoding (mSENSE) and k-space-based generalized autocalibrating partially parallel acquisitions (GRAPPA), were evaluated with DTI of the brain in 5 healthy subjects.
  
  
  METHODS
  GRAPPA and mSENSE with higher acceleration factors (R) up to 4 were compared with conventional DTI (with and without phase partial Fourier, another method of reducing the echo-train length) on a 1.5T Sonata scanner (Siemens, Erlangen, Germany). The resulting images and diffusion maps were evaluated qualitatively and quantitatively. Qualitative analysis was performed by 3 reviewers blinded to the technique using image sharpness and the level of artifacts as characteristics for scoring each set of images. Quantitative comparisons encompassed measuring signal-to-noise ratio, Trace/3 apparent diffusion coefficient (ADC), and fractional anisotropy (FA) in 6 white-matter (WM) and gray-matter (GM) regions.
  
  
  RESULTS
  Reviewers scored the GRAPPA and mSENSE R = 2 images better than images acquired with conventional techniques. FA contrast was improved at the GM/WM junction in peripheral brain areas. Trace/3 ADC and FA measurements were consistent for all methods. However, R = 3,4 images suffered from reconstruction-related artifacts.
  
  
  CONCLUSIONS
  GRAPPA and mSENSE (R = 2) minimized the susceptibility and off-resonance effects associated with conventional DTI methods, yielding high-quality images and reproducible quantitative diffusion measurements.
authors.affiliation: Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.
authors.forename: Y A
authors.initials: YA
authors.lastname: Bhagat
authors.forename: D J
authors.initials: DJ
authors.lastname: Emery
authors.forename: S
authors.initials: S
authors.lastname: Naik
authors.forename: T
authors.initials: T
authors.lastname: Yeo
authors.forename: C
authors.initials: C
authors.lastname: Beaulieu
mesh_terms: D000328:Adult; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping / Q000379:methods*; D002138:Calibration; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000592:standards; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity