title: High-resolution multishot spiral diffusion tensor imaging with inherent correction of motion-induced phase errors.
abstract: OBJECTIVE
  To develop and compare three novel reconstruction methods designed to inherently correct for motion-induced phase errors in multishot spiral diffusion tensor imaging without requiring a variable-density spiral trajectory or a navigator echo.
  
  
  METHODS
  The first method simply averages magnitude images reconstructed with sensitivity encoding from each shot, whereas the second and third methods rely on sensitivity encoding to estimate the motion-induced phase error for each shot and subsequently use either a direct phase subtraction or an iterative conjugate gradient algorithm, respectively, to correct for the resulting artifacts. Numerical simulations and in vivo experiments on healthy volunteers were performed to assess the performance of these methods.
  
  
  RESULTS
  The first two methods suffer from a low signal-to-noise ratio or from residual artifacts in the reconstructed diffusion-weighted images and fractional anisotropy maps. In contrast, the third method provides high-quality, high-resolution diffusion tensor imaging results, revealing fine anatomical details such as a radial diffusion anisotropy in cortical gray matter.
  
  
  CONCLUSIONS
  The proposed sensitivity encoding + conjugate gradient method can inherently and effectively correct for phase errors, signal loss, and aliasing artifacts caused by both rigid and nonrigid motion in multishot spiral diffusion tensor imaging, without increasing the scan time or reducing the signal-to-noise ratio.
authors: Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA.
authors: Trong-Kha
authors: TK
authors: Truong
authors: Arnaud
authors: A
authors: Guidon
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity