Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T. Tijssen, R. H., Jansen, J. F., & Backes, W. H. Hum Brain Mapp, 30(8):2641-55, 2009. Tijssen, Rob H N Jansen, Jacobus F A Backes, Walter H eng Research Support, Non-U.S. Gov't 2008/12/17 09:00 Hum Brain Mapp. 2009 Aug;30(8):2641-55. doi: 10.1002/hbm.20695.
Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T [link]Paper  doi  abstract   bibtex   
Compared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices.
@article{RN136,
   author = {Tijssen, R. H. and Jansen, J. F. and Backes, W. H.},
   title = {Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T},
   journal = {Hum Brain Mapp},
   volume = {30},
   number = {8},
   pages = {2641-55},
   note = {Tijssen, Rob H N
Jansen, Jacobus F A
Backes, Walter H
eng
Research Support, Non-U.S. Gov't
2008/12/17 09:00
Hum Brain Mapp. 2009 Aug;30(8):2641-55. doi: 10.1002/hbm.20695.},
   abstract = {Compared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices.},
   keywords = {Adult
Algorithms
Anisotropy
*Artifacts
Brain/anatomy & histology
Computer Simulation
Diffusion Magnetic Resonance Imaging/*methods
Female
Humans
Male
Monte Carlo Method
*Motion
Reproducibility of Results
Uncertainty
Young Adult},
   ISSN = {1097-0193 (Electronic)
1065-9471 (Linking)},
   DOI = {10.1002/hbm.20695},
   url = {http://www.ncbi.nlm.nih.gov/pubmed/19086023
https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.20695},
   year = {2009},
   type = {Journal Article}
}

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