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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Effects of random subject rotation on optimised diffusion gradient sampling schemes in diffusion tensor MRI.

Susana Muñoz Maniega1, Mark E Bastin, Paul A Armitage

  • 1Clinical Neurosciences, Western General Hospital, University of Edinburgh, EH4 2XU Edinburgh, UK.

Magnetic Resonance Imaging
|December 13, 2007
PubMed
Summary
This summary is machine-generated.

Optimizing diffusion tensor imaging (DTI) requires careful consideration of gradient sampling. This study reveals that while more sampling orientations reduce motion artifacts, significant subject rotation necessitates B-matrix recalculation for accurate fractional anisotropy (FA) estimation.

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Area of Science:

  • Medical Imaging
  • Neuroscience
  • Biophysics

Background:

  • Accurate water diffusion tensor measurement in diffusion tensor MRI (DT-MRI) depends on the number and orientation of diffusion sampling gradients.
  • Previous Monte Carlo studies suggested 20-30 orientations for robust diffusion parameter estimation.
  • The impact of subject motion, particularly rotation, on optimized gradient schemes has not been adequately addressed in clinical DT-MRI.

Purpose of the Study:

  • To investigate the effect of subject motion, specifically rotation, on diffusion tensor imaging (DTI) sampling schemes.
  • To evaluate the performance of icosahedral sampling schemes under simulated and in vivo rotational motion.
  • To determine optimal strategies for maintaining accurate diffusion parameter estimation in the presence of subject motion.

Main Methods:

  • Utilized Monte Carlo simulations to assess icosahedral sampling schemes.
  • Incorporated varying degrees of random subject rotation (alpha) into simulations.
  • Analyzed in vivo diffusion tensor MRI data to validate simulation findings.
  • Investigated the relationship between the number of sampling orientations (N) and rotational variance.

Main Results:

  • Increasing the number of sampling orientations (N) reduced the dependency of fractional anisotropy (FA) rotational variance on rotation magnitude (alpha).
  • Higher FA values were progressively underestimated as rotation (alpha) increased.
  • Polyhedra-based schemes demonstrated potential for use with restless subjects, allowing for optimized subsets if scanning is interrupted.

Conclusions:

  • For significant subject rotations in DT-MRI, recalculating the B-matrix is crucial for accurate diffusion anisotropy information.
  • Icosahedral sampling schemes offer advantages for studies involving subjects prone to motion.
  • Further research is needed to refine gradient schemes and motion correction techniques in DT-MRI.