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Comparison of generalized autocalibrating partially parallel acquisitions and modified sensitivity encoding for

Y A Bhagat¹, D J Emery, S Naik

¹Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.

AJNR. American Journal of Neuroradiology

|February 14, 2007

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Parallel imaging techniques like GRAPPA and mSENSE significantly reduce artifacts in brain diffusion tensor imaging (DTI). Acceleration factor 2 (R=2) yielded high-quality images and reproducible quantitative diffusion measurements.

Area of Science:

Neuroimaging
Magnetic Resonance Imaging (MRI)
Diffusion Tensor Imaging (DTI)

Background:

Conventional DTI brain imaging uses single-shot echo-planar imaging, prone to signal loss, geometric distortions, and blurring.
Parallel imaging techniques shorten echo-train acquisition, potentially reducing these artifacts.

Purpose of the Study:

Evaluate self-calibrating parallel acquisition techniques: modified sensitivity encoding (mSENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA).
Compare these techniques against conventional DTI in healthy subjects.

Main Methods:

GRAPPA and mSENSE with acceleration factors (R) up to 4 were compared to conventional DTI.
Image quality was assessed qualitatively (sharpness, artifacts) and quantitatively (SNR, ADC, FA) in white and gray matter regions.

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Main Results:

Reviewers preferred GRAPPA and mSENSE at R=2 over conventional DTI.
Improved fractional anisotropy (FA) contrast was observed at the gray/white matter junction.
While quantitative diffusion measurements (ADC, FA) were consistent, higher acceleration factors (R=3,4) introduced reconstruction artifacts.

Conclusions:

GRAPPA and mSENSE with R=2 effectively minimize susceptibility and off-resonance artifacts in DTI.
These parallel imaging methods produce high-quality brain images and reliable quantitative diffusion data.