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Updated: Jul 17, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
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.
Background And Purpose:
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.
