High-resolution human diffusion tensor imaging using 2-D navigated multishot SENSE EPI at 7 T.

Jeong HK, Gore JC, Anderson AW
Magn Reson Med. 2013 69 (3): 793-802

PMID: 22592941 · PMCID: PMC3424313 · DOI:10.1002/mrm.24320

The combination of parallel imaging with partial Fourier acquisition has greatly improved the performance of diffusion-weighted single-shot EPI and is the preferred method for acquisitions at low to medium magnetic field strength such as 1.5 or 3 T. Increased off-resonance effects and reduced transverse relaxation times at 7 T, however, generate more significant artifacts than at lower magnetic field strength and limit data acquisition. Additional acceleration of k-space traversal using a multishot approach, which acquires a subset of k-space data after each excitation, reduces these artifacts relative to conventional single-shot acquisitions. However, corrections for motion-induced phase errors are not straightforward in accelerated, diffusion-weighted multishot EPI because of phase aliasing. In this study, we introduce a simple acquisition and corresponding reconstruction method for diffusion-weighted multishot EPI with parallel imaging suitable for use at high field. The reconstruction uses a simple modification of the standard sensitivity-encoding (SENSE) algorithm to account for shot-to-shot phase errors; the method is called image reconstruction using image-space sampling function (IRIS). Using this approach, reconstruction from highly aliased in vivo image data using 2-D navigator phase information is demonstrated for human diffusion-weighted imaging studies at 7 T. The final reconstructed images show submillimeter in-plane resolution with no ghosts and much reduced blurring and off-resonance artifacts.

Copyright © 2012 Wiley Periodicals, Inc.

MeSH Terms (10)

Algorithms Brain Diffusion Magnetic Resonance Imaging Electron Spin Resonance Spectroscopy Humans Image Enhancement Image Interpretation, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted

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