Interleaved diffusion-weighted improved by adaptive partial-Fourier and multiband multiplexed sensitivity-encoding reconstruction.

Abstract:

PURPOSE:We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion-weighted imaging (DWI). METHODS:First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either (a) motion-induced k-space energy peak displacement, or (b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multiband MUSE, so that both through-plane and in-plane aliasing artifacts in multiband multishot interleaved DWI data can be effectively eliminated. RESULTS:The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multiband and high-throughput DWI. CONCLUSION:The integration of the multiband and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses.

journal_name

Magn Reson Med

authors

Chang HC,Guhaniyogi S,Chen NK

doi

10.1002/mrm.25318

subject

Has Abstract

pub_date

2015-05-01 00:00:00

pages

1872-84

issue

5

eissn

0740-3194

issn

1522-2594

journal_volume

73

pub_type

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