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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Chang, H-C; Guhaniyogi, S; Chen, N-K

Published Date

  • May 2015

Published In

Volume / Issue

  • 73 / 5

Start / End Page

  • 1872 - 1884

PubMed ID

  • 24925000

Pubmed Central ID

  • 24925000

Electronic International Standard Serial Number (EISSN)

  • 1522-2594

Digital Object Identifier (DOI)

  • 10.1002/mrm.25318

Language

  • eng

Conference Location

  • United States