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Accelerating phase-encoded proton MR spectroscopic imaging by compressed sensing.

Peng Cao1, Ed X Wu

  • 1Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China; Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong SAR, China.

Journal of Magnetic Resonance Imaging : JMRI
|January 18, 2014
PubMed
Summary
This summary is machine-generated.

Compressed sensing (CS) accelerates phase-encoded (1) H MR spectroscopic imaging (MRSI) by reducing phase encoding steps. This method preserves spectral resolution and metabolite levels, demonstrating feasibility for faster MRSI acquisition.

Keywords:
MR spectroscopic imagingcompressed sensingphase encoding reductionsparsity

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Area of Science:

  • Magnetic Resonance Imaging
  • Spectroscopy
  • Medical Imaging Technology

Background:

  • Phase-encoded (1) H MR spectroscopic imaging (MRSI) is crucial for in vivo metabolite quantification.
  • Acquisition time is a significant limitation in conventional MRSI due to extensive phase encoding steps.
  • Compressed sensing (CS) offers a potential solution for accelerating MRSI by undersampling k-space data.

Purpose of the Study:

  • To develop and evaluate a compressed sensing (CS) based phase encoding reduction scheme for (1) H MR spectroscopic imaging (MRSI).
  • To assess the feasibility of CS for accelerating phase-encoded MRSI acquisition without compromising data quality.

Main Methods:

  • Phantom and in vivo rat brain MRSI experiments were conducted at 7 Tesla.
  • CS undersampling utilized pseudorandom, density-varying phase encoding subsets.
  • Reconstruction involved residual water resonance removal and linearized Bregman iteration for L1 minimization.
  • Spectral and spatial fidelity were assessed using linewidths, metabolite maps, and Bland-Altman analysis.

Main Results:

  • Compressed sensing (CS) successfully preserved spectral resolution and metabolite content.
  • No significant spectral broadening was observed.
  • Estimation biases for metabolite levels were within 4%, with preserved metabolite map boundaries but minor loss of detail.

Conclusions:

  • The proposed compressed sensing (CS) approach is feasible for accelerating phase-encoded (1) H MRSI.
  • CS provides a viable strategy to reduce acquisition time in MRSI.
  • Further optimization may improve detail preservation in metabolite maps.