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A Multimodal Wide-Field Fourier-Transform Raman Microscope
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Spatial spectral modeling for robust MRSI.

Ramin Eslami1, Mathews Jacob

  • 1Department of Biomedical Engineering, University of Rochester, Rochester, NY 14627, USA. reslami@ieee.org

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
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This study introduces a new model for magnetic resonance spectroscopic imaging (MRSI) reconstruction. It improves spectral quality and accuracy by better handling spatial and spectral data, even in difficult areas.

Area of Science:

  • Magnetic Resonance Imaging
  • Spectroscopic Imaging
  • Biomedical Engineering

Background:

  • Magnetic Resonance Spectroscopic Imaging (MRSI) is crucial for non-invasive metabolite analysis.
  • Reconstruction of MRSI signals faces challenges like spatial properties of metabolite peaks and spectral leakage.
  • Intra-voxel line shape distortions due to magnetic field variations affect spectral accuracy.

Purpose of the Study:

  • To develop a novel spatial spectral model for improved MRSI signal reconstruction.
  • To enhance spectral quality and accuracy in MRSI data.
  • To address challenges in challenging spatial regions and suppress spectral leakage.

Main Methods:

  • Utilizing a spatial total variation norm to exploit spatial properties of metabolite peaks.

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  • Modeling the spectral signal as a sparse linear combination of spikes and polynomials.
  • Incorporating a high-resolution magnetic field map to correct for intra-voxel line shape distortions.
  • Acquiring MRSI data using Echo-Planar Spectroscopic Imaging (EPSI) and high-resolution MRI using Dixon scans.

    • Main Results:

    • The proposed model enables stable signal recovery in challenging spatial regions.
    • The spatial model effectively suppresses spectral leakage from extra-cranial fat and inter-voxel crosstalk.
    • Reconstruction of phantom and in vivo data shows significant improvements in spectral quality and accuracy compared to classical MRSI methods.

    Conclusions:

    • The novel spatial spectral model significantly advances MRSI reconstruction.
    • This method offers enhanced spectral quality and accuracy, crucial for metabolite analysis.
    • The approach is robust and effective for both phantom and in vivo MRSI data.