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Updated: Jul 10, 2026
09:30
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Accelerated short-TE 3D proton echo-planar spectroscopic imaging using 2D-SENSE with a 32-channel array coil
Ricardo Otazo1, Shang-Yueh Tsai, Fa-Hsuan Lin
1Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, New Mexico 87131, USA. otazo@ece.unm.edu
Magnetic Resonance in Medicine
|October 31, 2007
Summary
This study introduces a fast 3D MR Spectroscopic Imaging (MRSI) method combining proton echo planar spectroscopic imaging (PEPSI) with 2D-SENSE. This technique enables whole-brain metabolite mapping in just one minute, significantly reducing acquisition time for clinical studies.
Area of Science:
- Medical Imaging
- Magnetic Resonance Imaging
- Spectroscopy
Background:
- Whole-brain MR Spectroscopic Imaging (MRSI) is challenging due to long acquisition times.
- Parallel imaging and 2D acceleration show promise for reducing MRSI encoding times.
Purpose of the Study:
- To develop a very high-speed 3D-MRSI method for whole-brain coverage in clinically feasible times.
- To improve MRSI by combining proton echo planar spectroscopic imaging (PEPSI) with regularized 2D-SENSE reconstruction.
Main Methods:
- Developed a 3D-PEPSI method with regularized 2D-SENSE reconstruction.
- Applied singular value decomposition constraints and unaliased the point spread function to minimize artifacts.
- Utilized a 32-channel array coil for 8-fold acceleration (R = 4x2) along y-z at 3 Tesla.
Main Results:
- Achieved a minimum acquisition time of 1 minute for 3D-MRSI with a 32x32x8 spatial matrix.
- Reduced contamination from extracranial lipids by 1.6-fold compared to standard SENSE.
- Generated volumetric metabolite maps (NAA, Cr, Cho, Glu) with acceptable spatial-spectral quality.
Conclusions:
- The developed high-speed 3D-MRSI method significantly reduces acquisition time.
- This technique is suitable for volumetric metabolite mapping in clinical settings.
- The method offers a promising approach for accelerated whole-brain MRSI.
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