Compressed sensing for high-resolution nonlipid suppressed 1H FID MRSI of the human brain at 9.4T
Corresponding Author
Sahar Nassirpour
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
Sahar Nassirpour and Paul Chang contributed equally to this work.
Correspondence Sahar Nassirpour, Max Planck Institute for Biological Cybernetics, Spemannstrasse 41, 72076 Tübingen, Germany. Email: [email protected]Search for more papers by this authorPaul Chang
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
Sahar Nassirpour and Paul Chang contributed equally to this work.
Search for more papers by this authorNikolai Avdievitch
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
Search for more papers by this authorAnke Henning
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
Search for more papers by this authorCorresponding Author
Sahar Nassirpour
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
Sahar Nassirpour and Paul Chang contributed equally to this work.
Correspondence Sahar Nassirpour, Max Planck Institute for Biological Cybernetics, Spemannstrasse 41, 72076 Tübingen, Germany. Email: [email protected]Search for more papers by this authorPaul Chang
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
Sahar Nassirpour and Paul Chang contributed equally to this work.
Search for more papers by this authorNikolai Avdievitch
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
Search for more papers by this authorAnke Henning
Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
Search for more papers by this authorFunding information: Grant sponsor: European Research Council Starting, Grant Number: SYNAPLAST MR #679927; Grant sponsor: Horizon 2020, Grant Number: CDS_QUAMRI #634541
Abstract
Purpose
The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra-short TR and TE 1H FID MRSI sequence at 9.4T.
Methods
X-t sparse compressed sensing reconstruction was optimized for nonlipid suppressed 1H FID MRSI data. Coil-by-coil x-t sparse reconstruction was compared with SENSE x-t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared.
Results
Coil-by-coil x-t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x-t sparse). For acceleration factors of up to 5, both the low-rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved.
Conclusion
By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min.
Supporting Information
Additional Supporting Information may be found in the online version of this article.
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| mrm27225-sup-0001-suppinfo01.pdf1.3 MB |
FIGURE S1 Representative spectra from R = 4 acceleration resulting from the coil-by-coil x-t sparse reconstruction (red) and the SENSE x-t sparse reconstruction (black). For visualization purposes, only every four voxel in the grid has been shown. The spectra are shown between 0.1 and 4.2 ppm FIGURE S2 Metabolite maps for three major metabolites (NAA, Glu, and tCho) shown for different acceleration factors on the same volunteer as in Figure 6. Metabolite maps are shown for the compressed sensing reconstruction (top) and alternatively for the low rank reconstruction (bottom) FIGURE S3 Metabolite maps of four major metabolites (NAA, Cre, Glu, and tCho) resulting from applying the CS method for prospective in vivo acceleration (with R = 5) in 3 healthy subjects FIGURE S4 Accelerated reduced resolution metabolite maps of the same volunteer as Figure 8 using the compressed sensing reconstruction for different acceleration factors. Metabolite maps with in-plane matrix sizes of 48 × 48 and 32 × 32 are shown in the top and bottom panels, respectively. The maps are shown for NAA, Glu, and tCho |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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