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Whole‐Slab 3D MR Spectroscopic Imaging of the Human Brain With Spiral‐Out‐In Sampling at 7T
Author(s) -
Esmaeili Morteza,
Strasser Bernhard,
Bogner Wolfgang,
Moser Philipp,
Wang Zhe,
Andronesi Ovidiu C.
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27437
Subject(s) - imaging phantom , nuclear magnetic resonance , image quality , magnetic resonance spectroscopic imaging , shim (computing) , sampling (signal processing) , physics , magnetic resonance imaging , nuclear medicine , spiral (railway) , computer science , mathematics , optics , artificial intelligence , medicine , radiology , image (mathematics) , mathematical analysis , detector , erectile dysfunction
Background Metabolic imaging using proton magnetic resonance spectroscopic imaging (MRSI) has increased the sensitivity and spectral resolution at field strengths of ≥7T. Compared to the conventional Cartesian‐based spectroscopic imaging, spiral trajectories enable faster data collection, promising the clinical translation of whole‐brain MRSI. Technical considerations at 7T, however, lead to a suboptimal sampling efficiency for the spiral‐out (SO) acquisitions, as a significant portion of the trajectory consists of rewinders. Purpose To develop and implement a spiral‐out‐in (SOI) trajectory for sampling of whole‐brain MRSI at 7T. We hypothesized that SOI will improve the signal‐to‐noise ratio (SNR) of metabolite maps due to a more efficient acquisition. Study Type Prospective. Subjects/Phantom Five healthy volunteers (28–38 years, three females) and a phantom. Field Strength/Sequence Navigated adiabatic spin‐echo spiral 3D MRSI at 7T. Assessment A 3D stack of SOI trajectories was incorporated into an adiabatic spin‐echo MRSI sequence with real‐time motion and shim correction. Metabolite spectral fitting, SNR, and Cramér–Rao lower bound (CRLB) were obtained . We compared the signal intensity and CRLB of three metabolites of tNAA, tCr, and tCho. Peak SNR (PSNR), structure similarity index (SSIM), and signal‐to‐artifact ratio were evaluated on water maps. Statistical Tests The nonparametric Mann–Whitney U ‐test was used for statistical testing. Results Compared to SO, the SOI trajectory: 1) increased the k ‐space sampling efficiency by 23%; 2) is less demanding for the gradient hardware, requiring 36% lower G max and 26% lower S max ; 3) increased PSNR of water maps by 4.94 dB ( P = 0.0006); 4) resulted in a 29% higher SNR ( P = 0.003) and lower CRLB by 26–35% ( P = 0.02, tNAA), 35–55% ( P = 0.03, tCr), and 22–23% ( P = 0.04, tCho), which increased the number of well‐fitted voxels (eg, for tCr by 11%, P = 0.03). SOI did not significantly change the signal‐to‐artifact ratio and SSIM ( P = 0.65) compared to SO. Data Conclusion SOI provided more efficient MRSI at 7T compared to SO, which improved the data quality and metabolite quantification. Level of Evidence 1 Technical Efficacy Stage 2