Fast high‐resolution brain metabolite mapping on a clinical 3T MRI by accelerated H‐FID‐MRSI and low‐rank constrained reconstruction

Klauser, Antoine; Courvoisier, Sébastien; Kasten, Jeffrey; Kocher, Michel; Guerquin-Kern, M.; Ville, Dimitri Van De; Lazeyras, François

doi:10.1002/mrm.27623

Cited by 26 publications

(48 citation statements)

References 54 publications

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“…The present study did not directly compare this acquisition to others at 3Tesla in which the nominal resolution ranged from 300 μL (31) to 1000 μL (32). However, the resulted nominal resolution and metabolite maps achieved in this study are comparable (62.5 μL vs 40 μL) to the ones in which constrained reconstruction methods with FID acquisition were used (33,34). The achieved nominal resolution and provided metabolite maps within 9 minutes 36 seconds are also comparable with the ultra-high-field (UHF ≥ 7T) ones with nominal voxel sizes of 23 μL (35).…”

Section: Discussionsupporting

confidence: 61%

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High-Resolution Metabolic Mapping of the Cerebellum Using a Zoomed Magnetic Resonance Spectroscopic Imaging

Emir

Sood

Chiew

et al. 2020

Preprint

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Purpose: The human cerebellum plays an important role in functional activity cerebrum which is ranging from motor to cognitive activities since due to its relaying role between spinal cord and cerebrum. The cerebellum poses many challenges to magnetic resonance spectroscopic imaging (MRSI) due to the caudal location, the susceptibility to physiological artifacts and partial volume artifact due to its complex anatomical structure. Thus, in present study, we propose a high-resolution MRSI acquisition scheme for the cerebellum. Methods:A zoomed or reduced-field of view (rFOV) metabolite-cycled full-intensity magnetic resonance spectroscopic imaging (MRSI) at 3T with a nominal resolution of 62.5 μL was developed. Single-slice rFOV MRSI data were acquired from the cerebellum of 5 healthy subjects with a nominal resolution of 2.5 × 2.5 mm2 in 9 minutes 36. Spectra were quantified with LCModel. A spatially unbiased atlas template of the cerebellum was used for analyzing metabolite distributions in the cerebellum. Results:The high quality of the achieved spectra enabled to generate a high-resolution metabolic map of total N-acetylaspartate, total creatine, total choline, glutamate+glutamine and myo-inositol with Cramér-Rao lower bounds below 50%. A spatially unbiased atlas template of the cerebellum-based region of interest (ROIs) analysis resulted in spatially dependent metabolite distributions in 9 ROIs. The groupaveraging across subjects in the Montreal Neurological Institute-152 template space allowed to generate a very high-resolution metabolite maps in the cerebellum. Conclusion:These findings indicate that very high-resolution metabolite probing of cerebellum is feasible using rFOV or zoomed MRSI at 3T.

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Section: Discussionsupporting

confidence: 61%

“…Thus, we believe that our strategy offers substantial resolution improvement compared to the other implementations at 3T and UHF. With the use of constrained reconstruction methods, the proposed strategy is expected to provide higher resolution (33,34).…”

Section: Discussionmentioning

confidence: 99%

High-Resolution Metabolic Mapping of the Cerebellum Using a Zoomed Magnetic Resonance Spectroscopic Imaging

Emir

Sood

Chiew

et al. 2020

Preprint

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“…6 For high spectral bandwidths, the self-rewinding and constant-angular velocity properties of CRTs render them more SNR-efficient, faster, and less susceptible to gradient imperfections than other spatial-spectral encoding approaches. Although 3T MRI scanners are more widely available, so far only a few studies have used CRTs, 7,8 only 2 studies used FID-MRSI, 9,10 and no application has yet been reported for a combination of both at 3T. Besides being highly beneficial for clinical application, preliminary results 11 also raise the hope that the efficient combination of FID-MRSI and rapid CRT encoding could provide 3D mapping of glutamate with temporal and spatial resolutions high enough to observe stimuli-induced changes via functional MRSI.…”

Section: Introductionmentioning

confidence: 99%

Intra‐session and inter‐subject variability of 3D‐FID‐MRSI using single‐echo volumetric EPI navigators at 3T

Moser

Eckstein

Hingerl

et al. 2019

Magnetic Resonance in Med

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Purpose In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric‐ring trajectories (CRTs) at 3T. FID‐MRSI has many benefits including high detection sensitivity, in particular for J‐coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D‐FID‐MRSI sequence with single‐echo, imaging‐based volumetric navigators (se‐vNavs) for real‐time motion/shim‐correction (SHMOCO), which is 2× quicker than the original double‐echo navigators (de‐vNavs), hence allowing more efficient integration also in short‐TR sequences. Methods The tracking accuracy (position and B0‐field) of our proposed se‐vNavs was compared to the original de‐vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra‐session stability of a 5:40 min 3D‐FID‐MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter‐subject coefficients of variation (CV) and intra‐class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed. Results Phantom and in vivo scans showed highly consistent tracking performance for se‐vNavs compared to the original de‐vNavs, but lower frequency drift. Up to ~30% better intra‐subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m‐Ins ratios to tCr. ICCs were good‐to‐high (91% for Glx/tCr in motor cortex), whereas the inter‐subject variability was ~11–19%. Conclusion Real‐time motion/shim corrected 3D‐FID‐MRSI with time‐efficient CRT‐sampling at 3T allows reliable, high‐resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI.

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“…For instance, exploiting the Hankel low‐rank structures induced by the linear predictability properties in spectroscopy data may offer additional benefits . More advanced strategies to impose spatial prior information can also lead to potential improvements in SNR, and/or further reduction of artifacts (e.g., residual nuisance signals and spectral distortion) . The current subspace learning strategy assumes consistent subspace structures across different subjects (even when individual voxel spectra vary).…”

Section: Discussionmentioning

confidence: 99%

Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces

Lam

Guo

et al. 2019

Magnetic Resonance in Med

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Purpose:To develop a subspace learning method for the recently proposed subspace-based MRSI approach known as SPICE, and achieve ultrafast 1 H-MRSI of the brain. Theory and Methods: A novel strategy is formulated to learn a low-dimensional subspace representation of MR spectra from specially acquired training data and use the learned subspace for general MRSI experiments. Specifically, the subspace learning problem is formulated as learning "empirical" distributions of molecule-specific spectral parameters (e.g., concentrations, lineshapes, and frequency shifts) by integrating physics-based model and the training data. The learned spectral parameters and quantum mechanical simulation basis can then be combined to construct acquisition-specific subspace for spatiospectral encoding and processing. High-resolution MRSI acquisitions combining ultrashort-TE/short-TR excitation, sparse sampling, and the elimination of water suppression have been performed to evaluate the feasibility of the proposed method. Results: The accuracy of the learned subspace and the capability of the proposed method in producing high-resolution 3D 1 H metabolite maps and high-quality spatially resolved spectra (with a nominal resolution of ∼2.4 × 2.4 × 3 mm 3 in 5 minutes) were demonstrated using phantom and in vivo studies. By eliminating water suppression, we are also able to extract valuable information from the water signals for data processing (B 0 map, frequency drift, and coil sensitivity) as well as for mapping tissue susceptibility and relaxation parameters. Conclusions: The proposed method enables ultrafast 1 H-MRSI of the brain using a learned subspace, eliminating the need of acquiring subject-dependent navigator data (known as  1 ) in the original SPICE technique. It represents a new way to perform MRSI experiments and an important step toward practical applications of highresolution MRSI. K E Y W O R D SMR spectroscopic imaging, no water suppression, rapid spatiospectral encoding, subspace learning, union-of-subspaces model 378 |

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Fast high‐resolution brain metabolite mapping on a clinical 3T MRI by accelerated H‐FID‐MRSI and low‐rank constrained reconstruction

Cited by 26 publications

References 54 publications

High-Resolution Metabolic Mapping of the Cerebellum Using a Zoomed Magnetic Resonance Spectroscopic Imaging

High-Resolution Metabolic Mapping of the Cerebellum Using a Zoomed Magnetic Resonance Spectroscopic Imaging

Intra‐session and inter‐subject variability of 3D‐FID‐MRSI using single‐echo volumetric EPI navigators at 3T

Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces

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