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High-resolution, 3D Multi-TE H MRSI Using Fast Spatiospectral Encoding and Subspace Imaging

Overview
Journal Magn Reson Med
Publisher Wiley
Specialty Radiology
Date 2021 Nov 9
PMID 34752641
Citations 3
Authors
Affiliations
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Abstract

Purpose: To develop a novel method to achieve fast, high-resolution, 3D multi-TE H-MRSI of the brain.

Methods: A new multi-TE MRSI acquisition strategy was developed that integrates slab selective excitation with adiabatic refocusing for better volume coverage, rapid spatiospectral encoding, sparse multi-TE sampling, and interleaved water navigators for field mapping and calibration. Special data processing strategies were developed to interpolate the sparsely sampled data, remove nuisance signals, and reconstruct multi-TE spatiospectral distributions with high SNR. Phantom and in vivo experiments have been carried out to demonstrate the capability of the proposed method.

Results: The proposed acquisition can produce multi-TE H-MRSI data with three TEs at a nominal spatial resolution of 3.4 × 3.4 × 5.3 mm in around 20 min. High-SNR brain metabolite spatiospectral reconstructions can be obtained from both a metabolite phantom and in vivo experiments by the proposed method.

Conclusion: High-resolution, 3D multi-TE H-MRSI of the brain can be achieved within clinically feasible time. This capability, with further optimizations, could be translated to clinical applications and neuroscience studies where simultaneously mapping metabolites and neurotransmitters and TE-dependent molecular spectral changes are of interest.

Citing Articles

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High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models.

Zhao R, Peng X, Kelkar V, Anastasio M, Lam F IEEE Trans Biomed Eng. 2024; 71(6):1969-1979.

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Multi-Parametric Molecular Imaging of the Brain Using Optimized Multi-TE Subspace MRSI.

Wang Z, Li Y, Cao C, Anderson A, Huesmann G, Lam F IEEE Trans Biomed Eng. 2024; 71(6):1732-1744.

PMID: 38170654 PMC: 11160977. DOI: 10.1109/TBME.2023.3349375.


SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints.

Li Y, Wang Z, Lam F IEEE Trans Biomed Eng. 2022; 69(10):3087-3097.

PMID: 35320082 PMC: 9514378. DOI: 10.1109/TBME.2022.3161417.

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