Achieving high-resolution 1 H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla

Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contaminati...

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Veröffentlicht in:Journal of magnetic resonance (1997) 2021-10, Vol.331, p.107048
Hauptverfasser: Klauser, Antoine, Strasser, Bernhard, Thapa, Bijaya, Lazeyras, Francois, Andronesi, Ovidiu
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container_start_page 107048
container_title Journal of magnetic resonance (1997)
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creator Klauser, Antoine
Strasser, Bernhard
Thapa, Bijaya
Lazeyras, Francois
Andronesi, Ovidiu
description Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.
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subjects Brain - diagnostic imaging
Head
Healthy Volunteers
Humans
Magnetic Resonance Imaging
Phantoms, Imaging
title Achieving high-resolution 1 H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla
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