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

Antoine Klauser, Bernhard Strasser, Bijaya Thapa, François Lazeyras, Ovidiu C. Andronesi

2021Journal of Magnetic Resonance28 citationsDOIOpen Access PDF

Abstract

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 1H 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.

Topics & Concepts

Compressed sensingMagnetic resonance spectroscopic imagingNuclear magnetic resonanceImaging phantomIterative reconstructionSIGNAL (programming language)Computer scienceMagnetic resonance imagingMaterials sciencePhysicsArtificial intelligenceOpticsMedicineRadiologyProgramming languageAdvanced MRI Techniques and ApplicationsMedical Imaging Techniques and ApplicationsAtomic and Subatomic Physics Research
Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla | Litcius