ECCENTRIC: a fast and unrestrained approach for high-resolution in vivo metabolic imaging at ultra-high field MR
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Abstract (arXiv)
A novel method for fast and high-resolution metabolic imaging, called ECcentric Circle ENcoding TRajectorIes for Compressed sensing (ECCENTRIC), has been developed and implemented at 7 Tesla MRI. ECCENTRIC is a non-Cartesian spatial-spectral encoding method optimized to accelerate magnetic resonance spectroscopic imaging (MRSI) with high signal-to-noise at ultra-high field. The approach provides flexible and random (k,t) sampling without temporal interleaving to improve spatial response function and spectral quality. ECCENTRIC needs low gradient amplitudes and slew-rates that reduces electrical, mechanical and thermal stress of the scanner hardware, and is robust to timing imperfection and eddy-current delays. Combined with a model-based low-rank reconstruction, this approach enables simultaneous imaging of up to 14 metabolites over the whole-brain at 2-3mm isotropic resolution in 4-10 minutes. In healthy volunteers ECCENTRIC demonstrated unprecedented spatial mapping of fine structural details of human brain neurochemistry. This innovative tool introduces a novel approach to neuroscience, providing new insights into the exploration of brain activity and physiology.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 23 May 2023.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imagingcited by 2
- 2024WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imagingcited by 2
- 2025Deep learning water-unsuppressed MRSI at ultra-high field for simultaneous quantitative metabolic, susceptibility and myelin water imagingcited by 0
- 2026HyperFitS -- Hypernetwork Fitting Spectra for metabolic quantification of 1H MR spectroscopic imagingcited by 0
- 2026HyperFitS -- Hypernetwork Fitting Spectra for metabolic quantification of 1H MR spectroscopic imaging3 Apr 2026
- 2025Deep learning water-unsuppressed MRSI at ultra-high field for simultaneous quantitative metabolic, susceptibility and myelin water imaging16 Dec 2025
- 2024WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imaging1 Oct 2024
- 2024Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging26 Sep 2024