Klauser, AntoineCourvoisier, SebastienKasten, JeffreyKocher, MichelGuerquin-Kern, MatthieuVan De Ville, DimitriLazeyras, Francois2019-06-182019-06-182019-06-182019-05-0110.1002/mrm.27623https://infoscience.epfl.ch/handle/20.500.14299/157748WOS:000462688900003Purpose: Epitomizing the advantages of ultra short echo time and no chemical shift displacement error, high-resolution-free induction decay magnetic resonance spectroscopic imaging (FID-MRSI) sequences have proven to be highly effective in providing unbiased characterizations of metabolite distributions. However, its merits are often overshadowed in high-resolution settings by reduced signal-to-noise ratios resulting from the smaller voxel volumes procured by extensive phase encoding and the related acquisition times.Methods: To address these limitations, we here propose an acquisition and reconstruction scheme that offers both implicit dataset denoising and acquisition acceleration. Specifically, a slice selective high-resolution FID-MRSI sequence was implemented. Spectroscopic datasets were processed to remove fat contamination, and then reconstructed using a total generalized variation (TGV) regularized low-rank model. We further measured reconstruction performance for random under-sampled data to assess feasibility of a compressed-sensing SENSE acceleration scheme. Performance of the lipid suppression was assessed using an ad hoc phantom, while that of the low-rank TGV reconstruction model was benchmarked using simulated MRSI data. To assess real-world performance, 2D FID-MRSI acquisitions of the brain in healthy volunteers were reconstructed using the proposed framework.Results: Results from the phantom and simulated data demonstrate that skull lipid contamination is effectively removed and that data reconstruction quality is improved with the low-rank TGV model. Also, we demonstrated that the presented acquisition and reconstruction methods are compatible with a compressed-sensing SENSE acceleration scheme.Conclusions: An original reconstruction pipeline for 2D H-1-FID-MRSI datasets was presented that places high-resolution metabolite mapping on 3T MR scanners within clinically feasible limits.Radiology, Nuclear Medicine & Medical ImagingRadiology, Nuclear Medicine & Medical Imagingaccelerationbrain metabolitecompressed-sensingmagnetic resonance spectroscopic imagingsensemagnetic-resonancelipid suppressionimage-reconstruction1h mrsi7 tacquisitionh-1-mrsispectroscopywaterechotext::journal::journal article::research article