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Abstract PurposeTo improve liver proton density fat fraction (PDFF) and quantification at 0.55 T by systematically validating the acquisition parameter choices and investigating the performance of locally low‐rank denoising methods. MethodsA Monte Carlo simulation was conducted to design a protocol for PDFF and mapping at 0.55 T. Using this proposed protocol, we investigated the performance of robust locally low‐rank (RLLR) and random matrix theory (RMT) denoising. In a reference phantom, we assessed quantification accuracy (concordance correlation coefficient [] vs. reference values) and precision (using SD) across scan repetitions. We performed in vivo liver scans (11 subjects) and used regions of interest to compare means and SDs of PDFF and measurements. Kruskal–Wallis and Wilcoxon signed‐rank tests were performed (p < 0.05 considered significant). ResultsIn the phantom, RLLR and RMT denoising improved accuracy in PDFF and with >0.992 and improved precision with >67% decrease in SD across 50 scan repetitions versus conventional reconstruction (i.e., no denoising). For in vivo liver scans, the mean PDFF and mean were not significantly different between the three methods (conventional reconstruction; RLLR and RMT denoising). Without denoising, the SDs of PDFF and were 8.80% and 14.17 s−1. RLLR denoising significantly reduced the values to 1.79% and 5.31 s−1(p < 0.001); RMT denoising significantly reduced the values to 2.00% and 4.81 s−1(p < 0.001). ConclusionWe validated an acquisition protocol for improved PDFF and quantification at 0.55 T. Both RLLR and RMT denoising improved the accuracy and precision of PDFF and measurements.
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High‐resolution, 3D multi‐TE 1 H MRSI using fast spatiospectral encoding and subspace imaging
PurposeTo develop a novel method to achieve fast, high‐resolution, 3D multi‐TE1H‐MRSI of the brain. MethodsA 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. ResultsThe proposed acquisition can produce multi‐TE1H‐MRSI data with three TEs at a nominal spatial resolution of 3.4 × 3.4 × 5.3 mm3in 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. ConclusionHigh‐resolution, 3D multi‐TE1H‐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.
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- Award ID(s):
- 1944249
- PAR ID:
- 10419559
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Magnetic Resonance in Medicine
- Volume:
- 87
- Issue:
- 3
- ISSN:
- 0740-3194
- Page Range / eLocation ID:
- p. 1103-1118
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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