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PurposeBody composition MRI captures the distribution of fat and lean tissues throughout the body, and provides valuable biomarkers of obesity, metabolic disease, and muscle disorders, as well as risk assessment. Highly reproducible protocols have been developed for 1.5T and 3T MRI. The purpose of this work was to demonstrate the feasibility and test–retest repeatability of MRI body composition profiling on a 0.55T whole‐body system. MethodsHealthy adult volunteers were scanned on a whole‐body 0.55T MRI system using the integrated body RF coil. Experiments were performed to refine parameter settings such as TEs, resolution, flip angle, bandwidth, acceleration, and oversampling factors. The final protocol was evaluated using a test–retest study with subject removal and replacement in 10 adult volunteers (5 M/5F, age 25–60, body mass index 20–30). ResultsCompared to 1.5T and 3T, the optimal flip angle at 0.55T was higher (15°), due to the shorter T1 times, and the optimal echo spacing was larger, due to smaller chemical shift between water and fat. Overall image quality was comparable to conventional field strengths, with no significant issues with fat/water swapping or inadequate SNR. Repeatability coefficient of visceral fat, subcutaneous fat, total thigh muscle volume, muscle fat infiltration, and liver fat were 11.8 cL (2.2%), 46.9 cL (1.9%), 14.6 cL (0.5%), 0.1 pp (2%), and 0.2 pp (5%), respectively (coefficient of variation in parenthesis). ConclusionsWe demonstrate that 0.55T body composition MRI is feasible and present optimized scan parameters. The resulting images provide satisfactory quality for automated post‐processing and produce repeatable results. 

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. 

PurposeThe goal of this study was to determine the accuracy of displacement‐encoding with stimulated echoes (DENSE) MRI in a tissue motion phantom with displacements representative of those observed in human brain tissue. MethodsThe phantom was comprised of a plastic shaft rotated at a constant speed. The rotational motion was converted to a vertical displacement through a camshaft. The phantom generated repeatable cyclical displacement waveforms with a peak displacement ranging from 92 µm to 1.04 mm at 1‐Hz frequency. The surface displacement of the tissue was obtained using a laser Doppler vibrometer (LDV) before and after the DENSE MRI scans to check for repeatability. The accuracy of DENSE MRI displacement was assessed by comparing the laser Doppler vibrometer and DENSE MRI waveforms. ResultsLaser Doppler vibrometer measurements of the tissue motion demonstrated excellent cycle‐to‐cycle repeatability with a maximum root mean square error of 9 µm between the ensemble‐averaged displacement waveform and the individual waveforms over 180 cycles. The maximum difference between DENSE MRI and the laser Doppler vibrometer waveforms ranged from 15 to 50 µm. Additionally, the peak‐to‐peak difference between the 2 waveforms ranged from 1 to 18 µm. ConclusionUsing a tissue phantom undergoing cyclical motion, we demonstrated the percent accuracy of DENSE MRI to measure displacement similar to that observed for in vivo cardiac‐induced brain tissue.