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Abstract PurposeTo compare T1 and T2 measurements across commercial and prototype 0.55T MRI systems in both phantom and healthy participants using the same vendor‐neutral pulse sequences, reconstruction, and analysis methods. MethodsStandard spin echo measurements and abbreviated protocol measurements of T1, B1, and T2 were made on two prototype 0.55 T systems and two commercial 0.55T systems using an ISMRM/NIST system phantom. Additionally, five healthy participants were imaged at each system using the abbreviated protocol for T1, B1, and T2 measurement. The phantom measurements were compared to NMR‐based reference measurements to determine accuracy, and both phantom and in vivo measurements were compared to assess reproducibility and differences between the prototype and commercial systems. ResultsVendor‐neutral sequences were implemented across all four systems, and the code for pulse sequences and reconstruction is freely available. For participants, there was no difference in the mean T1 and T2 relaxation times between the prototype and commercial systems. In the phantom, there were no significant differences between the prototype and commercial systems for T1 and T2 measurements using the abbreviated protocol. ConclusionQuantitative T1 and T2 measurements at 0.55T in phantom and healthy participants are not statistically different across the prototype and commercial systems. 

Abstract PurposeBreath‐held fat‐suppressed volumetric T1‐weighted MRI is an important and widely‐used technique for evaluating the abdomen. Both fat‐saturation and Dixon‐based fat‐suppression methods are used at conventional field strengths; however, both have challenges at lower field strengths (<1.5T) due to insufficient fat suppression and/or inadequate resolution. Specifically, at lower field strengths, fat saturation often fails due to the short T1 of lipid; and Cartesian Dixon imaging provides poor spatial resolution due to the need for a long ∆TE, due to the smaller ∆f between water and lipid. The purpose of this work is to demonstrate a new approach capable of simultaneously achieving excellent fat suppression and high spatial resolution on a 0.55T whole‐body system. MethodsWe applied 3D stack‐of‐spirals Dixon imaging at 0.55T, with compensation of concomitant field phase during reconstruction. The spiral readouts make efficient use of the requisite ∆TE. We compared this with 3D Cartesian Dixon imaging. Experiments were performed in 2 healthy and 10 elevated liver fat volunteers. ResultsStack‐of‐spirals Dixon imaging at 0.55T makes excellent use of the required ∆TE, provided high SNR efficiency and finer spatial resolution (1.7 × 1.7 × 5 mm³) compared Cartesian Dixon (3.5 × 3.5 × 5 mm³), within a 17‐s breath‐hold. We observed successful fat suppression, and improved definition of structures such as the liver, kidneys, and bowel. ConclusionWe demonstrate that high‐resolution single breath‐hold volumetric abdominal T1‐weighted imaging is feasible at 0.55T using spiral sampling and concomitant field correction. This is an attractive alternative to existing Cartesian‐based methods, as it simultaneously provides high‐resolution and excellent fat‐suppression. 

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.