Improved liver fat and R2 quantification at 0.55 T using locally low‐rank denoising

PurposeTo improve liver proton density fat fraction (PDFF) and R2*$$ {R}_2^{\ast } $$ 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 desig...

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Bibliographic Details
Published in:	Magnetic resonance in medicine Vol. 93; no. 3; pp. 1348 - 1364
Main Authors:	Shu‐Fu Shih, Tasdelen, Bilal, Yagiz, Ecrin, Zhang, Zhaohuan, Zhong, Xiaodong, Cui, Sophia X, Nayak, Krishna S, Wu, Holden H
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc 01.03.2025 John Wiley and Sons Inc
Subjects:	Accuracy Computer Processing and Modeling Correlation coefficients In vivo methods and tests Liver Matrix theory Monte Carlo simulation Noise reduction Proton density (concentration) Rank tests Reconstruction
ISSN:	0740-3194, 1522-2594
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Summary:	PurposeTo improve liver proton density fat fraction (PDFF) and R2$$ {R}_2^{\ast } $$ 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 R2$$ {R}_2^{\ast } $$ 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 [ρc$$ {\rho}_c $$] 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 R2$$ {R}_2^{\ast } $$ 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 R2$$ {R}_2^{\ast } $$ with ρc$$ {\rho}_c $$ >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 R2$$ {R}_2^{\ast } $$ were not significantly different between the three methods (conventional reconstruction; RLLR and RMT denoising). Without denoising, the SDs of PDFF and R2$$ {R}_2^{\ast } $$ 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 R2$$ {R}_2^{\ast } $$ quantification at 0.55 T. Both RLLR and RMT denoising improved the accuracy and precision of PDFF and R2$$ {R}_2^{\ast } $$ measurements.
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ISSN:	0740-3194 1522-2594
DOI:	10.1002/mrm.30324