Noise properties of proton density fat fraction estimated using chemical shift–encoded MRI
Year: 2018
Type: article
Abstract: PURPOSE: The purpose of this work is to characterize the noise distribution of proton density fat fraction (PDFF) measured using chemical shift-encoded MRI, and to provide alternative strategies to reduce bias in PDFF estimation. THEORY: We derived the probability density function for PDFF estimated using chemical shift-encoded MRI, and found it to exhibit an asymmetric noise distribution that contributes to signal-to-noise-ratio dependent bias. METHODS: To study PDFF noise bias, we performed (at 1.5 T) numerical simulations, phantom acquisitions, and a retrospective in vivo experiment. In each experiment, we compared the performance of three statistics (mean, median, and maximum likelihood estimator) in estimating the PDFF in a region of interest. RESULTS: We demonstrated the presence of the asymmetric noise distribution in simulations, phantoms, and in vivo. In each experiment we demonstrated that both the median and proposed maximum likelihood estimator statistics outperformed the mean statistic in mitigating noise-related bias for low signal-to-noise-ratio acquisitions. CONCLUSIONS: Characterization of the noise distribution of PDFF estimated using chemical shift-encoded MRI enabled new strategies based on median and maximum likelihood estimator statistics to mitigate noise-related bias for accurate PDFF measurement from a region of interest. Such strategies are important for quantitative chemical shift-encoded MRI applications that typically operate in low signal-to-noise-ratio regimes. Magn Reson Med 80:685-695, 2018. © 2018 International Society for Magnetic Resonance in Medicine.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.27065
Institution: University of Wisconsin–Madison
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: Technical Validation of MR Biomarkers of Obesity-Associated NAFLD, Confounder-Corrected Quantitative MRI Biomarkers of Hepatic, Institutional Clinical and Translational Science Award, Evolution of Quantitative MRI Biomarkers of Metabolic Syndrome During Puberty, Technical Development of Quantitative Biomarkers of Fatty Liver Disease with MRI, University of Wisconsin Institute for Clinical and Translational Research
OpenAlex ID: W2783483733