Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI

Nathan T Roberts; Diego Hernando; James H Holmes; Curtis N Wiens; Scott B Reeder

doi:10.1002/mrm.27065

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$Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI$

Journal article

Peer reviewed

Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI

Nathan T Roberts, Diego Hernando, James H Holmes, Curtis N Wiens and Scott B Reeder

Magnetic resonance in medicine, Vol.80(2), pp.685-695

08/2018

DOI: 10.1002/mrm.27065

PMCID: PMC5910302

PMID: 29322549

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https://www.ncbi.nlm.nih.gov/pmc/articles/5910302View

Open Access

Abstract

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. 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. 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. 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. 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.

Adipose Tissue - diagnostic imaging

Algorithms

Computer Simulation

Fatty Liver - diagnostic imaging

Humans

Image Processing, Computer-Assisted - methods

Liver - diagnostic imaging

Magnetic Resonance Imaging - methods

Phantoms, Imaging

Protons

Signal-To-Noise Ratio

Details

Title: Subtitle: Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI
Creators: Nathan T Roberts - University of Wisconsin–Madison
Diego Hernando - University of Wisconsin–Madison
James H Holmes - University of Wisconsin–Madison
Curtis N Wiens - University of Wisconsin–Madison
Scott B Reeder - University of Wisconsin–Madison
Resource Type: Journal article
Publication Details: Magnetic resonance in medicine, Vol.80(2), pp.685-695
DOI: 10.1002/mrm.27065
PMID: 29322549
PMCID: PMC5910302
NLM abbreviation: Magn Reson Med
ISSN: 0740-3194
eISSN: 1522-2594
Grant note: UL1 TR000427 / NCATS NIH HHS K24 DK102595 / NIDDK NIH HHS R01 DK083380 / NIDDK NIH HHS R01 DK100651 / NIDDK NIH HHS R01 DK088925 / NIDDK NIH HHS UL1 TR002373 / NCATS NIH HHS
Language: English
Date published: 08/2018
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology
Record Identifier: 9984294922702771

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