TY - JOUR
T1 - Temperature-corrected proton density fat fraction estimation using chemical shift-encoded MRI in phantoms
AU - the RSNA Quantitative Imaging Biomarker Alliance – Proton Density Fat Fraction Biomarker Committee
AU - Navaratna, Ruvini
AU - Zhao, Ruiyang
AU - Colgan, Timothy J.
AU - Hu, Houchun Harry
AU - Bydder, Mark
AU - Yokoo, Takeshi
AU - Bashir, Mustafa R.
AU - Middleton, Michael S.
AU - Serai, Suraj D.
AU - Malyarenko, Dariya
AU - Chenevert, Thomas
AU - Smith, Mark
AU - Henderson, Walter
AU - Hamilton, Gavin
AU - Shu, Yunhong
AU - Sirlin, Claude B.
AU - Tkach, Jean A.
AU - Trout, Andrew T.
AU - Brittain, Jean H.
AU - Hernando, Diego
AU - Reeder, Scott B.
N1 - Publisher Copyright:
© 2021 International Society for Magnetic Resonance in Medicine
PY - 2021/7
Y1 - 2021/7
N2 - Purpose: Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study. Theory and Methods: A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature. Results: Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction. Conclusion: Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.
AB - Purpose: Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study. Theory and Methods: A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature. Results: Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction. Conclusion: Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.
KW - chemical shift-encoded MRI
KW - fat quantification
KW - phantom
KW - proton density fat fraction
KW - quantitative imaging biomarker
KW - temperature correction
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U2 - 10.1002/mrm.28669
DO - 10.1002/mrm.28669
M3 - Article
C2 - 33565112
AN - SCOPUS:85103195831
SN - 0740-3194
VL - 86
SP - 69
EP - 81
JO - Magnetic Resonance in Medicine
JF - Magnetic Resonance in Medicine
IS - 1
ER -