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Magn Reson Med. 2017 Apr;77(4):1516-1524. doi: 10.1002/mrm.26228. Epub 2016 Apr 15.

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom.

Author information

1
Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
2
Department of Radiology, The Johns Hopkins University, Baltimore, Maryland, USA.
3
Department of Anesthesiology, Vanderbilt University, Nashville, Tennessee, USA.
4
Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee, USA.
5
Department of Radiology, University of California, San Diego, California, USA.
6
Siemens Healthcare, Baltimore, Maryland, USA.
7
Department of Radiology, Duke University, Durham, North Carolina, USA.
8
Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
9
Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.
10
Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
11
Center for Advanced Magnetic Resonance Development, Duke University, Durham, North Carolina, USA.
12
Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
13
Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.
14
Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA.
15
Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA.
16
Department of Emergency Medicine, University of Wisconsin, Madison, Wisconsin, USA.

Abstract

PURPOSE:

To evaluate the accuracy and reproducibility of quantitative chemical shift-encoded (CSE) MRI to quantify proton-density fat-fraction (PDFF) in a fat-water phantom across sites, vendors, field strengths, and protocols.

METHODS:

Six sites (Philips, Siemens, and GE Healthcare) participated in this study. A phantom containing multiple vials with various oil/water suspensions (PDFF:0%-100%) was built, shipped to each site, and scanned at 1.5T and 3T using two CSE protocols per field strength. Confounder-corrected PDFF maps were reconstructed using a common algorithm. To assess accuracy, PDFF bias and linear regression with the known PDFF were calculated. To assess reproducibility, measurements were compared across sites, vendors, field strengths, and protocols using analysis of covariance (ANCOVA), Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

RESULTS:

PDFF measurements revealed an overall absolute bias (across sites, field strengths, and protocols) of 0.22% (95% confidence interval, 0.07%-0.38%) and R2  > 0.995 relative to the known PDFF at each site, field strength, and protocol, with a slope between 0.96 and 1.02 and an intercept between -0.56% and 1.13%. ANCOVA did not reveal effects of field strength (P = 0.36) or protocol (P = 0.19). There was a significant effect of vendor (F = 25.13, P = 1.07 × 10-10 ) with a bias of -0.37% (Philips) and -1.22% (Siemens) relative to GE Healthcare. The overall ICC was 0.999.

CONCLUSION:

CSE-based fat quantification is accurate and reproducible across sites, vendors, field strengths, and protocols. Magn Reson Med 77:1516-1524, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

KEYWORDS:

chemical shift-encoded; fat quantification; multicenter; nonalcoholic fatty liver disease; phantom; proton-density fat-fraction (PDFF); quantitative imaging biomarker

PMID:
27080068
PMCID:
PMC4835219
DOI:
10.1002/mrm.26228
[Indexed for MEDLINE]
Free PMC Article

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