Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom
- 15 April 2016
- journal article
- research article
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 77 (4) , 1516-1524
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 MedicineKeywords
Funding Information
- National Institutes of Health (UL1TR00427, R01 DK083380, R01 DK088925, R01 DK100651, K24 DK102595)
- University of Wisconsin D2P Igniter program
- General Electric
- Philips (to University of Texas Southwestern Medical Center and Vanderbilt University)
- Siemens Healthcare (to Duke University and The Johns Hopkins University)
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