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

Diego Hernando, Samir D. Sharma, Mounes Aliyari Ghasabeh, Bret D. Alvis, Sandeep S. Arora, Gavin Hamilton, Li Pan, Jean M. Shaffer, Keitaro Sofue, Nikolaus M. Szeverenyi, E. Brian Welch, Qing Yuan, Mustafa R. Bashir, Ihab R. Kamel, Mark J. Rice, Claude B. Sirlin, Takeshi Yokoo, Scott B. Reeder

Research output: Contribution to journalArticle

35 Citations (Scopus)

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.

Original languageEnglish (US)
JournalMagnetic Resonance in Medicine
DOIs
StateAccepted/In press - 2016

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Protons
Fats
Water
Delivery of Health Care
Linear Models
Suspensions
Oils
Confidence Intervals

Keywords

  • Chemical shift-encoded
  • Fat quantification
  • Multicenter
  • Nonalcoholic fatty liver disease
  • Phantom
  • Proton-density fat-fraction (PDFF)
  • Quantitative imaging biomarker

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. / Hernando, Diego; Sharma, Samir D.; Aliyari Ghasabeh, Mounes; Alvis, Bret D.; Arora, Sandeep S.; Hamilton, Gavin; Pan, Li; Shaffer, Jean M.; Sofue, Keitaro; Szeverenyi, Nikolaus M.; Welch, E. Brian; Yuan, Qing; Bashir, Mustafa R.; Kamel, Ihab R.; Rice, Mark J.; Sirlin, Claude B.; Yokoo, Takeshi; Reeder, Scott B.

In: Magnetic Resonance in Medicine, 2016.

Research output: Contribution to journalArticle

Hernando, D, Sharma, SD, Aliyari Ghasabeh, M, Alvis, BD, Arora, SS, Hamilton, G, Pan, L, Shaffer, JM, Sofue, K, Szeverenyi, NM, Welch, EB, Yuan, Q, Bashir, MR, Kamel, IR, Rice, MJ, Sirlin, CB, Yokoo, T & Reeder, SB 2016, 'Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom', Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.26228
Hernando, Diego ; Sharma, Samir D. ; Aliyari Ghasabeh, Mounes ; Alvis, Bret D. ; Arora, Sandeep S. ; Hamilton, Gavin ; Pan, Li ; Shaffer, Jean M. ; Sofue, Keitaro ; Szeverenyi, Nikolaus M. ; Welch, E. Brian ; Yuan, Qing ; Bashir, Mustafa R. ; Kamel, Ihab R. ; Rice, Mark J. ; Sirlin, Claude B. ; Yokoo, Takeshi ; Reeder, Scott B. / Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. In: Magnetic Resonance in Medicine. 2016.
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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.",
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T1 - Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom

AU - Hernando, Diego

AU - Sharma, Samir D.

AU - Aliyari Ghasabeh, Mounes

AU - Alvis, Bret D.

AU - Arora, Sandeep S.

AU - Hamilton, Gavin

AU - Pan, Li

AU - Shaffer, Jean M.

AU - Sofue, Keitaro

AU - Szeverenyi, Nikolaus M.

AU - Welch, E. Brian

AU - Yuan, Qing

AU - Bashir, Mustafa R.

AU - Kamel, Ihab R.

AU - Rice, Mark J.

AU - Sirlin, Claude B.

AU - Yokoo, Takeshi

AU - Reeder, Scott B.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Chemical shift-encoded

KW - Fat quantification

KW - Multicenter

KW - Nonalcoholic fatty liver disease

KW - Phantom

KW - Proton-density fat-fraction (PDFF)

KW - Quantitative imaging biomarker

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