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Abdominal Imaging

, Volume 40, Issue 8, pp 3084–3090 | Cite as

Feasibility of and agreement between MR imaging and spectroscopic estimation of hepatic proton density fat fraction in children with known or suspected nonalcoholic fatty liver disease

  • Emil Achmad
  • Takeshi Yokoo
  • Gavin Hamilton
  • Elhamy R. Heba
  • Jonathan C. Hooker
  • Christopher Changchien
  • Michael Schroeder
  • Tanya Wolfson
  • Anthony Gamst
  • Jeffrey B. Schwimmer
  • Joel E. Lavine
  • Claude B. Sirlin
  • Michael S. MiddletonEmail author
Article

Abstract

Purpose

To assess feasibility of and agreement between magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for estimating hepatic proton density fat fraction (PDFF) in children with known or suspected nonalcoholic fatty liver disease (NAFLD).

Materials and methods

Children were included in this study from two previous research studies in each of which three MRI and three MRS acquisitions were obtained. Sequence acceptability, and MRI- and MRS-estimated PDFF were evaluated. Agreement of MRI- with MRS-estimated hepatic PDFF was assessed by linear regression and Bland–Altman analysis. Age, sex, BMI-Z score, acquisition time, and artifact score effects on MRI- and MRS-estimated PDFF agreement were assessed by multiple linear regression.

Results

Eighty-six children (61 boys and 25 girls) were included in this study. Slope and intercept from regressing MRS-PDFF on MRI-PDFF were 0.969 and 1.591%, respectively, and the Bland–Altman bias and 95% limits of agreement were 1.17% ± 2.61%. MRI motion artifact score was higher in boys than girls (by 0.21, p = 0.021). Higher BMI-Z score was associated with lower agreement between MRS and MRI (p = 0.045).

Conclusion

Hepatic PDFF estimation by both MRI and MRS is feasible, and MRI- and MRS-estimated PDFF agree closely in children with known or suspected NAFLD.

Keywords

MRI MRS NAFLD Proton density fat fraction PDFF Steatosis 

Notes

Grant support

This work was supported by NCRR UL1 RR031980 for the Clinical and Translational Research Institute at UCSD, NIDDK R56 DK090350, NIDDK R01 DK075128, NCMHD P60 MD00220.

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Emil Achmad
    • 1
  • Takeshi Yokoo
    • 1
    • 2
  • Gavin Hamilton
    • 1
  • Elhamy R. Heba
    • 1
  • Jonathan C. Hooker
    • 1
  • Christopher Changchien
    • 1
  • Michael Schroeder
    • 1
  • Tanya Wolfson
    • 3
  • Anthony Gamst
    • 3
  • Jeffrey B. Schwimmer
    • 1
    • 4
    • 5
  • Joel E. Lavine
    • 6
  • Claude B. Sirlin
    • 1
  • Michael S. Middleton
    • 1
    • 7
    Email author
  1. 1.Liver Imaging Group, Department of Radiology, School of MedicineUniversity of California, San DiegoSan DiegoUSA
  2. 2.Department of Radiology and Advanced Imaging Research CenterUT Southwestern School of MedicineDallasUSA
  3. 3.Computational and Applied Statistics Laboratory (CASL), San Diego Supercomputing Center (SDSC)University of California, San DiegoSan DiegoUSA
  4. 4.Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, School of MedicineUniversity of California, San DiegoSan DiegoUSA
  5. 5.Department of GastroenterologyRady Children’s Hospital San DiegoSan DiegoUSA
  6. 6.Department of PediatricsColumbia UniversityNew YorkUSA
  7. 7.UCSD Department of RadiologyUCSD MRI InstituteSan DiegoUSA

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