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Validation of goose liver fat measurement by QCT and CSE-MRI with biochemical extraction and pathology as reference

European Radiology volume 28, pages 2003–2012 (2018)Cite this article

Abstract

Objectives

This study aimed to validate the accuracy and reliability of quantitative computed tomography (QCT) and chemical shift encoded magnetic resonance imaging (CSE-MRI) to assess hepatic steatosis.

Methods

Twenty-two geese with a wide range of hepatic steatosis were collected. After QCT and CSE-MRI examinations, the liver of each goose was removed and samples were taken from the left lobe, upper and lower half of the right lobe for biochemical measurement and histology. Fat percentages by QCT and proton density fat fraction by MRI (MRI-PDFF) were measured within the sample regions of biochemical measurement and histology. The accuracy of QCT and MR measurements were assessed through Spearman correlation coefficients (r) and Passing and Bablok regression equations using biochemical measurement as the "gold standard".

Results

Both QCT and MRI correlated highly with chemical extraction [r = 0.922 (p < 0.001) and r = 0.949 (p < 0.001) respectively]. Chemically extracted triglyceride was accurately predicted by both QCT liver fat percentages (Y = 0.6 + 0.866 × X) and by MRI-PDFF (Y = -1.8 + 0.773 × X).

Conclusions

QCT and CSE-MRI measurements of goose liver fat were accurate and reliable compared with biochemical measurement.

Key Points

• QCT and CSE-MRI can measure liver fat content accurately and reliably

• Histological grading of hepatic steatosis has larger sampling variability

• QCT and CSE-MRI have potential in the clinical setting

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Abbreviations

NAFLD:

Non-Alcoholic Fatty Liver Disease

QCT:

Quantitative Computed Tomography

BMD:

Bone Mineral Density

pQCT:

peripheral Quantitative Computed Tomography

PDFF:

Proton Density Fat Fraction

CSE-MRI:

Chemical Shift Encoded Magnetic Resonance Imaging

mDixon:

modified Dixon

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Acknowledgements

We thank our study participants for contributing with their time and efforts. We wish to thank Mindways Software and Philips Healthcare for their technical support. We also thank Chao Wang for his professional suggestions on statistics. The authors acknowledge the support of National Natural Science Foundation of China (81401407).

Funding

This study has received funding by National Natural Science Foundation of China (81401407).

Author information

Affiliations

  1. Department of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China

    Li Xu, Yangyang Duanmu, Chenxin Zhang, Yong Zhang, Zhe Guo & Xiaoguang Cheng

  2. Biomedical Engineering Department, King’s College London, London, UK

    Glen M. Blake

  3. Mindways Software, Austin, TX, USA

    Keenan Brown

  4. Philips Healthcare, Beijing, China

    Xiaoqi Wang

  5. Pathology Department, Capital Medical University Affiliated Beijing Ditan Hospital, Beijing, China

    Peng Wang & Xingang Zhou

  6. China National Food & Safety Supervision and Inspection Centre, Beijing, China

    Manling Zhang

  7. Statistics Department, Beijing Jishuitan Hospital, Beijing, China

    Chao Wang

  8. Department of Radiology, Scientific Institute Hospital, San Giovanni Rotondo, Italy

    Giuseppe Guglielmi

Authors
  1. Li Xu
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  2. Yangyang Duanmu
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  3. Glen M. Blake
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  4. Chenxin Zhang
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  8. Peng Wang
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  10. Manling Zhang
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  11. Chao Wang
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  13. Giuseppe Guglielmi
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  14. Xiaoguang Cheng
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Corresponding author

Correspondence to Xiaoguang Cheng.

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Guarantor

The scientific guarantor of this publication is Li Xu.

Conflict of interest

The authors of this manuscript declare relationships with the following companies. Keenan Brown is the employee and stock owner of Mindways Software. There was no involvement by this company in the design, execution, analysis, or publication of this manuscript. Xiaoqi Wang is employed by Philips Healthcare. There was no involvement by this company in the design, execution, analysis, or publication of this manuscript. All the other authors declare no potential conflict of interest.

Statistics and biometry

Chao Wang kindly provided statistical advice for this manuscript.

One of the authors has significant statistical expertise.

Ethical approval

Institutional Review Board approval was obtained.

Approval from the institutional animal care committee of Beijing Jishuitan Hospital was obtained.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

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Xu, L., Duanmu, Y., Blake, G.M. et al. Validation of goose liver fat measurement by QCT and CSE-MRI with biochemical extraction and pathology as reference. Eur Radiol 28, 2003–2012 (2018). https://doi.org/10.1007/s00330-017-5189-x

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  • DOI: https://doi.org/10.1007/s00330-017-5189-x

Keywords

  • Hepatic steatosis
  • Quantitative computed tomography
  • Chemical shift encoded magnetic resonance imaging
  • Proton density fat fraction
  • Hepatic triglyceride analysis