Validation of goose liver fat measurement by QCT and CSE-MRI with biochemical extraction and pathology as reference
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.
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2017 |
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| Erschienen: |
2017 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:28 |
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| Enthalten in: |
European radiology - 28(2017), 5 vom: 13. Dez., Seite 2003-2012 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Xu, Li [VerfasserIn] |
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| Links: |
Volltext [lizenzpflichtig] |
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| Themen: |
Chemical shift encoded magnetic resonance imaging |
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| Anmerkungen: |
© European Society of Radiology 2017 |
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| doi: |
10.1007/s00330-017-5189-x |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
OLC2092313088 |
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| 520 | |a 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 | ||
| 650 | 4 | |a Hepatic steatosis | |
| 650 | 4 | |a Quantitative computed tomography | |
| 650 | 4 | |a Chemical shift encoded magnetic resonance imaging | |
| 650 | 4 | |a Proton density fat fraction | |
| 650 | 4 | |a Hepatic triglyceride analysis | |
| 700 | 1 | |a Duanmu, Yangyang |4 aut | |
| 700 | 1 | |a Blake, Glen M. |4 aut | |
| 700 | 1 | |a Zhang, Chenxin |4 aut | |
| 700 | 1 | |a Zhang, Yong |4 aut | |
| 700 | 1 | |a Brown, Keenan |4 aut | |
| 700 | 1 | |a Wang, Xiaoqi |4 aut | |
| 700 | 1 | |a Wang, Peng |4 aut | |
| 700 | 1 | |a Zhou, Xingang |4 aut | |
| 700 | 1 | |a Zhang, Manling |4 aut | |
| 700 | 1 | |a Wang, Chao |4 aut | |
| 700 | 1 | |a Guo, Zhe |4 aut | |
| 700 | 1 | |a Guglielmi, Giuseppe |4 aut | |
| 700 | 1 | |a Cheng, Xiaoguang |4 aut | |
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