Evidence map›Paper›PMID 29238866›Full record

ArticleEuropean radiology2018

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

Li Xu, Yangyang Duanmu, Glen M Blake, Chenxin Zhang, Yong Zhang, Keenan Brown, Xiaoqi Wang, Peng Wang, Xingang Zhou, Manling Zhang and 4 more

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  8. Article
  9. Review
  10. Article
  11. [Quantitative analysis of non-alcoholic fatty liver disease based on MRI proton density fat fraction in the coastal region of Qingdao].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Topics on quantitative liver magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2019
    Review
  17. Review
  18. How to best assess abdominal obesity.Current opinion in clinical nutrition and metabolic care · 2018
    Review
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Li XuDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China.
Yangyang DuanmuDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China.
Glen M BlakeBiomedical Engineering Department, King's College London, London, UK.
Chenxin ZhangDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China.
Yong ZhangDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China.
Keenan BrownMindways Software, Austin, TX, USA.
Xiaoqi WangPhilips Healthcare, Beijing, China.
Peng WangPathology Department, Capital Medical University Affiliated Beijing Ditan Hospital, Beijing, China.
Xingang ZhouPathology Department, Capital Medical University Affiliated Beijing Ditan Hospital, Beijing, China.
Manling ZhangChina National Food & Safety Supervision and Inspection Centre, Beijing, China.
Chao WangStatistics Department, Beijing Jishuitan Hospital, Beijing, China.
Zhe GuoDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China.
Giuseppe GuglielmiDepartment of Radiology, Scientific Institute Hospital, San Giovanni Rotondo, Italy.
Xiaoguang ChengDepartment of Radiology, Beijing Jishuitan Hospital, 31 Xinjiekou East Street, Beijing, 100035, China. xiao65@263.net.

Funding

National Natural Science Fundation of China 81401407
6 · The paper itself

Abstract

objectivesThis 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.

methodsTwenty-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".

resultsBoth 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).

conclusionsQCT 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.

Indexed as

AnimalsDisease Models, AnimalFatty LiverFemaleGeeseHumansLiverMagnetic Resonance ImagingMaleReproducibility of ResultsTomography, X-Ray ComputedChemical shift encoded magnetic resonance imagingHepatic steatosisHepatic triglyceride analysisProton density fat fractionQuantitative computed tomography

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.