Evidence map›Paper›PMID 28811994›Full record

ArticleQuantitative imaging in medicine and surgery2017

The measurement of liver fat from single-energy quantitative computed tomography scans.

Xiaoguang Cheng, Glen M Blake, J Keenan Brown, Zhe Guo, Jun Zhou, Fengzhe Wang, Liqiang Yang, Xiaohong Wang, Li Xu

Open access · hybridAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

8 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Review
  3. The Effect of COVID 19 on Liver Parenchyma Detected and measured by CT scan Hounsfield Units.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2022
    Article
  4. Article
  5. Article
  6. The study protocol for the China Health Big Data (China Biobank) project.Quantitative imaging in medicine and surgery · 2019
    Article
  7. How to best assess abdominal obesity.Current opinion in clinical nutrition and metabolic care · 2018
    Review
  8. 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

9 authors at 4 institutions in 2 countries.

Xiaoguang ChengDepartment of Radiology, Beijing Jishuitan Hospital, Beijing 100035, China.
Glen M BlakeBiomedical Engineering Department, King's College London, Strand, London WC2R 2LS, UK.
J Keenan BrownMindways Software Inc., Austin, TX, USA.
Zhe GuoDepartment of Radiology, Beijing Jishuitan Hospital, Beijing 100035, China.
Jun ZhouDepartment of Radiology, Shenyang No.4 Hospital, Shenyang 110082, China.
Fengzhe WangDepartment of Radiology, Shenyang No.4 Hospital, Shenyang 110082, China.
Liqiang YangDepartment of Radiology, the General Hospital of CNPC in Jilin City, Jilin 132021, China.
Xiaohong WangDepartment of Radiology, the General Hospital of CNPC in Jilin City, Jilin 132021, China.
Li XuDepartment of Radiology, Beijing Jishuitan Hospital, Beijing 100035, China.
Beijing Jishuitan Hospital · CNShenyang 242 Hospital · CNKing's College London · GBPeking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudies of soft tissue composition using computed tomography (CT) scans are often semi-quantitative and based on Hounsfield units (HU) measurements that have not been calibrated with a quantitative CT (QCT) phantom. We describe a study to establish the water (H

methodsLiver fat content was measured by comparing single-energy QCT (SEQCT) HU measurements of the liver with predicted HU values for fat and fat-free liver tissue calculated from their H

resultsThe equivalent densities of fat were 941.75 mg/cm

conclusionsWe have established H

Indexed as

Dual-energy quantitative computed tomography (DEQCT)liver fat measurementsingle-energy quantitative computed tomography (SEQCT)soft tissue composition

Identifiers

PMID28811994
PMCPMC5537127
OpenAlexW2621562246

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.