Evidence map›Paper›PMID 36513994›Full record

ArticleBMC cardiovascular disorders2022

Comparison of epicardial adipose tissue volume quantification between ECG-gated cardiac and non-ECG-gated chest computed tomography scans.

Yuancheng Xu, Stanislau Hrybouski, D Ian Paterson, Zhiyang Li, Yulong Lan, Lin Luo, Xinping Shen, Lingyu Xu

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Abnormal "Frontiers in cardiovascular medicine · 2026
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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

8 authors at 5 institutions in 3 countries.

Yuancheng XuDepartment of Urology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China.
Stanislau HrybouskiNeuroscience and Mental Health Institute, University of Alberta, Edmonton, Alberta, Canada.
D Ian PatersonDepartment of Cardiology, Mackenzie Health Science Centre, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
Zhiyang LiDepartment of General Surgery, the Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Yulong LanDepartment of Cardiology, the Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Lin LuoDepartment of Radiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China.
Xinping ShenDepartment of Radiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China.
Lingyu XuDepartment of Cardiology, Mackenzie Health Science Centre, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada. lingyu1@ualberta.ca.
University of Alberta · CAUniversity of Hong Kong · HKSecond Affiliated Hospital of Shantou University Medical College · CNShantou University · CNUniversity of Hong Kong - Shenzhen Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study investigated accuracy and consistency of epicardial adipose tissue (EAT) quantification in non-ECG-gated chest computed tomography (CT) scans.

methodsEAT volume was semi-automatically quantified using a standard Hounsfield unit threshold (- 190, - 30) in three independent cohorts: (1) Cohort 1 (N = 49): paired 120 kVp ECG-gated cardiac non-contrast CT (NCCT) and 120 kVp non-ECG-gated chest NCCT; (2) Cohort 2 (N = 34): paired 120 kVp cardiac NCCT and 100 kVp non-ECG-gated chest NCCT; (3) Cohort 3 (N = 32): paired non-ECG-gated chest NCCT and chest contrast-enhanced CT (CECT) datasets (including arterial phase and venous phase). Images were reconstructed with the slice thicknesses of 1.25 mm and 5 mm in the chest CT datasets, and 3 mm in the cardiac NCCT datasets.

resultsIn Cohort 1, the chest NCCT-1.25 mm EAT volume was similar to the cardiac NCCT EAT volume, while chest NCCT-5 mm underestimated the EAT volume by 7.5%. In Cohort 2, 100 kVp chest NCCT-1.25 mm were 13.2% larger than 120 kVp cardiac NCCT EAT volumes. In Cohort 3, the chest arterial CECT and venous CECT dataset underestimated EAT volumes by ~ 28% and ~ 18%, relative to chest NCCT datasets. All chest CT-derived EAT volumes were similarly associated with significant coronary atherosclerosis with cardiac CT counterparts.

conclusionThe 120 kVp non-ECG-gated chest NCCT-1.25 mm images produced EAT volumes comparable to cardiac NCCT. Chest CT EAT volumes derived from consistent imaging settings are excellent alternatives to the cardiac NCCT to investigate their association with coronary artery disease.

Indexed as

Coronary Artery DiseasePericardiumAdipose TissueCoronary AngiographyHumansRadionuclide ImagingTomography, X-Ray ComputedChest Computed tomographyContrast enhancementEpicardial adipose tissueSlice thicknessTube voltage

Identifiers

PMID36513994
PMCPMC9746017
OpenAlexW4311826054

What OpenQuestion holds

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LicenceCC BY
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.