Evidence map›Paper›PMID 34435205›Full record

Trial reportEuropean radiology2022

Prediction of acute coronary syndrome within 3 years using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography.

Jin Shang, Shaowei Ma, Yan Guo, Linlin Yang, Qian Zhang, Fuchun Xie, Yue Ma, Quanmei Ma, Yuxue Dang, Ke Zhou and 3 more

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 2% 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

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

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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

13 authors at 3 institutions in 1 country.

Jin ShangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Shaowei MaDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Yan GuoGE Healthcare, Shanghai, China.
Linlin YangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Qian ZhangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Fuchun XieDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Yue MaDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Quanmei MaDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Yuxue DangDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Ke ZhouDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
Ting LiuDepartment of Radiology, First Affiliated Hospital of China Medical University, Shenyang, 110001, China.
Jinzhu YangKey Laboratory of Intelligent Computing in Medical Image (MIIC), Ministry of Education, Northeastern University, Shenyang, 110169, Liaoning, China.
Yang HouDepartment of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, China. houyang1973@163.com.
China Medical University · CNNortheastern University · CNUnited Imaging Healthcare (China) · CN

Funding

National Natural Science Foundation of China 81871435National Natural Science Foundation of China 81901741National Natural Science Foundation of China 82071920The key Research & Development Plan of Liaoning Province 2020JH2/10300037
6 · The paper itself

Abstract

objectivesTo evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years.

methodsWe designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application.

resultsRadiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital.

conclusionCCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years. KEY POINTS: • Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.

Indexed as

Acute Coronary SyndromeCoronary Artery DiseasePlaque, AtheroscleroticAdipose TissueCase-Control StudiesComputed Tomography AngiographyCoronary AngiographyHumansRetrospective StudiesTomography, X-Ray ComputedAcute coronary syndromeAdipose tissueComputed tomography angiographyInflammationRadiomics

Identifiers

PMID34435205
PMCPMC8794963
OpenAlexW3193463036

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.