Evidence map›Paper›PMID 32642877›Full record

ArticleThe international journal of cardiovascular imaging2020

Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV).

Mingming Ma, Yuhui Li, Ran Chen, Chao Huang, Yankai Mao, Bowen Zhao

Abstract read
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In one paragraph

Article in The international journal of cardiovascular imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Role of Artificial Intelligence in Congenital Heart Disease and Interventions.Journal of the Society for Cardiovascular Angiography & Interventions · 2025
    Review
  3. Artificial intelligence in fetal echocardiography: Recent advances and future prospects.International journal of cardiology. Heart & vasculature · 2024
    Review
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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

6 authors.

Mingming MaDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China.
Yuhui LiDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China.
Ran ChenDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China.
Chao HuangDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China.
Yankai MaoDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China.
Bowen ZhaoDepartment of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University College of Medicine, Hangzhou, People's Republic of China. zbwcjp@zju.edu.cn.ORCID http://orcid.org/0000-0002-4975-7069

Funding

Zhejiang Province Public Welfare Technology Application Research Project LGF18H180015
6 · The paper itself

Abstract

The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (RVOT) view, and 3-vessels and trachea (3VT) view in fetuses with double-outlet right ventricle (DORV). In this prospective study, thirty fetuses diagnosed with DORV by fetal echocardiography in the second and third trimesters were enrolled. One or more STIC volume data-sets were collected from the 4-chamber view as initial view for each fetus, one optimal volume per fetus was selected for on-line analysis using FINE, and the diagnosis plane image was optimized using the Virtual Intelligent Sonographer Assistance (VIS-assistance).The visualization rates of 3 specific abnormal fetal echocardiography views of DORV and key diagnostic elements were calculated. One or more STIC volumes (n = 30 total) were obtained in 25 patients. A single STIC volume per patient was analyzed using the FINE method. FINE was able to successfully generate and display 3 specific abnormal fetal echocardiography views. The display rates of the 3 specific abnormal fetal echocardiography views (3VT, LVOT, RVOT) were 84.0%, 76.0% and 84.0%, respectively. By applying intelligent navigation technology to STIC volume data-sets, the FINE method can successfully generate three specific abnormal cardiac fetal echocardiography diagnostic views in fetuses with DORV, the FINE method can be used for screening and remote consultation of fetal DORV.

Indexed as

Artificial IntelligenceDiagnosis, Computer-AssistedEchocardiography, Four-DimensionalUltrasonography, PrenatalAdultAnatomic LandmarksDouble Outlet Right VentricleFemaleFetal HeartGestational AgeHumansImage Interpretation, Computer-AssistedPredictive Value of TestsPregnancyReproducibility of ResultsSpatio-Temporal AnalysisCongenital heart defectDouble-outlet right ventricle(DORV)Fetal echocardiographyFetal intelligent navigation echocardiography(FINE)Spatiotemporal image correlation(STIC)

Identifiers

PMID32642877

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Registered trials

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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.