Evidence map›Paper›PMID 29720173›Full record

ArticleBiomedical engineering online2018

Clinical validation and assessment of aortic hemodynamics using computational fluid dynamics simulations from computed tomography angiography.

Yulei Zhu, Rui Chen, Yu-Hsiang Juan, He Li, Jingjing Wang, Zhuliang Yu, Hui Liu

Abstract read
In one paragraph

Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Applications of Computational Fluid Dynamics in Congenital Heart Disease: A Review.Journal of cardiovascular development and disease · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Hemodynamic Abnormalities in the Aorta of Turner Syndrome Girls.Frontiers in cardiovascular medicine · 2021
    Article
  15. Non-invasive Prediction of Peak Systolic Pressure Drop across Coarctation of Aorta using Computational Fluid Dynamics.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    Article
  16. Article
  17. Article
  18. 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

7 authors.

Yulei ZhuDepartment of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, No. 106, Zhong Shan Er Lu, Guangzhou, 510080, Guangdong, China.
Rui ChenDepartment of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, No. 106, Zhong Shan Er Lu, Guangzhou, 510080, Guangdong, China.
Yu-Hsiang JuanDepartment of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou Chang Gung University, Taoyuan, Taiwan.
He LiDepartment of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong General Hospital, Guangdong Academy of Medical Sciences, No. 106, Zhong Shan Er Lu, Guangzhou, 510080, Guangdong, China.
Jingjing WangDepartment of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, No. 106, Zhong Shan Er Lu, Guangzhou, 510080, Guangdong, China.
Zhuliang YuSchool of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China. zlyu@scut.edu.cn.
Hui LiuDepartment of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, No. 106, Zhong Shan Er Lu, Guangzhou, 510080, Guangdong, China. liuhuijiujiu@gmail.com.

Funding

National Natural Science Foundation of China 81771799
6 · The paper itself

Abstract

backgroundHemodynamic information including peak systolic pressure (PSP) and peak systolic velocity (PSV) carry an important role in evaluation and diagnosis of congenital heart disease (CHD). Since MDCTA cannot evaluate hemodynamic information directly, the aim of this study is to provide a noninvasive method based on a computational fluid dynamics (CFD) model, derived from multi-detector computed tomography angiography (MDCTA) raw data, to analyze the aortic hemodynamics in infants with CHD, and validate these results against echocardiography and cardiac catheter measurements.

methodsThis study included 25 patients (17 males, and 8 females; a median age of 2 years, range: 4 months-4 years) with CHD. All patients underwent both transthoracic echocardiography (TTE) and MDCTA within 2 weeks prior to cardiac catheterization. CFD models were created from MDCTA raw data. Boundary conditions were confirmed by lumped parameter model and transthoracic echocardiography (TTE). Peak systolic velocity derived from CFD models (PSV

resultsPSV

conclusionsOur result demonstrated that CFD scheme based on MDCTA raw data is an accurate and convenient method in obtaining the velocity and pressure from aorta and displaying the distribution of PSWSS and flow pattern of aorta. The preliminary results from our study demonstrate the capability in combining clinical imaging data and novel CFD tools in infants with CHD and provide a noninvasive approach for diagnose of CHD such as coarctation of aorta in future.

Indexed as

Computed Tomography AngiographyComputer SimulationHemodynamicsHydrodynamicsAortaChild, PreschoolFemaleHumansInfantMaleReproducibility of ResultsSystoleAortic hemodynamicsComputational fluid dynamicsCongenital heart diseaseMulti-detector computed tomography angiography

Identifiers

PMID29720173
PMCPMC5932836

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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.