Evidence map›Paper›PMID 32849909›Full record

ArticleComputational and mathematical methods in medicine2020

Patient-Specific CT-Based Fluid-Structure-Interaction Aorta Model to Quantify Mechanical Conditions for the Investigation of Ascending Aortic Dilation in TOF Patients.

Heng Zuo, Yunfei Ling, Peng Li, Qi An, Xiaobo Zhou

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

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2 · The registry

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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

1 citing paper in PubMed, 5 citations in OpenAlex.

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4 · The record

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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

5 authors at 2 institutions in 2 countries.

Heng ZuoBiomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.ORCID https://orcid.org/0000-0002-4937-6039
Yunfei LingDepartment of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.
Peng LiBiomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.
Qi AnDepartment of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu 610041, China.
Xiaobo ZhouCenter for Computational Systems Medicine and School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
Sichuan University · CNThe University of Texas Health Science Center at Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSome adult patients with Tetralogy of Fallot (TOF) were found to simultaneously develop ascending aortic dilation. Severe aortic dilation would lead to several aortic diseases, including aortic aneurysm and dissection, which seriously affect patients' living quality and even cause patients' death. Current practice guidelines of aortic-dilation-related diseases mainly focus on aortic diameter, which has been found not always a good indicator. Therefore, it may be clinically useful to identify some other factors that can potentially better predict aortic response to dilation.

methods20 TOF patients scheduled for TOF repair surgery were recruited in this study and were divided into dilated and nondilated groups according to the

resultsSimulation results demonstrated a good coincidence between numerical mean flow rate at inlet and the one obtained from color Doppler ultrasonography, which implied that computational models were able to simulate the movement of the aorta and blood inside accurately. Our results indicated that aortic stress can effectively differentiate patients of the dilated group from the ones of the nondilated group. Mean ascending aortic stress-P1 (maximal principal stress) from the dilated group was 54% higher than that from the nondilated group (97.97 kPa vs. 63.47 kPa,

conclusionComputational modeling and ascending aortic biomechanical factors may be used as a potential tool to identify and analyze aortic response to dilation. Large-scale clinical studies are needed to validate these preliminary findings.

Indexed as

Patient-Specific ModelingAdolescentAdultAortaAortic DiseasesBiomechanical PhenomenaChildComputational BiologyComputed Tomography AngiographyComputer SimulationDilatation, PathologicFemaleHemodynamicsHumansImaging, Three-DimensionalMale

Identifiers

PMID32849909
PMCPMC7439781
OpenAlexW3047799022

What Socratic holds

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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 Socratic graph.