Evidence map›Paper›PMID 39678645›Full record

ArticleEngineering with computers2024

Parameterization, algorithmic modeling, and fluid-structure interaction analysis for generative design of transcatheter aortic valves.

Xianyu George Pan, Ashton M Corpuz, Manoj R Rajanna, Emily L Johnson

Abstract read
In one paragraph

Article in Engineering with computers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

4 authors.

Xianyu George PanDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN USA.
Ashton M CorpuzDepartment of Mechanical Engineering, Iowa State University, Ames, IA USA.
Manoj R RajannaGlobal Engineering and Materials, Inc., Princeton, NJ USA.
Emily L JohnsonDepartment of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN USA.ORCID 0000-0003-2657-9906

Funding

Biomechanical indicators of bicuspid aortic valve dysfunctionR01HL142504 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI GORMAN, ROBERT C, HSU, MING-CHEN · 2018 to 2021
$2.9M
NHLBI NIH HHS R01 HL142504
6 · The paper itself

Abstract

Heart valves play a critical role in maintaining proper cardiovascular function in the human heart; however, valve diseases can lead to improper valvular function and reduced cardiovascular performance. Depending on the extent and severity of the valvular disease, replacement operations are often required to ensure that the heart continues to operate properly in the cardiac system. Transcatheter aortic valve replacement (TAVR) procedures have recently emerged as a promising alternative to surgical replacement approaches because the percutaneous methods used in these implant operations are significantly less invasive than open heart surgery. Despite the advantages of transcatheter devices, the precise deployment, proper valve sizing, and stable anchoring required to securely place these valves in the aorta remain challenging even in successful TAVR procedures. This work proposes a parametric modeling approach for transcatheter heart valves (THVs) that enables flexible valvular development and sizing to effectively generate existing and novel valve designs. This study showcases two THV configurations that are analyzed using an immersogeometric fluid-structure interaction (IMGA FSI) framework to demonstrate the influence of geometric changes on THV performance. The proposed modeling framework illustrates the impact of these features on THV behavior and indicates the effectiveness of parametric modeling approaches for enhancing THV performance and efficacy in the future.

Indexed as

Fluid–structure interactionImmersogeometric analysisParametric modelingTAVRTranscatheter heart valve

Identifiers

PMID39678645
PMCPMC11639685

What OpenQuestion holds

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LicenceCC BY
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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.