Evidence map›Paper›PMID 36209266›Full record

ArticleAnnals of biomedical engineering2023

Semi-Automated Construction of Patient-Specific Aortic Valves from Computed Tomography Images.

Dan Lior, Charles Puelz, Colin Edwards, Silvana Molossi, Boyce E Griffith, Ravi K Birla, Craig G Rusin

Abstract read
In one paragraph

Article in Annals of biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. CardioVision: A fully automated deep learning package for medical image segmentation and reconstruction generating digital twins for patients with aortic stenosis.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2023
    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.

Dan LiorDivision of Cardiology, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA.
Charles PuelzDivision of Cardiology, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA. charles.puelz@bcm.edu.ORCID http://orcid.org/0000-0002-1258-8433
Colin EdwardsDepartment of Mechanical Engineering, Rice University, Houston, TX, USA.
Silvana MolossiDivision of Cardiology, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA.
Boyce E GriffithDepartments of Mathematics, Biomedical Engineering, and Applied Physical Sciences, and Carolina Center for Interdisciplinary Applied Mathematics, University of North Carolina, Chapel Hill, NC, USA.ORCID http://orcid.org/0000-0002-9800-7504
Ravi K BirlaDivision of Congenital Heart Surgery, Department of Pediatric Surgery, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA.
Craig G RusinDivision of Cardiology, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA.

Funding

Multiscale Modeling of Clotting Risk in Atrial FibrillationU01HL143336 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GRIFFITH, BOYCE EUGENE · 2018 to 2022
$2.8M
Computational and Experimental Modeling of Subclinical Leaflet Thrombosis in Bioprosthetic Aortic ValvesR01HL157631 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FOGELSON, AARON L, GRIFFITH, BOYCE EUGENE · 2022 to 2025
$2.7M
National Science Foundation OAC 1652541National Science Foundation OAC 1931516NHLBI NIH HHS R01 HL157631NHLBI NIH HHS U01 HL143336NIH HHS R01HL157631NIH HHS U01HL143336
6 · The paper itself

Abstract

This paper presents a semi-automatic method for the construction of volumetric models of the aortic valve using computed tomography angiography images. Although the aortic valve typically cannot be segmented directly from a computed tomography angiography image, the method described herein uses manually selected samples of an aortic segmentation derived from this image to inform the construction. These samples capture certain physiologic landmarks and are used to construct a volumetric valve model. As a demonstration of the capabilities of this method, valve models for 25 pediatric patients are created. A selected valve anatomy is used to perform fluid-structure interaction simulations using the immersed finite element/difference method with physiologic driving and loading conditions. Simulation results demonstrate this method creates a functional valve that opens and closes normally and generates pressure and flow waveforms that are similar to those observed clinically.

Indexed as

Aortic ValveModels, CardiovascularChildComputed Tomography AngiographyComputer SimulationHumansTomography, X-Ray ComputedAnatomical reconstructionAortic valveComputed tomographyFluid–structure interactionImmersed finite element/difference method

Identifiers

PMID36209266
PMCPMC10682914

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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.