Evidence map›Paper›PMID 36853513›Full record

ArticleBiomechanics and modeling in mechanobiology2023

A parametric geometry model of the aortic valve for subject-specific blood flow simulations using a resistive approach.

Giorgia Pase, Emiel Brinkhuis, Tanja De Vries, Jiří Kosinka, Tineke Willems, Cristóbal Bertoglio

Abstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Coupling Models of Resistive Valves to Muscle Mechanics in Cardiac Fluid-Structure Interaction Simulations.International journal for numerical methods in biomedical engineering · 2025
    Article
  4. Review
  5. Article
  6. 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

6 authors.

Giorgia PaseBernoulli Institute, University of Groningen, Nijenborgh 9, Groningen, 9747AG, The Netherlands. g.pase@rug.nl.
Emiel BrinkhuisBernoulli Institute, University of Groningen, Nijenborgh 9, Groningen, 9747AG, The Netherlands.
Tanja De VriesBernoulli Institute, University of Groningen, Nijenborgh 9, Groningen, 9747AG, The Netherlands.
Jiří KosinkaBernoulli Institute, University of Groningen, Nijenborgh 9, Groningen, 9747AG, The Netherlands.
Tineke WillemsDepartment of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen, 9713GZ, The Netherlands.
Cristóbal BertoglioBernoulli Institute, University of Groningen, Nijenborgh 9, Groningen, 9747AG, The Netherlands.

Funding

HORIZON EUROPE European Research Council 852544 - Cardiozoom
6 · The paper itself

Abstract

Cardiac valves simulation is one of the most complex tasks in cardiovascular modeling. Fluid-structure interaction is not only highly computationally demanding but also requires knowledge of the mechanical properties of the tissue. Therefore, an alternative is to include valves as resistive flow obstacles, prescribing the geometry (and its possible changes) in a simple way, but, at the same time, with a geometry complex enough to reproduce both healthy and pathological configurations. In this work, we present a generalized parametric model of the aortic valve to obtain patient-specific geometries that can be included into blood flow simulations using a resistive immersed implicit surface (RIIS) approach. Numerical tests are presented for geometry generation and flow simulations in aortic stenosis patients whose parameters are extracted from ECG-gated CT images.

Indexed as

Aortic ValveAortic Valve StenosisComputer SimulationHemodynamicsHumansModels, CardiovascularAortic valve modelBlood flow simulationParametric modelSubject-specific

Identifiers

PMID36853513
PMCPMC10167200

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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.