Evidence map›Paper›PMID 28011839›Full record

ArticleEuropace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology2016

Patient-specific modeling of left ventricular electromechanics as a driver for haemodynamic analysis.

Christoph M Augustin, Andrew Crozier, Aurel Neic, Anton J Prassl, Elias Karabelas, Tiago Ferreira da Silva, Joao F Fernandes, Fernando Campos, Titus Kuehne, Gernot Plank

Abstract read
In one paragraph

Article in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2016. 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. Trial
  2. Accurate Reconstruction of Right Heart Shape and Motion From Cine-MRI for Image-Driven Computational Hemodynamics.International journal for numerical methods in biomedical engineering · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function.International journal for numerical methods in biomedical engineering · 2021
    Article
  9. Data integration for the numerical simulation of cardiac electrophysiology.Pacing and clinical electrophysiology : PACE · 2021
    Review
  10. Review
  11. Personalization of electro-mechanical models of the pressure-overloaded left ventricle: fitting of Windkessel-type afterload models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2020
    Article
  12. Article
  13. Article
  14. Optimization Framework for Patient-Specific Cardiac Modeling.Cardiovascular engineering and technology · 2019
    Article
  15. Virtual downsizing for decision support in mitral valve repair.International journal of computer assisted radiology and surgery · 2019
    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

10 authors.

Christoph M AugustinInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Andrew CrozierInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Aurel NeicInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Anton J PrasslInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Elias KarabelasInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Tiago Ferreira da SilvaDepartment of Congenital Heart Disease/Pediatric Cardiology, German Heart Institute Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
Joao F FernandesDepartment of Congenital Heart Disease/Pediatric Cardiology, German Heart Institute Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
Fernando CamposInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria.
Titus KuehneDepartment of Congenital Heart Disease/Pediatric Cardiology, German Heart Institute Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
Gernot PlankInstitute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010 Graz, Austria gernot.plank@medunigraz.at.

Funding

Austrian Science Fund FWF F 3210Austrian Science Fund FWF I 2760
6 · The paper itself

Abstract

aimsModels of blood flow in the left ventricle (LV) and aorta are an important tool for analysing the interplay between LV deformation and flow patterns. Typically, image-based kinematic models describing endocardial motion are used as an input to blood flow simulations. While such models are suitable for analysing the hemodynamic status quo, they are limited in predicting the response to interventions that alter afterload conditions. Mechano-fluidic models using biophysically detailed electromechanical (EM) models have the potential to overcome this limitation, but are more costly to build and compute. We report our recent advancements in developing an automated workflow for the creation of such CFD ready kinematic models to serve as drivers of blood flow simulations. METHODS AND

resultsEM models of the LV and aortic root were created for four pediatric patients treated for either aortic coarctation or aortic valve disease. Using MRI, ECG and invasive pressure recordings, anatomy as well as electrophysiological, mechanical and circulatory model components were personalized.

resultsThe implemented modeling pipeline was highly automated and allowed model construction and execution of simulations of a patient's heartbeat within 1 day. All models reproduced clinical data with acceptable accuracy.

conclusionUsing the developed modeling workflow, the use of EM LV models as driver of fluid flow simulations is becoming feasible. While EM models are costly to construct, they constitute an important and nontrivial step towards fully coupled electro-mechano-fluidic (EMF) models and show promise as a tool for predicting the response to interventions which affect afterload conditions.

Indexed as

HemodynamicsModels, CardiovascularPatient-Specific ModelingVentricular Function, LeftAction PotentialsAdolescentAortic CoarctationAortic ValveAutomationBiomechanical PhenomenaCardiac CatheterizationChildElectrocardiographyElectrophysiologic Techniques, CardiacFemaleHeart RateComputer modelLeft ventricular electromechanicsPersonalization

Identifiers

PMID28011839
PMCPMC5386137

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.