Evidence map›Paper›PMID 39434870›Full record

ArticlePNAS nexus2024

Simulating cardiac fluid dynamics in the human heart.

Marshall Davey, Charles Puelz, Simone Rossi, Margaret Anne Smith, David R Wells, Gregory M Sturgeon, W Paul Segars, John P Vavalle, Charles S Peskin, Boyce E Griffith

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. A modelling study of right ventricular growth with valvular regurgitation.Biomechanics and modeling in mechanobiology · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Coupling Models of Resistive Valves to Muscle Mechanics in Cardiac Fluid-Structure Interaction Simulations.International journal for numerical methods in biomedical engineering · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. DIRECT MEDICAL IMAGE TO SIMULATION USING AUTO-SEGMENTATION AND POINT CLOUD-BASED CFD.Advances in computational science and engineering · 2025
    Article
  13. Article
  14. Article
  15. A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics.Computer methods in applied mechanics and engineering · 2024
    Article
  16. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Marshall DaveyCurriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC 27599, USA.ORCID https://orcid.org/0000-0002-3909-9664
Charles PuelzDepartment of Pediatrics-Cardiology, Baylor College of Medicine and Texas Children's Hospital, Houston, TX 77030, USA.ORCID https://orcid.org/0000-0002-1258-8433
Simone RossiDepartment of Mathematics, University North Carolina, Chapel Hill, NC 27599, USA.
Margaret Anne SmithDepartment of Mathematics, University North Carolina, Chapel Hill, NC 27599, USA.ORCID https://orcid.org/0009-0007-1480-5714
David R WellsDepartment of Mathematics, University North Carolina, Chapel Hill, NC 27599, USA.ORCID https://orcid.org/0000-0002-8325-9186
Gregory M SturgeonDepartment of Radiology, Duke University Medical Center, Durham, NC 27705, USA.
W Paul SegarsDepartment of Radiology, Duke University Medical Center, Durham, NC 27705, USA.ORCID https://orcid.org/0000-0003-3687-5733
John P VavalleDivision of Cardiology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA.
Charles S PeskinCourant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA.ORCID https://orcid.org/0000-0003-3749-9864
Boyce E GriffithDepartment of Mathematics, University North Carolina, Chapel Hill, NC 27599, USA.ORCID https://orcid.org/0000-0002-9800-7504

Funding

TR&D Project 3: Virtual ReadersP41EB028744 · NIBIB · DUKE UNIVERSITY · PI Ehsan Samei · 2021 to 2026
$7.8M
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
Precision Cardiac CT: Development of a Computational Platform for Optimizing ImagingR01HL131753 · NHLBI · DUKE UNIVERSITY · PI SAMEI, EHSAN, SEGARS, WILLIAM P · 2017 to 2020
$2.7M
UNC Predoc Training Progr in Bioinformatics/Comp BiologyT32GM067553 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELSTON, TIMOTHY C · 2005 to 2019
$2.5M
NHLBI NIH HHS R01 HL131753NHLBI NIH HHS R01 HL157631NHLBI NIH HHS U01 HL143336NIBIB NIH HHS P41 EB028744NIGMS NIH HHS T32 GM067553
6 · The paper itself

Abstract

Cardiac fluid dynamics fundamentally involves interactions between complex blood flows and the structural deformations of the muscular heart walls and the thin valve leaflets. There has been longstanding scientific, engineering, and medical interest in creating mathematical models of the heart that capture, explain, and predict these fluid-structure interactions (FSIs). However, existing computational models that account for interactions among the blood, the actively contracting myocardium, and the valves are limited in their abilities to predict valve performance, capture fine-scale flow features, or use realistic descriptions of tissue biomechanics. Here we introduce and benchmark a comprehensive mathematical model of cardiac FSI in the human heart. A unique feature of our model is that it incorporates biomechanically detailed descriptions of all major cardiac structures that are calibrated using tensile tests of human tissue specimens to reflect the heart's microstructure. Further, it is the first FSI model of the heart that provides anatomically and physiologically detailed representations of all four cardiac valves. We demonstrate that this integrative model generates physiologic dynamics, including realistic pressure-volume loops that automatically capture isovolumetric contraction and relaxation, and that its responses to changes in loading conditions are consistent with the Frank-Starling mechanism. These complex relationships emerge intrinsically from interactions within our comprehensive description of cardiac physiology. Such models can serve as tools for predicting the impacts of medical interventions. They also can provide platforms for mechanistic studies of cardiac pathophysiology and dysfunction, including congenital defects, cardiomyopathies, and heart failure, that are difficult or impossible to perform in patients.

Indexed as

cardiac fluid dynamicscardiac mechanicscomputational modelfluid–structure interactionheart valves

Identifiers

PMID39434870
PMCPMC11492567

What OpenQuestion holds

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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.