Simulating cardiac fluid dynamics in the human heart

Cardiac fluid dynamics fundamentally involves interactions between complex blood flows and the structural deformations of the muscular heart walls and the thin, flexible 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. However, existing computational models that account for interactions among the blood, the actively contracting myocardium, and the cardiac valves are limited in their abilities to predict valve performance, resolve fine-scale flow features, or use realistic descriptions of tissue biomechanics. Here we introduce and benchmark a comprehensive mathematical model of cardiac fluid dynamics 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 fluid-structure interaction 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 predicts fine-scale flow features. None of these outputs are prescribed; instead, they emerge from interactions within our comprehensive description of cardiac physiology. Such models can serve as tools for predicting the impacts of medical devices or clinical interventions. They also can serve as 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.

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Publication Details

Journal
PNAS Nexus
Published
2024-09-10
DOI
https://doi.org/10.1093/pnasnexus/pgae392
Citations
21
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
Field-Weighted Citation Impact
8.44

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article

Simulating cardiac fluid dynamics in the human heart

Gregory M. Sturgeon, Charles Puelz, John P. Vavalle, W. Paul Segars et al.
21 citations
PNAS Nexus
Cardiovascular Function and Risk Factors
8.44
article

Simulating cardiac fluid dynamics in the human heart

Gregory M. Sturgeon, Charles Puelz, John P. Vavalle, W. Paul Segars, David Wells, Charles S. Peskin, Marshall Davey, Boyce E. Griffith, Símone Rossi, Margaret Anne Smith
article en
21 citations

Abstract

Cardiac fluid dynamics fundamentally involves interactions between complex blood flows and the structural deformations of the muscular heart walls and the thin, flexible 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. However, existing computational models that account for interactions among the blood, the actively contracting myocardium, and the cardiac valves are limited in their abilities to predict valve performance, resolve fine-scale flow features, or use realistic descriptions of tissue biomechanics. Here we introduce and benchmark a comprehensive mathematical model of cardiac fluid dynamics 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 fluid-structure interaction 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 predicts fine-scale flow features. None of these outputs are prescribed; instead, they emerge from interactions within our comprehensive description of cardiac physiology. Such models can serve as tools for predicting the impacts of medical devices or clinical interventions. They also can serve as 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.

PNAS NexusVol. 3(10)
University of North Carolina at Chapel Hill (US), Baylor College of Medicine (US), Courant Institute of Mathematical Sciences (US), Duke Medical Center (US), Texas Children's Hospital (US), Duke University Hospital (US), University of Houston (US), New York University (US)
National Science Foundation, National Institutes of Health, University of North Carolina at Chapel Hill
Good health and well-being
Openalex Percentile: Top 2%
Cardiovascular Function and Risk Factors
8.44
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