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Updated: Jan 17, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Cardiac mechanics modeling: recent developments and current challenges.

Aaron L Brown^1,2, Ju Liu³, Daniel B Ennis^2,4,5

¹Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.

|September 18, 2025

Summary

This summary is machine-generated.

Patient-specific computational heart models aid cardiovascular research but are complex to build. Simplifying essential complexities is key for clinical use.

Keywords:

Cardiac digital twin Cardiac mechanics Computational cardiology Multiphysics modeling Patient-specific modeling

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Published on: April 18, 2018

Area of Science:

Cardiovascular research
Computational modeling
Biomedical engineering

Background:

Patient-specific computational heart models offer significant potential in cardiovascular research and clinical applications, including treatment planning and device evaluation.
Constructing these models is challenging due to the heart's complexity, requiring careful consideration of anatomy, material properties, and physics.
Current modeling approaches often involve a trade-off between physiological accuracy and computational complexity.

Purpose of the Study:

To review recent advancements in patient-specific computational heart modeling.
To identify and discuss unresolved questions in the field, particularly concerning cardiac tissue mechanics.
To highlight the importance of balancing model complexity with physiological fidelity for clinical translation.

Main Methods:

Review of recent literature on computational heart modeling techniques.
Analysis of key considerations in model construction: anatomy reconstruction, mesostructure representation, material behavior, geometry and boundary conditions, multi-physics coupling, and numerical methods.
Emphasis on cardiac tissue mechanics and its associated challenges.

Main Results:

Recent advances have been made across various aspects of computational heart modeling, from image-based anatomy reconstruction to multi-physics coupling.
Significant challenges remain in accurately representing myocardial mesostructure and material behavior.
The selection of numerical methods and boundary conditions critically impacts model fidelity and computational cost.

Conclusions:

Clarifying which complex features are essential for physiological accuracy versus those that can be simplified is crucial.
Reducing unnecessary complexity will facilitate the clinical translation of patient-specific computational heart models.
Further research is needed to optimize the balance between fidelity and complexity for effective clinical application.