Computational modeling of left heart diastolic function: examination of ventricular dysfunction

Area of Science:

• Computational fluid dynamics
• Biomedical engineering
• Cardiovascular physiology

Background:

• Understanding diastolic dysfunction is crucial for diagnosing and treating heart failure.
• Existing models may not fully capture the complex blood-tissue interactions within the left heart during diastole.

Purpose of the Study:

• To develop and validate a computational model of the left heart that integrates blood-tissue dynamics.
• To simulate and analyze diastolic dysfunction by modifying cardiac chamber properties.

Main Methods:

• A computational model incorporating the Immersed Boundary Method for blood-tissue interaction.
• Solution of fluid mass and momentum conservation using Patankar's SIMPLE algorithm.
• Simulation of three diastolic dysfunction scenarios: delayed relaxation, increased stiffness, and increased atrial contraction.

Main Results:

• The model successfully replicated clinical observations of diastolic flow fields under abnormal conditions.
• Delayed ventricular relaxation decreased early filling, with a more pronounced effect when ventricular stiffness increased.
• Increased atrial contraction led to higher late filling velocity and atrial pressure.

Conclusions:

• Computational modeling of cardiac chamber properties (fiber resting-length, stiffness) can accurately represent diastolic dysfunction.
• This validated model provides a robust platform for future research into cardiovascular diseases and their impact on global flow dynamics.