Computational Fluid Dynamic Model of Left Atrium to Analyze Hemodynamic Manifestation during Atrial Fibrillation

Area of Science:

• Cardiovascular Physiology
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Atrial fibrillation (AF) is a complex arrhythmia impacting cardiac hemodynamics.
• Understanding AF progression requires detailed analysis of blood flow and pressure dynamics within the left atrium (LA).
• Existing models often lack the integrated approach to capture the interplay between cardiac rhythm and hemodynamic changes.

Purpose of the Study:

• To develop and validate a coupled lumped-CFD (0d-3d) model for analyzing atrial fibrillation (AF) manifestation and progression.
• To investigate hemodynamic metrics associated with different AF types and sinus rhythm.
• To identify vulnerable regions in the heart and vasculature linked to thrombogenic plaque formation.

Main Methods:

• A novel 0d-3d coupled computational fluid dynamics (CFD) pipeline was developed, integrating a lumped cardiac model with 3D LA flow simulations.
• A rhythm generator was implemented to simulate variations in cardiac chamber compliance and contraction rates, mimicking sinus rhythm and AF.
• Subject-specific CT scans were used to perform CFD simulations of pulsatile flow and pressure fields.

Main Results:

• The model successfully predicted hemodynamic parameters, including flow, pressure, and wall shear stress, under various rhythm conditions (sinus rhythm, HF-AF, remodeled AF).
• Left ventricular (LV) hemodynamic parameters like ejection fraction, stroke volume, and cardiac output were derived.
• The simulation identified potential vulnerable regions within the LA and arterial vasculature associated with stroke risk.

Conclusions:

• The proposed 0d-3d coupled hemodynamic model offers valuable insights into AF dynamics.
• This approach can predict regions susceptible to thrombogenic plaque formation, potentially leading to stroke and heart failure.
• The model serves as a powerful tool for understanding AF pathophysiology and guiding therapeutic strategies.