A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional...

Area of Science:

• Cardiovascular Imaging and Hemodynamics
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Stroke risk stratification is crucial for intervention, but current models lack personalization.
• Cardiac dynamics play a significant role in stroke etiology.
• Existing risk models often fail to capture individual patient variations.

Purpose of the Study:

• To develop a personalized stroke risk assessment framework.
• To integrate functional data from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations.
• To enhance the mechanistic understanding of stroke risk by analyzing hemodynamic features.

Main Methods:

• Utilized CINE CMR to compute kinematic features and assess left atrial volumes.
• Incorporated patient-specific atrial displacement into CFD simulations.
• Developed a novel framework for integrating hemodynamic and functional metrics.

Main Results:

• Stroke patients exhibited smaller left atrial volumes.
• Patient-specific atrial motion significantly influenced hemodynamic simulations, challenging rigid wall assumptions.
• Normalizing hemodynamic features by stroke volume, not ejection fraction, clearly differentiated stroke from control cases in the left atrium and appendage.

Conclusions:

• The synergistic fusion of CMR-derived functional data and patient-informed CFD simulations provides a personalized understanding of stroke risk.
• This integrated approach offers superior differentiation between stroke and control cases compared to standalone assessments.
• The findings highlight the clinical significance of motion-informed, personalized risk assessments for improved stroke prediction.