Ultrasound-based computational fluid dynamics analysis of carotid artery hemodynamics in healthy and stenosed...

Area of Science:

• Biomedical Engineering
• Cardiovascular Imaging
• Computational Fluid Dynamics

Background:

• Carotid atherosclerosis significantly elevates stroke risk.
• Current risk assessment relies on stenosis degree, which is an inadequate predictor of individual vulnerability.
• Novel methods are needed for precise patient-specific risk stratification.

Purpose of the Study:

• To develop and validate an ultrasound-based computational fluid dynamics (CFD) framework for patient-specific hemodynamic assessment of carotid arteries.
• To identify and visualize hemodynamic risk factors beyond simple stenosis measurements.
• To explore the diagnostic potential of novel hemodynamic parameters, such as helicity.

Main Methods:

• Reconstruction of patient-specific carotid artery geometries from tracked 2D ultrasound data and automated segmentation.
• Application of computational fluid dynamics (CFD) simulations to quantify hemodynamic parameters.
• Visualization of hemodynamic risk maps, including Time-Averaged Wall Shear Stress (TAWSS), Oscillatory Shear Index (OSI), and Relative Residence Time (RRT), and helicity.

Main Results:

• The developed CFD framework successfully generated patient-specific hemodynamic risk maps.
• Healthy carotid arteries displayed localized hemodynamic risk near bifurcations.
• Carotid arteries with severe stenoses exhibited widespread disturbed flow patterns and significantly altered helicity.

Conclusions:

• Ultrasound-driven CFD is a feasible approach for personalized hemodynamic risk mapping in carotid arteries.
• Helicity patterns show promise as a novel diagnostic marker for assessing stroke risk.
• This methodology offers a more accurate alternative to traditional stenosis-based risk assessment.