Computational Modeling Approach to Profile Hemodynamical Behavior in a Healthy Aorta

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Science

Background:

• Cardiovascular diseases (CVD) are a leading cause of mortality in older adults, necessitating early detection.
• Non-invasive tools for assessing aortic hemodynamic function are crucial for timely diagnosis and improved patient outcomes.
• Computational fluid dynamics (CFD) presents an efficient and cost-effective simulation method for cardiovascular dynamics.

Purpose of the Study:

• To develop and evaluate a CFD model for assessing aortic geometry and hemodynamics.
• To investigate the impact of mesh type (tetrahedral and polyhedral) on simulation accuracy and speed.
• To determine the clinical viability of CFD for non-invasive aortic assessment.

Main Methods:

• A CFD model of a healthy aorta was created using tetrahedral and polyhedral meshes (0.2–1 mm mesh size).
• Key hemodynamic parameters (pressure waveform, wall shear stress, relative residence time, oscillatory shear index, endothelial cell activation potential) were evaluated.
• Simulation accuracy and processing time were assessed to determine clinical applicability.

Main Results:

• The CFD model achieved over 95% accuracy in hemodynamic assessment.
• Simulation time was reduced by up to 54%, with the entire process completed in under 120 minutes.
• Both tetrahedral and polyhedral meshes yielded reliable hemodynamic analysis results.

Conclusions:

• CFD simulations provide accurate and efficient non-invasive aortic hemodynamic data.
• The developed CFD method is clinically viable, offering rapid diagnostics for routine check-ups.
• This approach can improve cardiovascular disease diagnostics, especially for underserved populations.