Computational Model for Early-Stage Aortic Valve Calcification Shows Hemodynamic Biomarkers

Area of Science:

• Biomaterials Science
• Cardiovascular Research
• Medical Engineering

Background:

• Heart disease remains a leading cause of mortality globally.
• Calcific aortic valve disease (CAVD) is the most common form, necessitating early detection for effective patient management.
• Predictive markers for early CAVD are crucial for timely intervention before aortic valve replacement surgery.

Purpose of the Study:

• To investigate hydrodynamic, mechanical, and hemodynamic differences between healthy and early-stage calcified porcine small intestinal submucosa (PSIS) bioscaffold valves.
• To identify potential parameters for tracking CAVD progression.
• To assess the suitability of PSIS bioscaffolds for modeling early CAVD.

Main Methods:

• Three groups of PSIS valves were tested: raw (control), calcified (seeded with VICs/VECs) in static conditions, and calcified (seeded with VICs/VECs) in bioreactor oscillatory flow.
• Hydrodynamic assessments and mechanical testing (Young's modulus) were performed.
• Fluid-structure interaction (FSI) simulations were conducted to analyze hemodynamic parameters like time-averaged wall shear stress (TAWSS).

Main Results:

• Hydrodynamic metrics in calcified valves were below thresholds for mild calcification.
• A significant increase in Young's modulus was observed in calcified valves compared to raw PSIS, indicating altered tissue structure.
• FSI simulations showed a significant increase in TAWSS in calcified valve groups compared to the raw control group.

Conclusions:

• While hydrodynamic metrics were not indicative of early calcification, increased mechanical stiffness (Young's modulus) suggests structural changes.
• Fluid-structure interaction simulations revealed a significant increase in time-averaged wall shear stress (TAWSS) in calcified valves.
• Hemodynamic monitoring, specifically TAWSS, may serve as a viable biomarker for early-stage calcific aortic valve disease (CAVD) tracking.