Multi-Modal in Vitro Experiments Mimicking the Flow Through a Mitral Heart Valve Phantom.

Area of Science:

• Cardiovascular Research
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Fluid-structure interaction (FSI) models are increasingly used in medical research, particularly for patient-specific cardiac applications.
• Accurate validation of these FSI models is critical for understanding heart valve disease.
• A need exists for comprehensive benchmarking datasets to ensure the reliability of cardiac FSI models.

Purpose of the Study:

• To establish a multi-modal benchmarking dataset for cardiac-inspired FSI models.
• To focus on clinically relevant parameters including pressure, velocity, and mitral valve dynamics.
• To utilize an in vitro phantom setup for data generation.

Main Methods:

• Developed a 3D-printed in vitro phantom replicating the left heart and a deforming mitral valve.
• Generated various pulsatile flow conditions using a computer-controlled pump system.
• Acquired data through catheter pressure measurements, magnetic resonance imaging (MRI), and echocardiography (Echo) for pressure, velocity, and valve opening quantification.

Main Results:

• Successfully constructed and validated the experimental setup with low cycle-to-cycle variation (0.5%).
• Investigated six distinct flow cases, observing increased mitral valve velocity and pressure differences with higher cardiac output.
• Qualitatively assessed ventricular flow patterns and streamlines using 4D phase-contrast MRI.

Conclusions:

• Created a comprehensive multi-modal dataset suitable for validating FSI models in cardiovascular research.
• The generated data is relevant for diagnosing heart valve disease.
• All collected data is publicly accessible to support the advancement of computational heart valve modeling.