Using high resolution cardiac CT data to model and visualize patient-specific interactions between trabeculae and...

Area of Science:

• Cardiovascular Science
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Accurate simulation of blood flow in the human heart is crucial for understanding cardiac function and disease.
• Previous methods lacked detailed visualization of blood interaction with complex intra-ventricular structures.
• The motion of the left ventricle's endocardial surface is a key determinant of intra-ventricular hemodynamics.

Purpose of the Study:

• To develop and present a method for simulating and visualizing blood flow within the human heart.
• To utilize 4D reconstructions of the left ventricle's endocardial motion as boundary conditions for simulations.
• To investigate the detailed interactions between blood flow and cardiac structures like papillary muscles and trabeculae.

Main Methods:

• Reconstruction of the 4D motion of the left ventricle's endocardial surface.
• Implementation of computational fluid dynamics (CFD) simulations using these 4D reconstructions.
• Generation of detailed flow field visualizations to analyze blood-tissue interactions.
• Comparison of simulation results between a healthy heart and two diseased heart models.

Main Results:

• The method successfully simulates and visualizes blood flow, capturing complex interactions with papillary muscles and trabeculae.
• Visualizations provide unprecedented detail on blood flow dynamics within the left ventricle.
• Significant differences in blood flow patterns were observed between the healthy and diseased heart simulations.
• The study offers a new tool for detailed analysis of cardiac hemodynamics.

Conclusions:

• The developed simulation method enhances the understanding of cardiac blood flow, particularly concerning intra-ventricular structures.
• This approach promises improved insights into the mechanisms of cardiac diseases affecting blood flow.
• The detailed visualization capabilities offer potential for clinical diagnostics and treatment planning.