Development of a Computational Fluid Dynamics Model for Myocardial Bridging

Area of Science:

• Cardiovascular Science
• Biomedical Engineering
• Computational Biology

Background:

• Myocardial bridging (MB) presents challenges in computational fluid dynamics (CFD) due to its dynamic nature.
• Accurate hemodynamic assessment of MB is crucial for understanding its clinical implications.

Purpose of the Study:

• To develop a patient-specific CFD model for simulating myocardial bridging (MB).
• To analyze the hemodynamic impact of MB in the left anterior descending (LAD) coronary artery.
• To investigate the relationship between MB severity and altered blood flow patterns.

Main Methods:

• Developed a moving-boundary CFD algorithm to model patient-specific muscle compression in the LAD coronary artery.
• Created an in silico model of LAD with and without MB for comparative hemodynamic analysis.
• Analyzed hemodynamic parameters, including shear stress, in three patients with varying degrees of MB.

Main Results:

• Significant differences in average shear stress were observed between segments with and without MB (proximal: 0.32 Pa vs 0.97 Pa; bridge: 2.60 Pa vs 1.50 Pa).
• Increasing MB severity reduced proximal shear stress while increasing shear stress within the bridge segment.
• Hemodynamic abnormalities were identified in the proximal segment due to MB presence.

Conclusions:

• The developed CFD model accurately captures patient-specific MB hemodynamics.
• MB significantly alters coronary artery shear stress, potentially influencing atheroma development.
• Hemodynamic changes associated with MB may protect bridge segments from atheroma formation.