Patient specific multiscale modelling for plaque formation and progression.

Area of Science:

• Computational Fluid Dynamics (CFD) applied to cardiovascular research.
• Biomedical engineering focusing on atherosclerosis modeling.
• Multiphysics modeling of arterial disease progression.

Background:

• Atherosclerosis, characterized by plaque formation, is a leading cause of cardiovascular disease.
• Accurate modeling of plaque progression is crucial for understanding disease mechanisms and developing treatments.
• Current models often lack the comprehensive integration of fluid dynamics, mass transfer, and inflammatory processes.

Purpose of the Study:

• To develop and validate a comprehensive three-dimensional computational model of plaque formation and progression in coronary arteries.
• To investigate the influence of various factors, including patient risk scores and plaque characteristics, on plaque growth.
• To assess the model's effectiveness in predicting plaque evolution over a six-month period.

Main Methods:

• Utilized Navier-Stokes and continuity equations for 3D blood flow simulation.
• Incorporated convection-diffusion and Kedem-Katchalsky equations for Low Density Lipoprotein (LDL) transport and mass transfer.
• Modeled the inflammatory process using three reaction-diffusion partial differential equations.
• Integrated patient-specific data from coronary Computed Tomography angiography (CTA).

Main Results:

• A fully three-dimensional model of plaque formation and progression was successfully created.
• The model integrated blood flow, LDL transport, and inflammatory responses.
• Initial validation involved assessing model effectiveness over a 6-month period in patients with anginal symptoms.

Conclusions:

• The developed 3D model provides a robust framework for studying atherosclerosis.
• The model's ability to integrate multiple physiological processes offers new insights into plaque development.
• Further validation and application of this model can aid in predicting cardiovascular events and guiding therapeutic strategies.