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Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression

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A Fluid-Solid-Growth Solver for Cardiovascular Modeling.

Erica L Schwarz¹, Martin R Pfaller², Jason M Szafron²

¹Department of Bioengineering, Stanford Univeristy, Stanford, CA 94306, USA.

Computer Methods in Applied Mechanics and Engineering

|December 4, 2023

Summary

This summary is machine-generated.

We developed a new computational model for vascular growth and remodeling, enabling long-term, patient-specific predictions of blood flow and vessel changes. This tool aids in studying disease progression in complex vascular domains.

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Published on: May 27, 2022

Area of Science:

Computational mechanics
Biomedical engineering
Vascular biology

Background:

Accurate simulation of vascular dynamics is crucial for understanding disease.
Current fluid-structure interaction (FSI) models typically focus on short-term predictions.
Long-term vascular changes, including growth and remodeling, are complex and mechanobiologically dependent.

Purpose of the Study:

To integrate a full, three-dimensional constrained mixture theory for vascular growth and remodeling into an FSI solver.
To develop a novel "fluid-solid-growth" (FSG) solver capable of long-term, patient-specific simulations.
To enhance the clinical relevance of computational models for vascular disease research.

Main Methods:

Implementation of a three-dimensional constrained mixture theory.
Integration into a finite element fluid-structure interaction (FSI) framework.
Development of the "fluid-solid-growth" (FSG) solver.

Main Results:

The FSG solver enables long-term predictions of hemodynamics.
It predicts changes in vessel wall morphology, tissue composition, and material properties.
The model facilitates mechanobiologically-dependent studies in complex vascular geometries.

Conclusions:

The developed FSG solver extends short-term FSI capabilities to long-term predictions.
This advancement increases clinical relevance for studying vascular disease progression.
The model supports patient-specific analysis of vascular growth and remodeling.