An integrated approach to simulating the vulnerable atherosclerotic plaque

Area of Science:

• Biomedical Engineering
• Computational Biology
• Cardiovascular Research

Background:

• Current atherosclerotic plaque analysis relies on descriptive, passive methods with limited quantitative predictive power.
• Understanding plaque vulnerability and internal dynamics is crucial for effective clinical intervention.

Purpose of the Study:

• To introduce and discuss a novel computational framework for visualizing internal atherosclerotic plaque dynamics.
• To provide clinicians with quantitative insights into plaque evolution and morphology.

Main Methods:

• Utilized partial differential equations (PDEs) with key variables: macrophages, necrotic cells, oxidized lipids, oxygen, and platelet-derived growth factor (PDGF).
• Coupled PDEs with a biomechanical model to simulate vessel growth and plaque development.
• Developed a deterministic model generating mechanical, morphological, and histological characteristics over time.

Main Results:

• Created computer-generated animations of plaque evolution, showing qualitative agreement with serial ultrasound images.
• The systems biology model accurately captured the morphology of necrotic cores in vulnerable plaques.
• Identified oxidized low-density lipoprotein (Ox-LDL), inflammation, and oxygenation as key drivers of core morphology changes.

Conclusions:

• The proposed quantitative framework offers a powerful tool for understanding and visualizing atherosclerotic plaque evolution.
• The model's outputs, including color-coded vessel sections, are qualitatively similar to enhanced intravascular ultrasound images.
• This computational approach has the potential to enhance clinical insights into plaque progression and vulnerability.