A Multiscale Computational Framework to Understand Vascular Adaptation.

Area of Science:

• Biomedical Engineering
• Computational Biology
• Vascular Biology

Background:

• Vascular interventions like bypass grafting and angioplasty have high failure rates.
• Neointimal hyperplasia and aberrant vascular remodeling are key failure mechanisms.
• Current understanding lacks clear cause-effect links between pathological drivers and occlusive phenotypes.

Purpose of the Study:

• To develop a multiscale computational framework for vascular adaptation.
• To bridge the gap between theoretical models and experimental observations.
• To provide a systematic method for testing clinical hypotheses related to vascular failure.

Main Methods:

• A multiscale computational framework integrating cellular and tissue levels.
• An agent-based model to describe cellular-level tissue plasticity.
• Incorporation of feedback mechanisms between environmental conditions and tissue response.

Main Results:

• The proposed framework is modular and built upon fundamental mechano-biology principles.
• It facilitates agile development and systematic testing of hypotheses.
• Provides a novel approach to understanding vascular adaptation.

Conclusions:

• The computational framework offers a new tool for investigating vascular intervention failures.
• It can elucidate cause-effect relationships in vascular pathologies.
• Aids in the development of targeted therapeutic strategies.