An agent-based model of cardiac allograft vasculopathy: toward a better understanding of chronic rejection dynamics

Elisa Serafini1,2,3, Anna Corti4, Diego Gallo1

  • 1PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.

Insights

Agent-based models (ABMs) simulate cardiac allograft vasculopathy (CAV) in heart transplant recipients. This computational approach aids understanding of CAV progression, highlighting inflammation as a key driver.

Area of Science:

  • Computational Biology
  • Cardiovascular Research
  • Transplantation Immunology

Background:

  • Cardiac allograft vasculopathy (CAV) affects 50% of heart transplant recipients, causing graft loss.
  • Current in vivo models are resource-intensive, ethically challenging, and limit detailed analysis.
  • Understanding CAV's complex etiology and pathology is crucial for improved disease management.

Purpose of the Study:

  • To develop and validate a bidimensional agent-based model (ABM) for simulating CAV.
  • To investigate the interplay of inflammation and hemodynamic disturbances (low wall shear stress) in CAV.
  • To assess the potential of ABMs to augment in vivo research for CAV.

Main Methods:

  • A 2D agent-based model simulating a mouse coronary artery cross-section was developed.
  • The model simulated responses to inflammatory stimuli and low wall shear stress (WSS).
  • Parameter and input sensitivity analyses were conducted to understand model behavior.

Main Results:

  • The ABM successfully replicated 4-week CAV initiation and progression, showing lumen area decrease.
  • Progressive intimal thickening was observed in regions with high inflammation and low WSS.
  • Sensitivity analysis indicated that inflammation, not WSS, predominantly drives CAV progression.

Conclusions:

  • Agent-based modeling provides a powerful, resource-efficient tool for studying CAV.
  • The model confirms the critical role of inflammation in cardiac allograft vasculopathy.
  • This ABM approach can deepen pathological knowledge and support in vivo CAV research.