A Multi-physics model of flow from coronary angiography: Insights to microvascular function

Haizhou Yang1, Jiyang Zhang2, Ismael Z Assi3

  • 1Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.

Insights

This study developed a computational model to analyze coronary angiography data for diagnosing coronary microvascular dysfunction (CMD). The model shows resistance significantly impacts contrast washout, offering a new way to assess microcirculation.

Area of Science:

  • Cardiovascular research
  • Medical imaging analysis
  • Computational fluid dynamics

Background:

  • Coronary microvascular dysfunction (CMD) affects millions, characterized by impaired vasodilation and reduced myocardial blood flow.
  • Current invasive diagnostics (IMR, CFR) have limited clinical adoption due to complexity.
  • Coronary angiography provides flow data for CMD diagnosis but is underutilized.

Purpose of the Study:

  • To develop and validate a computational fluid dynamics (CFD) model for analyzing coronary angiography data.
  • To introduce a contrast intensity profile (CIP) to quantify contrast dynamics.
  • To assess the impact of coronary lumped parameter model (LPM) variables on CIP.

Main Methods:

  • A 3D-0D coupled multi-physics CFD model was created and calibrated.
  • Simulations focused on contrast injection and washout during angiography.
  • Sensitivity analyses explored the influence of LPM parameters on CIP.

Main Results:

  • The CFD model successfully produced physiologically relevant hemodynamic outcomes.
  • Model calibration allowed for effective simulation of angiography processes.
  • Sensitivity studies indicated resistance significantly influences CIP slopes compared to capacitance.

Conclusions:

  • A novel modeling framework shows potential for extracting coronary microcirculation information from angiography.
  • The approach requires in vivo validation for clinical application.
  • Future clinical studies are necessary to confirm the model's utility in diagnosing CMD.
Abstract