A framework for personalization of coronary flow computations during rest and hyperemia

Area of Science:

• Cardiovascular Physiology
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Accurate assessment of coronary artery disease requires patient-specific hemodynamic analysis.
• Non-invasive methods are preferred for determining physiological parameters.
• Computational Fluid Dynamics (CFD) offers a powerful tool for simulating blood flow.

Purpose of the Study:

• To develop and validate a CFD-based method for patient-specific coronary hemodynamics at rest and during hyperemia.
• To introduce a novel boundary condition estimation technique using non-invasively acquired data.
• To assess the impact of hyperemic resistance estimation on pressure and flow rate accuracy.

Main Methods:

• A multi-variable feedback control framework was employed to match computed hemodynamics with estimated patient-specific values at rest.
• Boundary conditions for hyperemia were derived from rest-state values using a vasodilation model transfer function.
• Simulations were performed on a coronary tree model with a 65% diameter stenosis in the LAD artery.

Main Results:

• The proposed method successfully estimated patient-specific coronary hemodynamic conditions.
• Accurate estimation of hyperemic resistances was found to be critical for precise pressure and flow rate calculations.
• Sensitivity analysis revealed the variability of trans-stenotic pressure drop and Fractional Flow Reserve (FFR) due to measurement uncertainties.

Conclusions:

• The developed CFD method provides a robust approach for patient-specific coronary hemodynamic assessment.
• Accurate characterization of hyperemic states is essential for reliable FFR and pressure drop predictions.
• The findings highlight the importance of considering measurement variability in clinical applications.