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

Abstract

We introduce a Computational Fluid Dynamics (CFD) based method for performing patient-specific coronary hemodynamic computations under two conditions: at rest and during drug-induced hyperemia. The proposed method is based on a novel estimation procedure for determining the boundary conditions from non-invasively acquired patient data at rest. A multi-variable feedback control framework ensures that the computed mean arterial pressure and the flow distribution matches the estimated values for an individual patient during the rest state. The boundary conditions at hyperemia are derived from the respective rest-state values via a transfer function that models the vasodilation phenomenon. Simulations are performed on a coronary tree where a 65% diameter stenosis is introduced in the left anterior descending (LAD) artery, with the boundary conditions estimated using the proposed method. The results demonstrate that the estimation of the hyperemic resistances is crucial in order to obtain accurate values for pressure and flow rates. Results from an exhaustive sensitivity analysis have been presented for analyzing the variability of trans-stenotic pressure drop and Fractional Flow Reserve (FFR) values with respect to various measurements and assumptions.

Coronary CT Angiography–derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling

“…For the FFR CFD algorithm, a hybrid reduced-order for fast flow computation was used (7,8). Blood flow during a hyperemic state was computed from the geometric coronary artery model along with patient-specific boundary conditions.…”

Mathematical Modeling of Coronary Blood Flow to Assess the Functional Significance of Stenotic Lesion by Computed Tomography

“…Формулировка граничных условий включает систолическое и диастолическое давление в аорте в состоянии покоя, частоту сердечных сокращений и массу миокарда левого желудочка (ЛЖ). Указанные условия модифицируют так, чтобы учесть эффект максимальной гиперемии путем моделирования снижения микрососудистого сопротивления, вызванного введением аденозина [15,22]. Вычисление значений ФРККТА основано на уравнениях Навье-Стокса, описывающих гидродинамические закономерности кровотока.…”

Coronary CT Angiography–derived Fractional Flow Reserve

“…Tesche et al heart rate, and ventricular mass. The conditions are then modified to incorporate the effect of maximal hyperemia by modeling the decrease in microvascular resistance caused by the administration of adenosine (75,81). The computation of FFR CT values are based on the Navier-Stokes equations, the physical laws that govern fluid dynamics.…”

“…A patientspecific reduced-order computational fluid dynamics model has been recently introduced, enabling FFR CT determination by using individual boundary conditions with a hybrid approach, coupling reduced-order and full-order models for fast flow computation. The computational fluid dynamics approach employs numerical methods to compute time-varying flow and pressures by solving the reduced-order Navier-Stokes equations, with blood being modeled as an incompressible fluid with constant an approach is attractive, as there is no need for additional image acquisition or administration of pharmacologic stress agents (75,76). The scientific principles of some of the underlying techniques were previously described in detail (5,75,77,78).…”