Hemodynamic parameters measurements to assess severity of serial lesions in patient specific right coronary artery

Abstract

In this study, effects of serial stenosis on coronary hemodynamics were investigated in the human right coronary artery (RCA) using blood flow analysis. A 3-D model of a serial stenosed RCA was reconstructed based on multislice computerized tomography images. Numerical analysis examined the effect of multiple serial stenoses on the hemodynamic characteristics such as flow separation, pressure drop and FFR. Pressure loss associated with flow expansion after each constriction was large. Overall pressure drop increased from 1700 Pa (12.75 mmHg) at the end diastole to 11000 Pa (82.5 mmHg) at the peak systole. In two stenoses the corresponding pressure gradients werearound 30 mmHg and corresponded to the stenosis with FFR < 0.7 (associated to the sever stenosis). Severe stenosies caused large pressure drops across the throat. Blood flow distal to the stenosis was associated with fluctuations of the wall shear stress and vorticity.

Quantification of disturbed coronary flow by disturbed vorticity index and relation with fractional flow reserve

“…The magnitude of vorticity inherently depicts both the flow rate and its directional information. Previous studies have demonstrated that vorticity is relevant to turbulent flow as a result of lumen obstruction, local vessel expansion, or vessel motion; however, in these studies vorticity was assessed qualitatively rather than quantitatively (13)(14)(15).…”

Hemodynamic analysis of patient‐specific coronary artery tree

“…As can be seen, FFR had close and significant correlation with blood flow rate ( r = −0.995 and p = 0.005). This is because the curvilinear relation between flow increases and pressure loss (Figure ) . Holding other variable constant, higher flow rate led to higher pressure drop over the stenosis, which resulted in lower FFR.…”

“…These HPs include wall shear stress (WSS) , oscillatory shear index (OSI) , wall shear stress gradient (WSSG) , stress phase angle (SPA) , wall pressure, wall pressure gradient (WPG) and relative residence time (RRT) . In addition, CFD simulation on patient‐specific models has been explored to predict the clinical hemodynamic index of fractional flow reserve (FFR) for CAD diagnosis .…”

“…To the best of our knowledge, there were only a few studies that investigated the blood flow in the coronary artery tree as a complex network with the consideration of the interactions between bifurcation structure and single or multiple lesions. In this study, a left coronary artery tree was reconstructed using computed tomography angiography (CTA) images from a patient that exhibited multiple stenoses along the left anterior descending (LAD) artery.…”

Mathematical modelling of atherosclerosis

“…There exist two options for computation of the virtual FFR. The first option uses the 3D or 2D model of blood flow in the local region of the studied vessel [16,38,73,121,135,159,163,187] and suffers the bad posedness of upstream and downstream boundary conditions, rigid wall approximation for the vessel wall, high computational cost, local region for computational domain, difficulties in determining patient-specific parameters [140,181]. The recent trend is the use of machine learning tools for replacement of costly 3D simulations [45].…”