Compound Ex Vivo and In Silico Method for Hemodynamic Analysis of Stented Arteries

Abstract

Hemodynamic factors such as low wall shear stress have been shown to influence endothelial healing and atherogenesis in stent-free vessels. However, in stented vessels, a reliable quantitative analysis of such relations has not been possible due to the lack of a suitable method for the accurate acquisition of blood flow. The objective of this work was to develop a method for the precise reconstruction of hemodynamics and quantification of wall shear stress in stented vessels. We have developed such a method that can be applied to vessels stented in or ex vivo and processed ex vivo. Here we stented the coronary arteries of ex vivo porcine hearts, performed vascular corrosion casting, acquired the vessel geometry using micro-computed tomography and reconstructed blood flow and shear stress using computational fluid dynamics. The method yields accurate local flow information through anatomic fidelity, capturing in detail the stent geometry, arterial tissue prolapse, radial and axial arterial deformation as well as strut malapposition. This novel compound method may serve as a unique tool for spatially resolved analysis of the relationship between hemodynamic factors and vascular biology. It can further be employed to optimize stent design and stenting strategies.

Sequential Structural and Fluid Dynamics Analysis of Balloon-Expandable Coronary Stents: A Multivariable Statistical Analysis

“…These computational methods of analysis employ sophisticated numerical techniques, such as the finite element and finite volume methods, to obtain approximate numerical solutions to complex physical problems. To date, a large number of studies have carried out computational structural (CS) analyses 1,4,5,14,15,19,[25][26][27][28][29]37,44,53,54,57,59,[62][63][64]72,73,78,80,85,87,[90][91][92] and computational fluid dynamics (CFD) analyses 3,8,9,12,30,31,33,42,[47][48][49][50][51]65,66,69,[74][75][76]83,89 ...…”

Optimized Computer-Aided Segmentation and Three-Dimensional Reconstruction Using Intracoronary Optical Coherence Tomography

“…The shear-thinning behavior of blood was considered modeling it as a non-Newtonian fluid with density of 1060 kg / m 3 and shear dependent dynamic viscosity following the Carreau model [30], [31]: $$\frac{\mu -{\mu }_{\infty }}{{\mu }_O-{\mu }_{\infty }}={[1+{(\lambda ·\stackrel{.}{\gamma })}^2]}^{(n-1)/2},$$ where γ̇ is the shear rate, μ O = 0.25 kg / m.s and μ ∞ = 0.0035 kg / m.s are the blood viscosities at infinite and zero shear rates, and λ = 25 s and n =0.25 values are Carreau parameters [32]. Volumetric flow rate at the inlet was set to 0.95 mL / s [33] while the outlet boundary was extended (to minimize the numerical noise of boundary condition) and set to zero pressure. Sensitivity analysis was performed on the boundary conditions by considering ±10 % and ±20 % change in the inlet mass flow and showed no significant change in the acquired results.…”

Drug deposition in coronary arteries with overlapping drug-eluting stents

“…No slip boundary conditions were set at the stent wall, while on the vessel wall the transmural velocity of plasma was applied in the normal direction according to the pre-calculated luminal pressure distribution and resistance of the tissue excluding endothelial resistance as explained in [36, 37]. Murray’s law was applied at the outlets, to where the outlet with the largest diameter was set to 70 mmHg relative pressure, and the remaining outlets were assigned outflow rates according to their cross-sectional area [32, 38]. Drug transport inside the lumen was determined by the advection-diffusion equation $$\overrightarrow{V_l}․\nabla C_l=D_l․{\nabla }^2{C}_l$$ where C l is the drug concentration within the fluid domain and D l denotes the diffusivity of the drug.…”

“…Following a methodology we have developed and previously described in detail [32], we resolve the precise three dimensional geometry of stented arteries from microscale computed tomography data, ensuring high geometric fidelity both at the whole stent as well as at the individual strut scale. In conjunction with computational modeling, this allows prediction of drug distribution and deposition in anatomically accurate arteries under physiologic and pathophysiologic flow conditions.…”