The arteriovenous fistula (AVF) is the main form of vascular access for hemodialysis patients, but its maintenance is very challenging. Its failure is mainly related to intimal hyperplasia (IH), leading to stenosis. The aim of this work was twofold: (i) to perform a computational study for the comparison of the disturbed blood dynamics in different configurations of AVF and (ii) to assess the amount of transition to turbulence developed by the specific geometric configuration of AVF. For this aim, we reconstructed realistic three-dimensional (3D) geometries of two patients with a side-to-end AVF, performing a parametric study by changing the angle of incidence at the anastomosis. We solved the incompressible Navier–Stokes equations modeling the blood as an incompressible and Newtonian fluid. Large eddy simulations (LES) were considered to capture the transition to turbulence developed at the anastomosis. The values of prescribed boundary conditions are obtained from clinical echo-color Doppler (ECD) measurements. To assess the disturbed flow, we considered hemodynamic quantities such as the velocity field, the pressure distribution, and wall shear stresses (WSS) derived quantities, whereas to quantify the transition to turbulence, we computed the standard deviation of the velocity field among different heartbeats and the turbulent kinetic energy.
This work dealt with the assessment of a computational tool to estimate the electrical activation in the left ventricle focusing on the latest electrically activated segment (LEAS) in patients with left bundle branch block and possible myocardial fibrosis. We considered the Eikonal-diffusion equation and to recover the electrical activation maps in the myocardium. The model was calibrated by using activation times acquired in the coronary sinus (CS) branches or in the CS solely with an electroanatomic mapping system (EAMS) during cardiac resynchronization therapy (CRT). We applied our computational tool to ten patients founding an excellent accordance with EAMS measures; in particular, the error for LEAS location was less than 4 mm. We also calibrated our model using only information in the CS, still obtaining an excellent agreement with the measured LEAS. The proposed tool was able to accurately reproduce the electrical activation maps and in particular LEAS location in the CS branches, with an almost real-time computational effort, regardless of the presence of myocardial fibrosis, even when information only at CS was used to calibrate the model. This could be useful in the clinical practice since LEAS is often used as a target site for the left lead placement during CRT.
Graphical abstract
Overall picture of the computational pipeline for the estimation of LEAS
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