Computational Fluid Dynamics Study of Cerebral Thromboembolism Risk in Ventricular Assist Device Patients: Effects of Pulsatility and Thrombus Origin

Purpose: This study investigates the hypothesis that by surgically manipulating the outflow graft implantation during ventricle assist device placement, it may be possible to reduce the risk of cerebral embolism. Methods: We investigate this hypothesis using a computational approach on a patient specific basis under fully-pulsatile hemodynamics with a multi-scale computational fluid dynamics model incorporating a coupled Eulerian-Lagrangian scheme that effectively tracks emboli in the fluid domain. Blood is modeled as a non-Newtonian fluid based on the hematocrit level. Results: Preliminary flow analysis shows that, depending on the anastomosis angle the LVAD can enhance the flow to the cerebral circulation by nearly 31%. Z-test results suggest that unsteady flow modelling ought to be an integral part of any cardiovascular simulation with residual ventricular function. Assuming unsteady flow conditions, a shallow LVAD outflow graft anastomosis angle is the most optimal if thrombi are released from the aortic root reducing cerebral embolization incidence to 15.5% and from the ventricle to 17%, while a more pronounced anastomosis angle becomes advantageous when particles originate from the LVAD with an embolization rate of 16.9%. Conclusion: Overall, computations suggest that a pronounced LVAD anastomosis angle is the better implementation. Unsteady modeling is shown to be necessary in the presence of significant antegrade aortic root flow which induces cyclical flow patterns due to residual pulsatility. On the other hand depending on thrombus origin and VAD anastomosis angle there is a strong tradeoff in embolization rates.

Non-linearity of end-systolic pressure–volume relation in afterload increases is caused by an overlay of shortening deactivation and the Frank–Starling mechanism

The linearity and load insensitivity of the end-systolic pressure–volume-relationship (ESPVR), a parameter that describes the ventricular contractile state, are controversial. We hypothesize that linearity is influenced by a variable overlay of the intrinsic mechanism of autoregulation to afterload (shortening deactivation) and preload (Frank-Starling mechanism). To study the effect of different short-term loading alterations on the shape of the ESPVR, experiments on twenty-four healthy pigs were executed. Preload reductions, afterload increases and preload reductions while the afterload level was increased were performed. The ESPVR was described either by a linear or a bilinear regression through the end-systolic pressure volume (ES-PV) points. Increases in afterload caused a biphasic course of the ES-PV points, which led to a better fit of the bilinear ESPVRs (r2 0.929 linear ESPVR vs. r2 0.96 and 0.943 bilinear ESPVR). ES-PV points of a preload reduction on a normal and augmented afterload level could be well described by a linear regression (r2 0.974 linear ESPVR vs. r2 0.976 and 0.975 bilinear ESPVR). The intercept of the second ESPVR (V0) but not the slope demonstrated a significant linear correlation with the reached afterload level (effective arterial elastance Ea). Thus, the early response to load could be described by the fixed slope of the ESPVR and variable V0, which was determined by the actual afterload. The ESPVR is only apparently nonlinear, as its course over several heartbeats was affected by an overlay of SDA and FSM. These findings could be easily transferred to cardiovascular simulation models to improve their accuracy.

An Approximation of Heart Failure Using Cardiovascular Simulation Toolbox

In this paper, we present the simulation of 5 different heart failures with the help of the Cardiovascular Simulation Toolbox (CVST) proposed by O. Barnea et al. at Tel-Aviv University. This is a modified version of the CVST, proposed by G.Ortiz; here, we show that the pathological failures can be covered by this tool. We varied the value of the tool blocks, included the results of the hemodynamic parameters and the P-V loop curves for each disease and compared them to the medical data to prove the effectiveness of the simulation. Based on these changes, we achieved an effective simulation of the following heart failures in the CVST: Diastolic Heart Failure (DHF), Systolic Heart Failure (SHF), Right Ventricle Heart Failure (RVHF), Low Output Heart Failure (LOHF) and High Output Heart Failure (HOHF).