Comparison between a generalized Newtonian model and a network-type multiscale model for hemodynamic behavior in the aortic arch: Validation with 4D MRI data for a case study

Impact of wall displacements on the large-scale flow coherence in ascending aorta

In the context of aortic hemodynamics, uncertainties affecting blood flow simulations hamper their translational potential as supportive technology in clinics. Computational fluid dynamics (CFD) simulations under rigid-walls assumption are largely adopted, even though the aorta contributes markedly to the systemic compliance and is characterized by a complex motion. To account for personalized wall displacements in aortic hemodynamics simulations, the moving-boundary method (MBM) has been recently proposed as a computationally convenient strategy, although its implementation requires dynamic imaging acquisitions not always available in clinics. In this study we aim to clarify the real need for introducing aortic wall displacements in CFD simulations to accurately capture the large-scale flow structures in the healthy human ascending aorta (AAo). To do that, the impact of wall displacements is analyzed using subject-specific models where two CFD simulations are performed imposing (1) rigid walls, and (2) personalized wall displacements adopting a MBM, integrating dynamic CT imaging and a mesh morphing technique based on radial basis functions. The impact of wall displacements on AAo hemodynamics is analyzed in terms of large-scale flow patterns of physiological significance, namely axial blood flow coherence (quantified applying the Complex Networks theory), secondary flows, helical flow and wall shear stress (WSS). From the comparison with rigid-wall simulations, it emerges that wall displacements have a minor impact on the AAo large-scale axial flow, but they can affect secondary flows and WSS directional changes. Overall, helical flow topology is moderately affected by aortic wall displacements, whereas helicity intensity remains almost unchanged. We conclude that CFD simulations with rigid-wall assumption can be a valid approach to study large-scale aortic flows of physiological significance.

Numerical investigation of different viscosity models on pulsatile blood flow of thoracic aortic aneurysm (TAA) in a patient-specific model

Aortic aneurysm is one of the most common aortic diseases that can lead to unfortunate consequences. Numerical simulations have an important role in the prediction of the aftereffects of vascular diseases including aneurysm. In this research, numerical simulation of pulsatile blood flow is performed for a 3-dimensional patient-specific model of a thoracic aortic aneurysm (TAA). Since the choice of blood viscosity model may have a significant impact on the simulation results, the effects of four non-Newtonian models of blood viscosity namely Carreau, Casson, Herschel-Bulkley, power low, and the Newtonian model on the wall shear stress (WSS) distribution, shear rate, and oscillatory shear index (OSI) have been analyzed. Simulation results showed that all the non-Newtonian and Newtonian models generally, predict similar patterns for blood flow and shear rate. At high flow rates in the cardiac cycle, the WSS value for all the models are similar to each other except for the power-law model due to the shear thinning behavior. All models predict high values of OSI on the inner wall of the ascending aorta and broad areas of the inner wall of the aneurysm sac. However, the Newtonian model predicts the OSI less than the non-Newtonian models in some areas of the aneurysm sac. Results indicated that the Newtonian model generally can predict the hemodynamic parameters of the blood flow similar to the non-Newtonian but for more precise analysis and to predict the regions prone to rupture and atherosclerosis, choosing a proper non-Newtonian model is recommended.

Semi-Automatic Planning and Three-Dimensional Electrospinning of Patient-Specific Grafts for Fontan Surgery

This paper proposes a semi-automatic Fontan surgery planning method for designing and manufacturing hemodynamically optimized patient-specific grafts. Fontan surgery is a palliative procedure for patients with a single ventricle heart defect by creating a new path using a vascular graft for the deoxygenated blood to be directed to the lungs, bypassing the heart. However, designing patient-specific grafts with optimized hemodynamic performance is a complex task due to the variety of patient-specific anatomies, confined surgical planning space, and the requirement of simultaneously considering multiple design criteria for vascular graft optimization. To address these challenges, we used parameterized Fontan pathways to explore patient-specific vascular graft design spaces and search for optimal solutions by formulating a nonlinear constrained optimization problem, which minimizes indexed power loss (iPL) of the Fontan model by constraining hepatic flow distribution (HFD), percentage of abnormal wall shear stress (%WSS) and geometric interference between Fontan pathways and the heart models (InDep) within clinically acceptable thresholds. Gaussian process regression was employed to build surrogate models of the hemodynamic parameters as well as InDep and [Formula: see text] (conduit model smoothness indicator) for optimization by pattern search. We tested the proposed method on two patient-specific models (n=2). The results showed the automatically optimized (AutoOpt) Fontan models hemodynamically outperformed or at least are comparable to manually optimized Fontan models with significantly reduced surgical planning time (15 hours versus over 2 weeks). We also demonstrated feasibility of manufacturing the AutoOpt Fontan conduits by using electrospun nanofibers.

A parametric model for studying the aorta hemodynamics by means of the computational fluid dynamics

Perturbed aorta hemodynamics, as for the carotid and the coronary artery, has been identified as potential predicting factor for cardiovascular diseases. In this study, we propose a parametric study based on the computational fluid dynamics with the aim of providing information regarding aortic disease. In particular, the blood flow inside a parametrized aortic arch is computed as a function of morphological changes of baseline aorta geometry. Flow patterns, wall shear stress, time average wall shear stress and oscillatory shear index were calculated during the cardiac cycle. The influence of geometrical changes on the hemodynamics and on these variables was evaluated. The results suggest that the distance between inflow and aortic arch and the angle between aortic arch and descending trunk are the most influencing parameters regarding the WSS-related indices while the effect of the inlet diameter seems limited. In particular, an increase of the aforementioned distance produces a reduction of the spatial distribution of the higher values of the time average wall shear stress and of the oscillatory shear index independently on the other two parameters while an increase of the angle produce an opposite effect. Moreover, as expected, the analysis of the wall shear stress descriptors suggests that the inlet diameter influences only the flow intensity. As conclusion, the proposed parametric study can be used to evaluate the aorta hemodynamics and could be also applied in the future, for analyzing pathological cases and virtual situations, such as pre- and/or post-operative cardiovascular surgical states that present enhanced changes in the aorta morphology yet promoting important variations on the considered indexes.

Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries?

Patient-specific computational fluid dynamics (CFD) is a promising tool that provides highly resolved haemodynamics information. The choice of blood rheology is an assumption in CFD models that has been subject to extensive debate. Blood is known to exhibit shear-thinning behaviour, and non-Newtonian modelling has been recommended for aneurysmal flows. Current non-Newtonian models ignore rouleaux formation, which is the key player in blood's shear-thinning behaviour. Experimental data suggest that red blood cell aggregation and rouleaux formation require notable red blood cell residence-time (RT) in a low shear rate regime. This study proposes a novel hybrid Newtonian and non-Newtonian rheology model where the shear-thinning behaviour is activated in high RT regions based on experimental data. Image-based abdominal aortic and cerebral aneurysm models are considered and highly resolved CFD simulations are performed using a minimally dissipative solver. Lagrangian particle tracking is used to define a backward particle RT measure and detect stagnant regions with increased rouleaux formation likelihood. Our novel RT-based non-Newtonian model shows a significant reduction in shear-thinning effects and provides haemodynamic results qualitatively identical and quantitatively close to the Newtonian model. Our results have important implications in patient-specific CFD modelling and suggest that non-Newtonian models should be revisited in large artery flows.