Computational Model Of Blood Flow Research Articles

Multi-scale Modelling of Shear Stress on the Syncytiotrophoblast: Could Maternal Blood Flow Impact Placental Function Across Gestation?

The placenta is a critical fetal exchange organ, with a complex branching tree-like structure. Its surface is covered by a single multinucleated cell, the syncytiotrophoblast, which bathes in maternal blood for most of pregnancy. Mechanosensing protein expression by the syncytiotrophoblast at term suggests that shear stress exerted by maternal blood flow may modulate placental development and function. However, it is not known how the mechanosensitive capacity of the syncytiotrophoblast, or the shear stress it experiences, change across gestation. Here, we show that the syncytiotrophoblast expresses both mechanosensitive ion channels (Piezo 1, Polycystin 2, TRPV6) and motor proteins associated with primary cilia (Dynein 1, IFT88, Kinesin 2), with higher staining for all these proteins seen in late first trimester placentae than at term. MicroCT imaging of placental tissue was then used to inform computational models of blood flow at the placentone scale (using a porous media model), and at the villous scale (using explicit flow simulations). These two models are then linked to produce a combined model that allows the variation of shear stress across both these scales simultaneously. This combined model predicts that the range of shear stress on the syncytiotrophoblast is higher in the first-trimester than at term (0.8 dyne/cm2 median stress compared to 0.04 dyne/cm2) when considering both these scales. Together, this suggests that the nature of blood flow through the intervillous space, and the resulting shear stress on the syncytiotrophoblast have important influences on placental morphogenesis and function from early in pregnancy.

In silico modeling for the hepatic circulation and transport: From the liver organ to lobules.

The function of the liver depends critically on its blood supply. Numerous in silico models have been developed to study various aspects of the hepatic circulation, including not only the macro-hemodynamics at the organ level, but also the microcirculation at the lobular level. In addition, computational models of blood flow and bile flow have been used to study the transport, metabolism, and clearance of drugs in pharmacokinetic studies. These in silico models aim to provide insights into the liver organ function under both healthy and diseased states, and to assist quantitative analysis for surgical planning and postsurgery treatment. The purpose of this review is to provide an update on state-of-the-art in silico models of the hepatic circulation and transport processes. We introduce the numerical methods and the physiological background of these models. We also discuss multiscale frameworks that have been proposed for the liver, and their linkage with the large context of systems biology, systems pharmacology, and the Physiome project. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering Cardiovascular Diseases > Computational Models.

A computational study of red blood cell deformability effect on hemodynamic alteration in capillary vessel networks

Capillary blood vessels, the smallest vessels in the body, form an intricate network with constantly bifurcating, merging and winding vessels. Red blood cells (RBCs) must navigate through such complex microvascular networks in order to maintain tissue perfusion and oxygenation. Normal, healthy RBCs are extremely deformable and able to easily flow through narrow vessels. However, RBC deformability is reduced in many pathological conditions and during blood storage. The influence of reduced cell deformability on microvascular hemodynamics is not well established. Here we use a high-fidelity, 3D computational model of blood flow that retains exact geometric details of physiologically realistic microvascular networks, and deformation of every one of nearly a thousand RBCs flowing through the networks. We predict that reduced RBC deformability alters RBC trafficking with significant and heterogeneous changes in hematocrit. We quantify such changes along with RBC partitioning and lingering at vascular bifurcations, perfusion and vascular resistance, and wall shear stress. We elucidate the cellular-scale mechanisms that cause such changes. We show that such changes arise primarily due to the altered RBC dynamics at vascular bifurcations, as well as cross-stream migration. Less deformable cells tend to linger less at majority of bifurcations increasing the fraction of RBCs entering the higher flow branches. Changes in vascular resistance also seen to be heterogeneous and correlate with hematocrit changes. Furthermore, alteration in RBC dynamics is shown to cause localized changes in wall shear stress within vessels and near vascular bifurcations. Such heterogeneous and focal changes in hemodynamics may be the cause of morphological abnormalities in capillary vessel networks as observed in several diseases.

Capillary module haemodynamics and mechanisms of blood flow regulation in skeletal muscle capillary networks: Experimental and computational analysis.

The capillary module (CM), consisting of parallel capillaries from terminal arteriole to post-capillary venule, is classically considered to be the building block of complex capillary networks. In skeletal muscle, CMs form interconnected columns spanning thousands of microns, which we recently described as the capillary fascicle. However, detailed evaluation of CM haemodynamics has not been described, and may provide insight into mechanisms of blood flow regulation in the microcirculation. We used intravital videomicroscopy from resting extensor digitorum longus muscle in rats (n=9 networks, 112 capillary modules), as well as dual-phase computational modelling of blood flow in simulated CM geometries. We found that the mean driving pressure across CMs was 3.236±1.833mmHg. Red blood cell (RBC) flow was independent of CM resistance, and the ratio of blood flow in adjacent modules was not correlated with their ratio of resistances. In simulated CM geometries, increases to driving pressure produced a direct linear increase to RBC and plasma flow, with no changes to RBC distribution; increases to arteriolar inflow haematocrit resulted in increased RBC flow, but with viscosity-dependent increases to CM resistance. CM RBC flow heterogeneity was higher than plasma flow heterogeneity in experimental data, in contrast to simulated geometries, suggesting that time-dependent flow variability may have important consequences for RBC distribution. In summary, these findings suggest that CMs are active participants in microvascular flow regulation, likely achieved through adjustments to CM driving pressure using pre- and post-capillary loci of flow control. Increases to CM viscosity may be important during the regulation of functional hyperaemia. KEY POINTS: The capillary module (CM), consisting of parallel capillaries from the arteriole to venule, is classically considered to be the building block of capillary networks in skeletal muscle. A detailed evaluation of module haemodynamics may provide insight into mechanisms of blood flow regulation in the microcirculation. Using experimental data from resting skeletal muscle in rats, as well as dual-phase computational models of blood flow, we analysed haemodynamic relationships and the impact of variations to boundary conditions on red blood cell and plasma distribution. We showed that driving pressure across CMs is low, and that simulated increases to inflow haematocrit have important viscosity-dependent effects on module resistance. We found that red blood cell flow was independent from module resistance, which strongly suggests the regulation of driving pressure at the level of the capillary module using pre- and post-capillary loci of flow control. These findings place CMs as central participants in microvascular flow regulation, with important consequences for disease and functional hyperaemia.

Computational investigation of blood cell transport in retinal microaneurysms.

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). MA leakage or rupture may precipitate local pathology in the surrounding neural retina that impacts visual function. Thrombosis in MAs may affect their turnover time, an indicator associated with visual and anatomic outcomes in the diabetic eyes. In this work, we perform computational modeling of blood flow in microchannels containing various MAs to investigate the pathologies of MAs in DR. The particle-based model employed in this study can explicitly represent red blood cells (RBCs) and platelets as well as their interaction in the blood flow, a process that is very difficult to observe in vivo. Our simulations illustrate that while the main blood flow from the parent vessels can perfuse the entire lumen of MAs with small body-to-neck ratio (BNR), it can only perfuse part of the lumen in MAs with large BNR, particularly at a low hematocrit level, leading to possible hypoxic conditions inside MAs. We also quantify the impacts of the size of MAs, blood flow velocity, hematocrit and RBC stiffness and adhesion on the likelihood of platelets entering MAs as well as their residence time inside, two factors that are thought to be associated with thrombus formation in MAs. Our results show that enlarged MA size, increased blood velocity and hematocrit in the parent vessel of MAs as well as the RBC-RBC adhesion promote the migration of platelets into MAs and also prolong their residence time, thereby increasing the propensity of thrombosis within MAs. Overall, our work suggests that computational simulations using particle-based models can help to understand the microvascular pathology pertaining to MAs in DR and provide insights to stimulate and steer new experimental and computational studies in this area.

Two-scale haemodynamic modelling for patients with Fontan circulation

Abstract Palliation of congenital single ventricle heart defects suggests multi-stage surgical interventions that divert blood flow from the inferior and superior vena cava directly to the right and left pulmonary arteries, skipping the right ventricle. Such system with cavopulmonary anastomoses and single left ventricle is called Fontan circulation, and the region of reconnection is called the total cavopulmonary connection (TCPC). Computational blood flow models allow clinicians to predict the results of the Fontan operation, to choose an optimal configuration of TCPC and thus to reduce negative postoperative consequences. We propose a two-scale (1D3D) haemodynamic model of systemic circulation for a patient who has underwent Fontan surgical operation. We use CT and 4D flow MRI data to personalize the model. The model is tuned to patient’s data and is able to represent measured time-averaged flow rates at the inlets and outlets of TCPC, as well as pressure in TCPC for the patient in horizontal position.We demonstrate that changing to quiescent standing position leads to other patterns of blood flow in regional (TCPC) and global haemodynamics. This confirms clinical data on exercise intolerance of Fontan patients.

Multiscale modeling of blood flow to assess neurological complications in patients supported by venoarterial extracorporeal membrane oxygenation

Computational blood flow models in large arteries elucidate valuable relationships between cardiovascular diseases and hemodynamics, leading to improvements in treatment planning and clinical decision making. One such application with potential to benefit from simulation is venoarterial extracorporeal membrane oxygenation (VA-ECMO), a support system for patients with cardiopulmonary failure. VA-ECMO patients develop high rates of neurological complications, partially due to abnormal blood flow throughout the vasculature from the VA-ECMO system. To better understand these hemodynamic changes, it is important to resolve complex local flow parameters derived from three-dimensional (3D) fluid dynamics while also capturing the impact of VA-ECMO support throughout the systemic arterial system. As high-resolution 3D simulations of the arterial network remain computationally expensive and intractable for large studies, a validated, multiscale model is needed to compute both global effects and high-fidelity local hemodynamics. In this work, we developed and demonstrated a framework to model hemodynamics in VA-ECMO patients using coupled 3D and one-dimensional (1D) models (1D→3D). We demonstrated the ability of these multiscale models to simulate complex flow patterns in specific regions of interest while capturing bulk flow throughout the systemic arterial system. We compared 1D, 3D, and 1D→3D coupled models and found that multiscale models were able to sufficiently capture both global and local hemodynamics in the cerebral arteries and aorta in VA-ECMO patients. This study is the first to develop and compare 1D, 3D, and 1D→ 3D coupled models on the larger arterial system scale in VA-ECMO patients, with potential use for other large scale applications.

Red Blood Cell‐resolved 3D Computational Modeling of Blood Flow in Physiologically Realistic Microvascular Networks

Microvascular networks represent geometrically complex architecture due to constantly bifurcating and merging vessels. Moreover, blood vessels are not necessarily straight, and often highly winding. Mathematical models of blood flow in such networks have treated these vessels as 1D straight segments neglecting the geometric complexity and details. These models also do not consider the deformation and flow of individual red blood cell, and instead use empirical relations to prescribe blood viscosity and red blood cell distribution at a vascular bifurcation. As such, these models cannot predict hemodynamic variations over short time and length scales. To overcome this limitation, we have recently developed a high‐fidelity 3D, first‐principle based, fluid‐‐structure interaction model of blood flow in physiologically realistic microvascular networks. The model retains the exact geometric details of the vasculature, e.g., 3D nature of the blood vessels and bifurcations, and vessel curvature. Deformation and flow of each individual red blood cell as they flow through the vessels are exactly modeled. The model is based on the minimal assumptions: it does not assume any empirical viscosity law or bifurcation law; rather, these laws are predicted by the model. The model provides microscale details of hemodynamic quantities that are not readily available in experiments, and cannot be predicted by the traditional 1D network models, such as wall shear stress gradient and time‐dependent red blood cell partitioning at bifurcations.Of particular interest is the role of red blood cell deformability on hematocrit distribution in the networks. Cell deformability is known to reduce in many diseases, such as sickle cell disease, malaria and diabetes. By using in vivo images of retinal microvasculature, we have performed simulation of network blood flow under varying cell deformability in such networks. The model shows that altered cell deformability significantly changes the cell distribution in the network, and subsequently the flow resistance in vessels. While some vessels show a significant increase in hematocrit, some show a significant decrease. Such a redistribution of hematocrit for diseased red blood cells may have a significant impact on tissue oxygen delivery. The simulation results are used to mechanistically explain the observed redistribution of hematocrit and vascular resistance.Support or Funding InformationFunded by NSF

Predictive Models of Coronary Artery Disease Based on Computational Modeling: The SMARTool System.

SMARTool aims to the development of Decision Support Systems (DSS) for the risk stratification, diagnosis, prediction and treatment of coronary artery disease (CAD). In this work, we present the results of the prediction DSS, which utilizes clinical data, imaging morphological characteristics and computational modeling results. More specifically, 263 patients were recruited in the SMARTool clinical trial and 196 patients were selected for the DSS development. Traditional risk factors, blood examinations and computed coronary tomography angiography (CCTA) were performed at two different time points with an interscan period 6.22 ± 1.42 years. Computational modeling of blood flow and LDL transport was performed at the baseline. Predictive models are built for the prediction of CAD at the follow-up. The results show that CAD can be predicted with 83% accuracy, when low ESS, high accumulation of LDL and imaging data are included in the model.

Three-dimensional distribution of wall shear stress and its gradient in red cell-resolved computational modeling of blood flow in invivo-like microvascular networks.

Using a high‐fidelity, 3D computational model of blood flow in microvascular networks, we provide the full 3D distribution of wall shear stress (WSS), and its gradient (WSSG), and quantify the influence of red blood cells (RBCs) on WSS and WSSG. The deformation and flow dynamics of the individual RBCs are accurately resolved in the model, while physiologically realistic microvascular networks comprised of multiple bifurcations, convergences, and tortuous vessels are considered. A strong heterogeneity in WSS and WSSG is predicted across the networks, with the highest WSS occurring in precapillary bifurcations and capillary vessels. 3D variations of WSS and WSSG are shown to occur due to both network morphology and the influence of RBCs. The RBCs increase the WSS by as much as three times compared to that when no RBCs are present, and the highest increase is observed in venules. WSSG also increases significantly, and high WSSGs occur over wider regions in the presence of RBCs. In most vessels, the circumferential component of WSSG is observed to be greater than the axial component in the presence of RBCs, while the opposite trend is observed when RBCs are not considered. These results underscore the important role of RBCs on WSS and WSSG that cannot be predicted by widely used 1D models of network blood flow. Furthermore, the subendothelium‐scale variations of WSS and WSSG predicted by the present model have implications in terms of endothelial cell functions in the microvasculature.

Importance of incorporating systemic cerebroarterial hemodynamics into computational modeling of blood flow in intracranial aneurysm

The importance of properly treating boundary conditions (BCs) in numerical simulation of hemodynamics in intracranial aneurysm (IA) has been increasingly recognized. In this study, we constructed three types of computational model for each IA to investigate how the outcome of numerical simulation is affected by the treatment of BCs. The first type of model (i.e., Type-A model) was obtained by applying 3-D hemodynamic modeling to the entire cerebral arterial network, with its solution being taken as the reference for evaluating the performance of the other two types of model (i.e., Type-B and Type-C models) in which 3-D modeling was confined to the aneurysm region. In addition, patient-specific 1-D models of the cerebral arterial network were developed to provide hemodynamic information for setting the inflow/outflow BCs of the 3-D models. Numerical tests on three IAs revealed that prescribing the outflow BCs of a localized 3-D aneurysm model based on 1-D model-simulated outflow division (i.e., Type-B model) instead of imposing the free outflow BC on all outlets (i.e., Type-C model) helped to improve the fidelity of the simulation of intra-aneurysmal hemodynamics, but could not guarantee a complete reproduction of the reference solution obtained by the Type-A model. Moreover, it was found that the outcome of hemodynamic simulation was more sensitive to the treatment of BCs when an aneurysm was located at arterial bifurcation rather than sidewall. These findings highlight the importance of taking into account systemic cerebroarterial hemodynamics in computational modeling of hemodynamics in IAs, especially those located at bifurcations.

A critical comparison of different residence time measures in aneurysms

Flow stagnation and residence time (RT) are important features of diseased arterial flows that influence biochemical transport processes and thrombosis. RT calculation methods are classified into Eulerian and Lagrangian approaches where several measures have been proposed to quantify RT. Each of these methods has a different definition of RT, and it is not clear how they are related. In this study, image-based computational models of blood flow in an abdominal aortic aneurysm and a cerebral aneurysm were considered and RT was calculated using different methods. In the Lagrangian methods, discrete particle tracking of massless tracers was used to calculate particle residence time and mean exposure time. In the Eulerian methods, continuum transport models were used to quantify RT using Eulerian RT and virtual ink approaches. Point-wise RT and Eulerian indicator RT were also computed based on measures derived from velocity. A comparison of these methods is presented and the implications of each method are discussed. Our results highlight that most RT methods have a conceptually distinct definition of RT and therefore should be utilized depending on the specific application of interest.

A computational modeling of blood flow in asymmetrically bifurcating microvessels and its experimental validation.

Microvascular transport is complex due to its heterogeneity. Many researchers have been developing mathematical and computational models in predicting microvascular geometries and blood transport. However, previous works were focused on developing simulation models, not on validating suggested models with microvascular geometry and blood flow in the real microvasculature. In this paper, we suggest a computational model for microvascular transport with experimental validation in its geometry and blood flow. The geometry is generated by controlling asymmetric conditions of microvascular network. Also, the blood flow in microvascular networks is predicted by considering in vivo viscosity, Poiseuille flow model, and hematocrit redistribution by plasma skimming. The suggested model is validated by the measured data in rat mesentery. Also, the microvascular transport in a case of mouse cortex is predicted and compared against experimental data to check applicability of the suggested model.

Association of Placental Jets and Mega-Jets With Reduced Villous Density

Spiral arteries (SAs) lie at the interface between the uterus and placenta, and supply nutrients to the placental surface. Maternal blood circulation is separated from the fetal circulation by structures called villous trees. SAs are transformed in early pregnancy from tightly coiled vessels to large high-capacity channels, which is believed to facilitate an increased maternal blood flow throughout pregnancy with minimal increase in velocity, preventing damage to delicate villous trees. Significant maternal blood flow velocities have been theorized in the space surrounding the villi (the intervillous space, IVS), particularly when SA conversion is inadequate, but have only recently been visualized reliably using pulsed wave Doppler ultrasonography. Here, we present a computational model of blood flow from SA openings, allowing prediction of IVS properties based on jet length. We show that jets of flow observed by ultrasound are likely correlated with increased IVS porosity near the SA mouth and propose that observed mega-jets (flow penetrating more than half the placental thickness) are only possible when SAs open to regions of the placenta with very sparse villous structures. We postulate that IVS tissue density must decrease at the SA mouth through gestation, supporting the hypothesis that blood flow from SAs influences villous tree development.

A head-to-head comparison between CT- and IVUS-derived coronary blood flow models

The goal of this work is to compare coronary hemodynamics as predicted by computational blood flow models derived from two imaging modalities: coronary computed tomography angiography (CCTA) and intravascular ultrasound integrated with angiography (IVUS). Criteria to define boundary conditions are proposed to overcome the dissimilar anatomical definition delivered by both modalities. The strategy to define boundary conditions is novel in the present context, and naturally accounts for the flow redistribution induced by the resistance of coronary vessels. Hyperemic conditions are assumed to assess model predictions under stressed hemodynamic environments similar to those encountered in Fractional Flow Reserve (FFR) calculations. As results, it was found that CCTA models predict larger pressure drops, higher average blood velocity and smaller FFR. Concerning the flow rate at distal locations in the major vessels of interest, it was found that CCTA predicted smaller flow than IVUS, which is a consequence of a larger sensitivity of CCTA models to coronary steal phenomena. Comparisons to in-vivo measurements of FFR are shown.

3D Simulations of Blood Flow Dynamics in Compliant Vessels: Normal, Aneurysmal, and Stenotic Arteries

AbstractArterial diseases such as aneurysm and stenosis may result from the mechanical and/or morphological change of an arterial wall structure and correspondingly altered hemodynamics. The development of a 3D computational model of blood flow can be useful to study the hemodynamics in major blood vessels and may provide an insight into the noninvasive technique to detect arterial diseases in early stage. In this paper, we present a three-dimensional model of blood flow in the aorta, which is based on the immersed boundary method to describe the interaction of blood flow with the aortic wall. Our simulation results show that the hysteresis loop is evident in the pressure-diameter relationship of the normal aorta when the arterial wall is considered to be viscoelastic. In addition, it is shown that flow patterns and pressure distributions are altered in response to the change of aortic morphology.

Fluid-Structure Interaction Analysis for Drug Transport in a Curved Stenotic Right Coronary Artery

A blockage of blood vessels resulting from thrombus or plaque deposit causes serious cardiovascular diseases. This study developed a computational model of blood flow and drug transport to investigate the effectiveness of drug delivery to the stenotic sites. A three-dimensional (3D) model of the curved stenotic right coronary artery (RCA) was reconstructed based on the clinical angiogram image. Then, blood flow and drug transport with the flexible RCA wall were simulated using the fluid structure interaction (FSI) analysis and compared with the rigid RCA wall. Results showed that the maximal total displacement and von Mises stress of the flexible RCA model are 2.14 mm and 92.06 kPa. In addition, the effective injecting time point for the best performance of drug delivery was found to be between 0 s and 0.15 s (i.e., the fluid acceleration region) for both rigid and flexible RCA models. However, there was no notable difference in the ratio of particle deposition to the stenotic areas between the rigid and flexible RCA models. This study will be significantly useful to the design of a drug delivery system for the treatment of the stenotic arteries by targeting drugs selectively to the stenotic sites.

COMPUTATIONAL FLUID DYNAMICS MODELS OF HEALTHY AND FAILING FONTAN CIRCULATIONS

Failing Fontan circulation is a clinical diagnosis and can be characterized by elevated Fontan pressures and reduced cardiac output. For many of these patients, heart transplant is the only viable treatment option, and there are currently no minimally invasive medical devices available to bridge these patients to transplant. The goal of our study is to design, build, and test such a device. As a first step in the design process, we have developed representative computational models of blood flow in the total cavopulmonary connection (TCPC) in both healthy and failing Fontan cases, which are described in this abstract. Measurements made from angiograms of paediatric Fontan patients were used to develop an average three-dimensional computational model of the TCPC. Computational fluid dynamics simulations were performed in ANSYS Fluent (ANSYS, Inc., Canonsburg, PA, USA) for both healthy and failing Fontan circulations. Representative boundary conditions were defined for our model at the superior vena cava and extracardiac conduit (inlets) and the left and right pulmonary arteries (outlets) based on data from our patient cohort. At the inlets, we specified flow rates based on cardiac outputs of 1.8 L/min for the healthy case and 0.94 L/min for the failing case and a 65%/35% flow split between the extracardiac conduit and the superior vena cava. At the outlets, we specified pressures of 11 mm Hg for the healthy case and 18 mm Hg for the failing case. Results for healthy and failing Fontan circulations are presented in Figure 1 as streamlines of the blood flow through the TCPC. As expected, the velocities were higher in the healthy case than in the failing case, and the pressures (not shown) were lower in the healthy case than in the failing case. We have successfully developed a computational model to predict the blood flow in the TCPC for both healthy and failing Fontan circulations. Our calculated pressures and flow rates were consistent with expected values and fit within relevant physiological ranges. These models are a first step in the design process to develop a medical device for short-term minimally-invasive treatment for failing Fontan circulation as a bridge to heart transplant.

Computational analysis of energy distribution of coupled blood flow and arterial deformation

The present study analyzes the distribution and dissipation of the energy delivered to arteries. A computational model of blood flow and arterial deformation is used to examine the behavior of different constitutive models of arterial wall. In particular, we consider poroelastic and viscoelastic descriptions of the artery. Energy estimates are derived for each constitutive model of the arterial wall from the weak formulation of the fluid/solid coupled problem and are applied to assess energy exchange between different compartments of the model. The objective of this work is to determine new criteria, based on energy distribution, for the assessment of constitutive models of the arterial wall. Two-dimensional numerical experiments are presented to illustrate the energy distribution within the fluid and solid model compartments. Results highlight the importance of including both poroelasticity and viscoelasticity in modeling fluid-structure interaction in large arteries. Our results show that both viscoelastic and poroelastic models for the arterial walls absorb part of the input energy flowing to the artery, but the underlying mechanisms are substantially different.

Patient-specific computational modeling of blood flow in the pulmonary arterial circulation

Computational fluid dynamics (CFD) modeling of the pulmonary vasculature has the potential to reveal continuum metrics associated with the hemodynamic stress acting on the vascular endothelium. It is widely accepted that the endothelium responds to flow-induced stress by releasing vasoactive substances that can dilate and constrict blood vessels locally. The objectives of this study are to examine the extent of patient specificity required to obtain a significant association of CFD output metrics and clinical measures in models of the pulmonary arterial circulation, and to evaluate the potential correlation of wall shear stress (WSS) with established metrics indicative of right ventricular (RV) afterload in pulmonary hypertension (PH). Right Heart Catheterization (RHC) hemodynamic data and contrast-enhanced computed tomography (CT) imaging were retrospectively acquired for 10 PH patients and processed to simulate blood flow in the pulmonary arteries. While conducting CFD modeling of the reconstructed patient-specific vasculatures, we experimented with three different outflow boundary conditions to investigate the potential for using computationally derived spatially averaged wall shear stress (SAWSS) as a metric of RV afterload. SAWSS was correlated with both pulmonary vascular resistance (PVR) (R2=0.77, P<0.05) and arterial compliance (C) (R2=0.63, P<0.05), but the extent of the correlation was affected by the degree of patient specificity incorporated in the fluid flow boundary conditions. We found that decreasing the distal PVR alters the flow distribution and changes the local velocity profile in the distal vessels, thereby increasing the local WSS. Nevertheless, implementing generic outflow boundary conditions still resulted in statistically significant SAWSS correlations with respect to both metrics of RV afterload, suggesting that the CFD model could be executed without the need for complex outflow boundary conditions that require invasively obtained patient-specific data. A preliminary study investigating the relationship between outlet diameter and flow distribution in the pulmonary tree offers a potential computationally inexpensive alternative to pressure based outflow boundary conditions.