Predicting Hemodynamic Performance of Fontan Operation for Glenn Physiology using Computational Fluid Dynamics: Ten Patient-specific Cases.

Single ventricle hearts have only one ventricle that can pump blood effectively and the treatment requires three stages of operations to reconfigure the heart and circulatory system. At the second stage, Glenn procedure is performed to connect superior vena cava (SVC) to the pulmonary arteries (PA). For the third and most complex operation, called Fontan, an extracardiac conduit is used to connect inferior vena cava (IVC) to the PL and thereafter no deoxygenated blood goes to the heart. Predicting Hemodynamic Performance of Fontan Operation using computational fluid dynamics (CFD) is hypothesized to improve outcomes and optimize this treatment planning in children with single-ventricle heart disease. An important reason for this surgical planning is to reduce the development of pulmonary arteriovenous malformations (PAVM) and the need to perform Fontan revisions. The purpose of this study was to develop amodel for Fontan surgical planning and use this model to compare blood circulation in two designed graft types of Fontan operation known as T-shape and Y-graft. The functionality of grafts was compared in terms of power loss (PL) and hepatic flow distribution (HFD), a known factor in PAVM development. To perform this study, ten single-ventricle children with Glenn physiology were included and a CFD model was developed to estimate the blood flow circulation to the left and right pulmonary arteries. The estimated blood flow by CFD was compared with that measured by cardiovascular magnetic resonance. Results showed that there was an excellent agreement between the net blood flow in the right and left pulmonary arteries computed by CFD and CMR (ICC= 0.98, P-value ≥0.21). After validating the accuracy of each CFD model, Fontan operations using T-shape and Y-graft conduits were performed in silico for each patient and the developed CFD model was used to predict the post-surgical PL and HFD. We found that the PL in the Y-graft was significantly lower than in the T-shape (P-value ≤0.001) and HFD was significantly better balanced in Y-graft compared to the T-shape (P-value=0.004).

Circulating cell clusters aggravate the hemorheological abnormalities in COVID-19.

Microthrombi and circulating cell clusters are common microscopic findings in patients with coronavirus disease 2019 (COVID-19) at different stages in the disease course, implying that they may function as the primary drivers in disease progression. Inspired by a recent flow imaging cytometry study of the blood samples from patients with COVID-19, we perform computational simulations to investigate the dynamics of different types of circulating cell clusters, namely white blood cell (WBC) clusters, platelet clusters, and red blood cell clusters, over a range of shear flows and quantify their impact on the viscosity of the blood. Our simulation results indicate that the increased level of fibrinogen in patients with COVID-19 can promote the formation of red blood cell clusters at relatively low shear rates, thereby elevating the blood viscosity, a mechanism that also leads to an increase in viscosity in other blood diseases, such as sickle cell disease and type 2 diabetes mellitus. We further discover that the presence of WBC clusters could also aggravate the abnormalities of local blood rheology. In particular, the extent of elevation of the local blood viscosity is enlarged as the size of the WBC clusters grows. On the other hand, the impact of platelet clusters on the local rheology is found to be negligible, which is likely due to the smaller size of the platelets. The difference in the impact of WBC and platelet clusters on local hemorheology provides a compelling explanation for the clinical finding that the number of WBC clusters is significantly correlated with thrombotic events in COVID-19 whereas platelet clusters are not. Overall, our study demonstrates that our computational models based on dissipative particle dynamics can serve as a powerful tool to conduct quantitative investigation of the mechanism causing the pathological alterations of hemorheology and explore their connections to the clinical manifestations in COVID-19.

Thixotropy and rheological hysteresis in blood flow.

Hemorheology is known to be a major diagnostic tool for many blood-altering diseases. While hemorheological measures of blood, such as the general flow curve, shear-thinning behavior, and its yield stress, are much more studied in detail, thixotropic behavior and thermokinematic memory formation in blood are less understood. Here, we study the thermokinematic memory formation in blood, resulting in a clear sensitivity to the flow history, i.e., thixotropic behavior. We also measure the thixotropic timescale for blood flow using a well-defined flow protocol. Employing a series of in silico flow loops in which the blood is subject to a sweep down/up flow, we measure and discuss the dependence of the thixotropic timescale to the concentration of fibrinogen in the plasma as the main driver of structural evolution under flow.

Correction: Hemorheology: the critical role of flow type in blood viscosity measurements.

Correction for 'Hemorheology: the critical role of flow type in blood viscosity measurements' by Elahe Javadi et al., Soft Matter, 2021, 17, 8446-8458, DOI: 10.1039/D1SM00856K.

Hemorheology: the critical role of flow type in blood viscosity measurements.

The crucial role of the hemorheological characteristics of blood in a range of diagnoses, treatments and drug delivery mechanisms is widely accepted. Nonetheless, the literature on blood rheology remains inconclusive and sometimes even contradictory. This is in part due to natural variance of blood samples from one study to another, but also stems from fundamental differences in the consequences of the choice of rheometric flow employed. Here, and using a detailed and accurate computational scheme, we thoroughly study the role of flow type in measurement of blood viscosity. Performing these in silico measurements, we isolate the role of flow type and geometry at different hematocrit levels. We show that flow curves obtained in pressure-driven flows relevant to laminar circulatory flows deviate greatly from ones obtained in drag flow at the same hematocrit level. Our numerical platform also allows for the yield stress to be measured under quiescent conditions and without imposing any flow for different hematocrits. We discuss the scaling of the yield stress with the hematocrit level, and show that the differences in pressure vs. drag flows stem from the Red Blood Cell (RBC) orientation at different flow rates as well as the existence of a cell free layer close to the walls.

In silico biophysics and hemorheology of blood hyperviscosity syndrome.

Hyperviscosity syndrome (HVS) is characterized by an increase of the blood viscosity by up to seven times the normal blood viscosity, resulting in disturbances to the circulation in the vasculature system. HVS is commonly associated with an increase of large plasma proteins and abnormalities in the properties of red blood cells, such as cell interactions, cell stiffness, and increased hematocrit. Here, we perform a systematic study of the effect of each biophysical factor on the viscosity of blood by employing the dissipative particle dynamic method. Our in silico platform enables manipulation of each parameter in isolation, providing a unique scheme to quantify and accurately investigate the role of each factor in increasing the blood viscosity. To study the effect of these four factors independently, each factor was elevated more than its values for a healthy blood while the other factors remained constant, and viscosity measurement was performed for different hematocrits and flow rates. Although all four factors were found to increase the overall blood viscosity, these increases were highly dependent on the hematocrit and the flow rates imposed. The effect of cell aggregation and cell concentration on blood viscosity were predominantly observed at low shear rates, in contrast to the more magnified role of cell rigidity and plasma viscosity at high shear rates. Additionally, cell-related factors increase the whole blood viscosity at high hematocrits compared with the relative role of plasma-related factors at lower hematocrits. Our results, mapped onto the flow rates and hematocrits along the circulatory system, provide a correlation to underpinning mechanisms for HVS findings in different blood vessels.

Integrating blood cell mechanics, platelet adhesive dynamics and coagulation cascade for modelling thrombus formation in normal and diabetic blood.

Normal haemostasis is an important physiological mechanism that prevents excessive bleeding during trauma, whereas the pathological thrombosis especially in diabetics leads to increased incidence of heart attacks and strokes as well as peripheral vascular events. In this work, we propose a new multiscale framework that integrates seamlessly four key components of blood clotting, namely transport of coagulation factors, coagulation kinetics, blood cell mechanics and platelet adhesive dynamics, to model the development of thrombi under physiological and pathological conditions. We implement this framework to simulate platelet adhesion due to the exposure of tissue factor in a three-dimensional microchannel. Our results show that our model can simulate thrombin-mediated platelet activation in the flowing blood, resulting in platelet adhesion to the injury site of the channel wall. Furthermore, we simulate platelet adhesion in diabetic blood, and our results show that both the pathological alterations in the biomechanics of blood cells and changes in the amount of coagulation factors contribute to the excessive platelet adhesion and aggregation in diabetic blood. Taken together, this new framework can be used to probe synergistic mechanisms of thrombus formation under physiological and pathological conditions, and open new directions in modelling complex biological problems that involve several multiscale processes.