Modeling blood flow around a thrombus using a hybrid particle–continuum approach

Analysis of factors related to thrombosis in patients with PICC placements

This study aimed to investigate the conditions of patients with peripherally inserted central catheter (PICC) placements, analyze the risk factors influencing thrombosis in PICC-placed patients, and formulate more accurate and effective PICC management strategies. A total of 147 patients undergoing PICC placements were selected as the study subjects. Clinical data were collected, and the patients were divided into thrombosis and non-thrombosis groups. Detect levels of bilirubin, white blood cells, venous pressure, heparin concentration, blood flow, citric acid, and platelets. Pearson chi-square test, Spearman correlation analysis, as well as univariate and multivariate logistic regression were employed to analyze independent risk factors. Among the 147 patients with PICC placements, there were 84 males and 63 females. Thrombosis occurred in 116 cases, with an incidence rate of 78.91%. Pearson chi-square test showed a significant correlation between citric acid, blood flow, platelets and frailty (P < .001) with thrombosis formation. Spearman correlation analysis revealed a significant correlation between citric acid (ρ = -0.636, P < .001), blood flow (ρ = 0.584, P < .001), platelet count (ρ = 0.440, P < .001), frailty (ρ = -0.809, P < .001) and thrombosis in PICC placement patients. Univariate logistic regression analysis indicated a significant correlation between thrombosis formation and citric acid (OR = 0.022, 95% CI = 0.006-0.08, P < .001), blood flow (OR = 33.973, 95% CI = 9.538-121.005, P < .001), platelet count (OR = 22.065, 95% CI = 5.021-96.970, P < .001), frailty (OR = 0.003, 95% CI = 0.001-0.025, P < .001). Multivariate logistic regression analysis also showed a significant correlation between thrombosis formation and citric acid (OR = 0.013, 95% CI = 0.002-0.086, P < .001), blood flow (OR = 35.064, 95% CI = 6.385-192.561, P < .001), platelet count (OR = 4.667, 95% CI = 0.902-24.143, P < .001), frailty (OR = 0.006, 95% CI = 0.001-0.051, P < .001). However, gender (OR = 0.544, 95% CI = 0.113-2.612, P = .447), age (OR = 4.178, 95% CI = 0.859-20.317, P = .076), bilirubin (OR = 2.594, 95% CI = 0.586-11.482, P = .209), white blood cells (OR = 0.573, 95% CI = 0.108-3.029, P = .512), venous pressure (OR = 0.559, 95% CI = 0.129-2.429, P = .438), and heparin concentration (OR = 2.660, 95% CI = 0.333-21.264, P = .356) showed no significant correlation with thrombosis formation. Patients with PICC placements have a higher risk of thrombosis, citric acid, blood flow, platelet count and frailty are the main risk factors.

Investigating clot-flow interactions by integrating intravital imaging with in silico modeling for analysis of flow, transport, and hemodynamic forces

As a blood clot forms, grows, deforms, and embolizes following a vascular injury, local clot-flow interactions lead to a highly dynamic flow environment. The local flow influences transport of biochemical species relevant for clotting, and determines the forces on the clot that in turn lead to clot deformation and embolization. Despite this central role, quantitative characterization of this dynamic clot-flow interaction and flow environment in the clot neighborhood remains a major challenge. Here, we propose an approach that integrates dynamic intravital imaging with computer geometric modeling and computational flow and transport modeling to develop a unified in silico framework to quantify the dynamic clot-flow interactions. We outline the development of the methodology referred to as Intravital Integrated In Silico Modeling or IVISim, and then demonstrate the method on a sample set of simulations comprising clot formation following laser injury in two mouse cremaster arteriole injury model data: one wild-type mouse case, and one diYF knockout mouse case. Simulation predictions are verified against experimental observations of transport of caged fluorescent Albumin (cAlb) in both models. Through these simulations, we illustrate how the IVISim methodology can provide insights into hemostatic processes, the role of flow and clot-flow interactions, and enable further investigations comparing and contrasting different biological model scenarios and parameter variations.

Decoding thrombosis through code: a review of computational models

From the molecular level up to a blood vessel, thrombosis and hemostasis involves many interconnected biochemical and biophysical processes over a wide range of length and time scales. Computational modeling has gained eminence in offering insights into these processes beyond what can be obtained from in vitro or in vivo experiments, or clinical measurements. The multiscale and multiphysics nature of thrombosis has inspired a wide range of modeling approaches that aim to address how a thrombus forms and dismantles. Here, we review recent advances in computational modeling with a focus on platelet-based thrombosis. We attempt to summarize the diverse range of modeling efforts straddling the wide-spectrum of physical phenomena, length scales, and time scales; highlighting key advancements and insights from existing studies. Potential information gleaned from models is discussed, ranging from identification of thrombus-prone regions in patient-specific vasculature to modeling thrombus deformation and embolization in response to fluid forces. Furthermore, we highlight several limitations of current models, future directions in the field, and opportunities for clinical translation, to illustrate the state-of-the-art. There are a plethora of opportunity areas for which models can be expanded, ranging from topics of thromboinflammation to platelet production and clearance. Through successes demonstrated in existing studies described here, as well as continued advancements in computational methodologies and computer processing speeds and memory, in silico investigations in thrombosis are poised to bring about significant knowledge growth in the years to come.

Study of trioleoylglycerol two-layer and adiposome cross-section mimicking four-layer systems through atomic-level simulations

Adiposomes are artificially prepared lipid droplet (LD)-mimetic structures, which, unlike LDs, do not harbor proteins. The dynamics of interaction between triacylglycerols (TAGs), drug molecule, and phospholipids in adiposomes is currently not well-established. Trioleoylglycerol (TOG) molecule was divided into three parts: two oleoyl tails and one 2-monooleoylglycerol (MOG). Forcefield parameters for two oleoyl tails were adopted from the AMBER18 repository while that of the MOG forcefield was taken from the literature. Charge correction was performed on the MOG forcefield before its utilization. After charge correction, the resulting TOG molecule had zero charge. TOG bilayer (2L) and tetralayer (4L) systems were prepared and simulated. TOG bilayer (2L) systems-modeled from two different initial conformations, the TOG3 conformation and the TOG2:1 conformation-showed that TOG2:1 conformation was more prevailing irrespective of the starting conformation and was subsequently used in further simulations. The hydrated TOG 2L system showed TOG-water solution solubility of 0.051 mol L^-1 which is near experimental values. This validated the correct parameterization of the TOG molecule. The simulations of 4L systems showed stable membrane behaviors toward the end of simulations. It was also observed that in the 4L system, the TOG molecules showed the formation of micelles with the drug molecule. Almost six TOGs remained continuously in contact with the drug molecule throughout the simulation. The availability of charge-corrected TOG parameterization is expected to equip future studies with a framework for molecular dynamics simulations of adiposomes and/or LDs at the atomic level.

Multiphysics and multiscale modeling of microthrombosis in COVID-19

Emerging clinical evidence suggests that thrombosis in the microvasculature of patients with Coronavirus disease 2019 (COVID-19) plays an essential role in dictating the disease progression. Because of the infectious nature of SARS-CoV-2, patients’ fresh blood samples are limited to access for in vitro experimental investigations. Herein, we employ a novel multiscale and multiphysics computational framework to perform predictive modeling of the pathological thrombus formation in the microvasculature using data from patients with COVID-19. This framework seamlessly integrates the key components in the process of blood clotting, including hemodynamics, transport of coagulation factors and coagulation kinetics, blood cell mechanics and adhesive dynamics, and thus allows us to quantify the contributions of many prothrombotic factors reported in the literature, such as stasis, the derangement in blood coagulation factor levels and activities, inflammatory responses of endothelial cells and leukocytes to the microthrombus formation in COVID-19. Our simulation results show that among the coagulation factors considered, antithrombin and factor V play more prominent roles in promoting thrombosis. Our simulations also suggest that recruitment of WBCs to the endothelial cells exacerbates thrombogenesis and contributes to the blockage of the blood flow. Additionally, we show that the recent identification of flowing blood cell clusters could be a result of detachment of WBCs from thrombogenic sites, which may serve as a nidus for new clot formation. These findings point to potential targets that should be further evaluated, and prioritized in the anti-thrombotic treatment of patients with COVID-19. Altogether, our computational framework provides a powerful tool for quantitative understanding of the mechanism of pathological thrombus formation and offers insights into new therapeutic approaches for treating COVID-19 associated thrombosis.

Emerging clinical evidence suggests that thrombosis in the microvasculature of patients with Coronavirus disease 2019 (COVID-19) plays an essential role in dictating the disease progression. We employ a novel multiphysics and multiscale computational framework to investigate the underlying mechanism of the pathological formation of microthrombi and circulating cell clusters in COVID-19. We quantify the contributions of many prothrombotic factors reported in the literature, such as stasis, the derangement in blood coagulation factor levels and activities, inflammatory responses of endothelial cells and leukocytes to the microthrombus formation in COVID-19, through which we identify the potential targets that should be further evaluated, and prioritized in the anti-thrombotic treatment of patients with COVID-19.

In vitro and in silico modeling of endovascular stroke treatments for acute ischemic stroke

Acute ischemic stroke occurs when a thrombus obstructs a cerebral artery, leading to sub-optimal blood perfusion to brain tissue. A recently developed, preventive treatment is the endovascular stroke treatment (EVT), which is a minimally invasive procedure, involving the use of stent-retrievers and/or aspiration catheters. Despite its increasing use, many critical factors of EVT are not well understood. In this respect, in vitro, and in silico studies have the great potential to help us deepen our understanding of the procedure, perform further device and procedural optimization, and help in clinical training. This review paper provides an overview of the previous in vitro and in silico evaluations of EVT treatments, with a special emphasis on the four main aspects of the adopted experimental and numerical set-ups: vessel, thrombus, device, and procedural settings.

Microstructure aware modeling of biochemical transport in arterial blood clots

Flow-mediated transport of biochemical species is central to thrombotic phenomena. Comprehensive three-dimensional modeling of flow-mediated transport around realistic macroscale thrombi poses challenges owing to their arbitrary heterogeneous microstructure. Here, we develop a microstructure aware model for species transport within and around a macroscale thrombus by devising a custom preconditioned fictitious domain formulation for thrombus-hemodynamics interactions, and coupling it with a fictitious domain advection-diffusion formulation for transport. Microstructural heterogeneities are accounted through a hybrid discrete particle-continuum approach for the thrombus interior. We present systematic numerical investigations on unsteady arterial flow within and around a three-dimensional macroscale thrombus; demonstrate the formation of coherent flow structures around the thrombus which organize advective transport; illustrate the role of the permeation processes at the thrombus boundary and subsequent intra-thrombus transport; and characterize species transport from bulk flow to the thrombus boundary and vice versa.

Healthy and diseased in vitro models of vascular systems

Irregular hemodynamics affects the progression of various vascular diseases, such atherosclerosis or aneurysms. Despite the extensive hemodynamics studies on animal models, the inter-species differences between humans and animals hamper the translation of such findings. Recent advances in vascular tissue engineering and the suitability of in vitro models for interim analysis have increased the use of in vitro human vascular tissue models. Although the effect of flow on endothelial cell (EC) pathophysiology and EC-flow interactions have been vastly studied in two-dimensional systems, they cannot be used to understand the effect of other micro- and macro-environmental parameters associated with vessel wall diseases. To generate an ideal in vitro model of the vascular system, essential criteria should be included: 1) the presence of smooth muscle cells or perivascular cells underneath an EC monolayer, 2) an elastic mechanical response of tissue to pulsatile flow pressure, 3) flow conditions that accurately mimic the hemodynamics of diseases, and 4) geometrical features required for pathophysiological flow. In this paper, we review currently available in vitro models that include flow dynamics and discuss studies that have tried to address the criteria mentioned above. Finally, we critically review in vitro fluidic models of atherosclerosis, aneurysm, and thrombosis.

Computational investigation of blood flow and flow-mediated transport in arterial thrombus neighborhood

A pathologically formed blood clot or thrombus is central to major cardiovascular diseases like heart attack and stroke. Detailed quantitative evaluation of flow and flow-mediated transport processes in the thrombus neighborhood within large artery hemodynamics is crucial for understanding disease progression and assessing treatment efficacy. This, however, remains a challenging task owing to the complexity of pulsatile viscous flow interactions with arbitrary shape and heterogeneous microstructure of realistic thrombi. Here, we address this challenge by conducting a systematic parametric simulation-based study on characterizing unsteady hemodynamics and flow-mediated transport in the neighborhood of an arterial thrombus. We use a hybrid particle-continuum-based finite element approach to handle arbitrary thrombus shape and microstructural variations. Results from a cohort of 50 different unsteady flow scenarios are presented, including unsteady vortical structures, pressure gradient across the thrombus boundary, finite time Lyapunov exponents, and dynamic coherent structures that organize advective transport. We clearly illustrate the combined influence of three key parameters-thrombus shape, microstructure, and extent of wall disease-in terms of: (a) determining hemodynamic features in the thrombus neighborhood and (b) governing the balance between advection, permeation, and diffusion to regulate transport processes in the thrombus neighborhood.

Development of a novel hybrid method combining finite difference method and dissipative particle dynamics to simulate thrombus formation on orifice flow

In our previous works, the transport of activated platelets (APs) on orifice flow has been simulated by finite difference method (FDM). And the distribution of AP concentration on the flow was obtained. However, the effect of platelet aggregation on the distribution of AP concentration can't be investigated by FDM because FDM can't simulate platelet aggregation. On the other hand, platelet aggregation has been simulated by dissipative particle dynamics (DPD). In this paper, a hybrid method combining FDM and DPD is proposed to investigate the effect of platelet aggregation on the distribution of AP concentration. And the hybrid method is used to simulate thrombus formation on orifice flow. As for the effect of platelet aggregation, it is found that the distribution of AP concentration in the hybrid method is different from the distribution in FDM at the places of platelet aggregation. It is considered that the difference is induced by platelet aggregation. As for the distribution of thrombus, higher AP concentration and more aggregated APs are found around the reattachment point and in the recirculation area. It is considered that thrombus is mainly distributed at these places in the simulation. And according to our previous experimental results, thrombus is mainly distributed around the reattachment point and in the recirculation area. It is concluded that the effect of platelet aggregation on the distribution of AP concentration can be investigated by the hybrid method, and the computational results agree with our previous experimental results.