Continuous Modeling of Arterial Platelet Thrombus Formation Using a Spatial Adsorption Equation

Probing interactions of red blood cells and contracting fibrin platelet clots

Contraction of blood clots plays an important role in blood clotting, a natural process that restores hemostasis and regulates thrombosis in the body. Upon injury, a chain of events culminate in the formation of a soft plug of cells and fibrin fibers attaching to wound edges. Platelets become activated and apply contractile forces to shrink the overall clot size, modify clot structure, and mechanically stabilize the clot. Impaired blood clot contraction results in unhealthy volumetric, mechanical, and structural properties of blood clots associated with a range of severe medical conditions for patients with bleeding and thrombotic disorders. Due to the inherent mechanical complexity of blood clots and a confluence of multiple interdependent factors governing clot contraction, the mechanics and dynamics of clot contraction and the interactions with red blood cells (RBCs) remain elusive. Using an experimentally informed, physics-based mesoscale computational model, we probe the dynamic interactions among platelets, fibrin polymers, and RBCs, and examine the properties of contracted blood clots. Our simulations confirm that RBCs strongly affect clot contraction. We find that RBC retention and compaction in thrombi can be solely a result of mechanistic contraction of fibrin mesh due to platelet activity. Retention of RBCs hinders clot contraction and reduces clot contractility. Expulsion of RBCs located closer to clot outer surface results in the development of a dense fibrin shell in thrombus clots commonly observed in experiments. Our simulations identify the essential parameters and interactions that control blood clot contraction process, highlighting its dependence on platelet concentration and the initial clot size. Furthermore, our computational model can serve as a useful tool in clinically relevant studies of hemostasis and thrombosis disorders, and post thrombotic clot lysis, deformation, and breaking.

A three-dimensional multiscale model for the prediction of thrombus growth under flow with single-platelet resolution

Modeling thrombus growth in pathological flows allows evaluation of risk under patient-specific pharmacological, hematological, and hemodynamical conditions. We have developed a 3D multiscale framework for the prediction of thrombus growth under flow on a spatially resolved surface presenting collagen and tissue factor (TF). The multiscale framework is composed of four coupled modules: a Neural Network (NN) that accounts for platelet signaling, a Lattice Kinetic Monte Carlo (LKMC) simulation for tracking platelet positions, a Finite Volume Method (FVM) simulator for solving convection-diffusion-reaction equations describing agonist release and transport, and a Lattice Boltzmann (LB) flow solver for computing the blood flow field over the growing thrombus. A reduced model of the coagulation cascade was embedded into the framework to account for TF-driven thrombin production. The 3D model was first tested against in vitro microfluidics experiments of whole blood perfusion with various antiplatelet agents targeting COX-1, P₂Y₁, or the IP receptor. The model was able to accurately capture the evolution and morphology of the growing thrombus. Certain problems of 2D models for thrombus growth (artifactual dendritic growth) were naturally avoided with realistic trajectories of platelets in 3D flow. The generalizability of the 3D multiscale solver enabled simulations of important clinical situations, such as cylindrical blood vessels and acute flow narrowing (stenosis). Enhanced platelet-platelet bonding at pathologically high shear rates (e.g., von Willebrand factor unfolding) was required for accurately describing thrombus growth in stenotic flows. Overall, the approach allows consideration of patient-specific platelet signaling and vascular geometry for the prediction of thrombotic episodes.

The excessive formation of blood clots under flow within the circulatory system (thrombosis) is known to initiate heart attacks and strokes. Therefore, obtaining insights into the formation and progression of these clots will be useful in evaluating pharmacological options. To this end, we have developed a 3D computational model that tracks the growth of a blood clot under flow from initial platelet deposition to full vessel occlusion in the presence of soluble platelet agonists. We first validated the model against experimental predictions of blood clots formed in vitro. Due to the construction of the model in 3D, we were able to carry out simulations of clot formation under important clinical situations, namely cylindrical blood vessels and acute flow narrowings (stenoses). To our knowledge, our model is the first of its kind that can account for patient-specific platelet phenotypes to perform robust 3D simulations of thrombus growth in geometries of clinical relevance.

Analysis of microvascular thrombus mechanobiology with a novel particle-based model

Platelet accumulation at the site of a vascular injury is regulated by soluble platelet agonists, which induce various types of platelet responses, including integrin activation and granule secretion. The interplay between local biochemical cues, mechanical interactions between platelets and macroscopic thrombus dynamics is poorly understood. Here we describe a novel computational model of microvascular clot formation for the detailed analysis of thrombus mechanics. We adopt a previously developed two-dimensional particle-based model focused on the thrombus shell formation and revise it to introduce the platelet agonists. Blood flow is simulated via a computational fluid dynamics approach. In order to model soluble platelet activators, we apply Langevin dynamics to a large number of non-dimensional virtual particles. Taking advantage of the available data on platelet dense granule secretion kinetics, we model platelet degranulation as a stochastic agonist-dependent process. The new model qualitatively reproduces the enhanced thrombus formation due to dense granule secretion, in line with in vivo findings, and provides a mechanism for the thrombin confinement at the early stages of clot formation. Our calculations also predict that the release of platelet dense granules results in the additional mechanical stabilization of the inner layers of thrombus. Distribution of the inter-platelet forces throughout the aggregate reveals multiple weak spots in the outer regions of a thrombus, which are expected to result in the mechanical disruptions at the later stages of clot formation.

Modeling Thrombus Shell: Linking Adhesion Receptor Properties and Macroscopic Dynamics

Damage to arterial vessel walls leads to the formation of platelet aggregate, which acts as a physical obstacle for bleeding. An arterial thrombus is heterogeneous; it has a dense inner part (core) and an unstable outer part (shell). The thrombus shell is very dynamic, being composed of loosely connected discoid platelets. The mechanisms underlying the observed mobility of the shell and its (patho)physiological implications are unclear. To investigate arterial thrombus mechanics, we developed a novel, to our knowledge, two-dimensional particle-based computational model of microvessel thrombosis. The model considers two types of interplatelet interactions: primary reversible (glycoprotein Ib (GPIb)-mediated) and stronger integrin-mediated interaction, which intensifies with platelet activation. At high shear rates, the former interaction leads to adhesion, and the latter is primarily responsible for stable platelet aggregation. Using a stochastic model of GPIb-mediated interaction, we initially reproduced experimental curves that characterize individual platelet interactions with a von Willebrand factor-coated surface. The addition of the second stabilizing interaction results in thrombus formation. The comparison of thrombus dynamics with experimental data allowed us to estimate the magnitude of critical interplatelet forces in the thrombus shell and the characteristic time of platelet activation. The model predicts moderate dependence of maximal thrombus height on the injury size in the absence of thrombin activity. We demonstrate that the developed stochastic model reproduces the observed highly dynamic behavior of the thrombus shell. The presence of primary stochastic interaction between platelets leads to the properties of thrombus consistent with in vivo findings; it does not grow upstream of the injury site and covers the whole injury from the first seconds of the formation. А simplified model, in which GPIb-mediated interaction is deterministic, does not reproduce these features. Thus, the stochasticity of platelet interactions is critical for thrombus plasticity, suggesting that interaction via a small number of bonds drives the dynamics of arterial thrombus shell.

In Silico Hemostasis Modeling and Prediction

Computational physiology, i.e., reproduction of physiological (and, by extension, pathophysiological) processes in silico, could be considered one of the major goals in computational biology. One might use computers to simulate molecular interactions, enzyme kinetics, gene expression, or whole networks of biochemical reactions, but it is (patho)physiological meaning that is usually the meaningful goal of the research even when a single enzyme is its subject. Although exponential rise in the use of computational and mathematical models in the field of hemostasis and thrombosis began in the 1980s (first for blood coagulation, then for platelet adhesion, and finally for platelet signal transduction), the majority of their successful applications are still focused on simulating the elements of the hemostatic system rather than the total (patho)physiological response in situ. Here we discuss the state of the art, the state of the progress toward the efficient "virtual thrombus formation," and what one can already get from the existing models.

Occlusive thrombosis in arteries

Thrombus formation in major arteries is life threatening. In this review article, we discuss how an arterial thrombus can form under pathologically high shear stresses, with bonding rates estimated to be the fastest Kon values in biochemistry. During occlusive thrombosis in arteries, the growth rate of the thrombus explodes to capture a billion platelets in about 10 min. Close to 100% of all platelets passing the thrombus are captured by long von Willebrand factor (vWF) strands that quickly form tethered nets. The nets grow in patches where shear stress is high, and the local concentration of vWF is elevated due to α-granule release by previously captured platelets. This rapidly formed thrombus has few red blood cells and so has a white appearance and is much stronger and more porous than clots formed through coagulation. Understanding and modeling the biophysics of this event can predict totally new approaches to prevent and treat heart attacks and strokes.

Hemodynamics of neonatal double lumen cannula malposition

Objective:

Malposition of dual lumen cannula is a frequent and challenging complication in neonates and plays a significant role in shaping the in vitro device hemodynamics. This study aims to analyze the effect of the dual lumen cannula malposition on right-atrial hemodynamics in neonatal patients using an experimentally validated computational fluid dynamics model.

Methods:

A computer model was developed for clinically approved dual lumen cannula (13Fr Origen Biomedical, Austin, Texas, USA) oriented inside the atrium of a 3-kg neonate with normal venous return. Atrial hemodynamics and dual lumen cannula malposition were systematically simulated for two rotations (antero-atrial and atrio-septal) and four translations (two intravascular movements along inferior vena cava and two dislodged configurations in the atrium). A multi-domain compartmentalized mesh was prepared to allow the site-specific evaluation of important hemodynamic parameters. Transport of each blood stream, blood damage levels, and recirculation times are quantified and compared to dual lumen cannula in proper position.

Results:

High recirculation levels (39 ± 4%) in malpositioned cases resulted in poor oxygen saturation where maximum recirculation of up to 42% was observed. Apparently, Origen dual lumen cannula showed poor inferior vena cava blood–capturing efficiency (48 ± 8%) but high superior vena cava blood–capturing efficiency (86 ± 10%). Dual lumen cannula malposition resulted in corresponding changes in residence time (1.7 ± 0.5 seconds through the tricuspid). No significant differences in blood damage were observed among the simulated cases compared to normal orientation. Compared to the correct dual lumen cannula position, both rotational and translational displacements of the dual lumen cannula resulted in significant hemodynamic differences.

Conclusion:

Rotational or translational movement of dual lumen cannula is the determining factor for atrial hemodynamics, venous capturing efficiency, blood residence time, and oxygenated blood delivery. Results obtained through computational fluid dynamics methodology can provide valuable foresight in assessing the performance of the dual lumen cannula in patient-specific configurations.

Microfluidic and computational study of structural properties and resistance to flow of blood clots under arterial shear

The ability of a blood clot to modulate blood flow is determined by the clot’s resistance, which depends on its structural features. For a flow with arterial shear, we investigated the characteristic patterns relating to clot shape, size, and composition on the one hand, and its viscous resistance, intraclot axial flow velocity, and shear distributions on the other. We used microfluidic technology to measure the kinetics of platelet, thrombin, and fibrin accumulation at a thrombogenic surface coated with collagen and tissue factor (TF), the key clot-formation trigger. We subsequently utilized the obtained data to perform additional calibration and validation of a detailed computational fluid dynamics model of spatial clot growth under flow. We then ran model simulations to gain insights into the resistance of clots formed under our experimental conditions. We found that increased thrombogenic surface length and TF surface density enhanced the bulk thrombin and fibrin generation in a nonadditive, synergistic way. The height of the platelet deposition domain—and, therefore, clot occlusivity—was rather robust to thrombogenic surface length and TF density variations, but consistently increased with time. Clot viscous resistance was non-uniform and tended to be higher in the fibrin-rich, inner “core” region of the clot. Interestingly, despite intraclot structure and viscous resistance variations, intraclot flow velocity variations were minor compared to the abrupt decrease in flow velocity around the platelet deposition region. Our results shed new light on the connection between the structure of clots under arterial shear and spatiotemporal variations in their resistance to flow.

Multiscale simulation of thrombus growth and vessel occlusion triggered by collagen/tissue factor using a data-driven model of combinatorial platelet signalling

During clotting under flow, platelets bind and activate on collagen and release autocrinic factors such as ADP and thromboxane, while tissue factor (TF) on the damaged wall leads to localized thrombin generation. Towards patient-specific simulation of thrombosis, a multiscale approach was developed to account for: platelet signalling [neural network (NN) trained by pairwise agonist scanning (PAS), PAS-NN], platelet positions (lattice kinetic Monte Carlo, LKMC), wall-generated thrombin and platelet-released ADP/thromboxane convection–diffusion (partial differential equation, PDE) and flow over a growing clot (lattice Boltzmann). LKMC included shear-driven platelet aggregate restructuring. The PDEs for thrombin, ADP and thromboxane were solved by finite element method using cell activation-driven adaptive triangular meshing. At all times, intracellular calcium was known for each platelet by PAS-NN in response to its unique exposure to local collagen, ADP, thromboxane and thrombin. When compared with microfluidic experiments of human blood clotting on collagen/TF driven by constant pressure drop, the model accurately predicted clot morphology and growth with time. In experiments and simulations at TF at 0.1 and 10 molecule-TF/\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\mu$\end{document}m\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{2}$\end{document} and initial wall shear rate of 200 s\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{-1}$\end{document}, the occlusive blockade of flow for a 60-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\mu$\end{document}m channel occurred relatively abruptly at 600 and 400 s, respectively (with no occlusion at zero TF). Prior to occlusion, intrathrombus concentrations reached 50 nM thrombin, ~ 1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\mu$\end{document}M thromboxane and ~ 10 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\mu$\end{document}M ADP, while the wall shear rate on the rough clot peaked at ~ 1000–2000 s\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$^{-1}$\end{document}. Additionally, clotting on TF/collagen was accurately simulated for modulators of platelet cyclooxygenase-1, P2Y\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$_{1}$\end{document} and IP-receptor. This multiscale approach facilitates patient-specific simulation of thrombosis under hemodynamic and pharmacological conditions.

Model predictions of deformation, embolization and permeability of partially obstructive blood clots under variable shear flow

Thromboembolism, one of the leading causes of morbidity and mortality worldwide, is characterized by formation of obstructive intravascular clots (thrombi) and their mechanical breakage (embolization). A novel two-dimensional multi-phase computational model is introduced that describes active interactions between the main components of the clot, including platelets and fibrin, to study the impact of various physiologically relevant blood shear flow conditions on deformation and embolization of a partially obstructive clot with variable permeability. Simulations provide new insights into mechanisms underlying clot stability and embolization that cannot be studied experimentally at this time. In particular, model simulations, calibrated using experimental intravital imaging of an established arteriolar clot, show that flow-induced changes in size, shape and internal structure of the clot are largely determined by two shear-dependent mechanisms: reversible attachment of platelets to the exterior of the clot and removal of large clot pieces. Model simulations predict that blood clots with higher permeability are more prone to embolization with enhanced disintegration under increasing shear rate. In contrast, less permeable clots are more resistant to rupture due to shear rate-dependent clot stiffening originating from enhanced platelet adhesion and aggregation. These results can be used in future to predict risk of thromboembolism based on the data about composition, permeability and deformability of a clot under specific local haemodynamic conditions.

Modeling thrombosis in silico: Frontiers, challenges, unresolved problems and milestones

Hemostasis is a complex physiological mechanism that functions to maintain vascular integrity under any conditions. Its primary components are blood platelets and a coagulation network that interact to form the hemostatic plug, a combination of cell aggregate and gelatinous fibrin clot that stops bleeding upon vascular injury. Disorders of hemostasis result in bleeding or thrombosis, and are the major immediate cause of mortality and morbidity in the world. Regulation of hemostasis and thrombosis is immensely complex, as it depends on blood cell adhesion and mechanics, hydrodynamics and mass transport of various species, huge signal transduction networks in platelets, as well as spatiotemporal regulation of the blood coagulation network. Mathematical and computational modeling has been increasingly used to gain insight into this complexity over the last 30 years, but the limitations of the existing models remain profound. Here we review state-of-the-art-methods for computational modeling of thrombosis with the specific focus on the analysis of unresolved challenges. They include: a) fundamental issues related to physics of platelet aggregates and fibrin gels; b) computational challenges and limitations for solution of the models that combine cell adhesion, hydrodynamics and chemistry; c) biological mysteries and unknown parameters of processes; d) biophysical complexities of the spatiotemporal networks' regulation. Both relatively classical approaches and innovative computational techniques for their solution are considered; the subjects discussed with relation to thrombosis modeling include coarse-graining, continuum versus particle-based modeling, multiscale models, hybrid models, parameter estimation and others. Fundamental understanding gained from theoretical models are highlighted and a description of future prospects in the field and the nearest possible aims are given.