Thrombosis and Hemodynamics: external and intrathrombus gradients

Multiscale simulations that incorporate patient-specific neural network models of platelet calcium signaling predict diverse thrombotic outcomes under flow

During thrombosis, platelets rapidly deposit and activate on the vessel wall, driving conditions such as myocardial infarction and stroke. The complexity of thrombus formation in pathological flow geometries, along with patient-specific pharmacological responses, presents an opportunity for computational modeling to help deliver novel diagnostic and therapeutic insights. In the present study, we employed a multiscale 3D computational model that incorporates unique donor-derived neural networks (NNs) trained with platelet calcium mobilization traces under combinatorial exposure to 6 agonists (n = 10 donors). The 3D model comprises four modules: a donor-specific NN model for platelet calcium mobilization, a lattice kinetic Monte Carlo solver for tracking platelet motion and bonding, a finite volume method solver for modeling soluble agonist release and convective-diffusive transport, and a lattice Boltzmann method solver for predicting the blood velocity field. Simulations were conducted for platelets from individual blood donors under venous and arterial flow conditions on a defined collagen surface, examining the effects of inhibiting ADP and TXA2, as well as the influence of nitric oxide and prostacyclin. The results reveal significant individual variability in platelet responses, influencing simulated thrombus growth dynamics and emphasizing the importance of personalized models for predicting thrombotic behavior. This approach enables consideration of patient-specific platelet signaling, drug responses, and vascular geometry for predicting thrombotic episodes, essential for advancing precision medicine and improving patient outcomes in thrombotic conditions.

The impact of clot permeability on platelet fluxes toward its surface

Platelet aggregation is regulated by a series of chemical reactions that control platelet adhesion on a thrombogenic surface. These reactions are influenced by the complex interaction between reaction kinetics and hemodynamics. This study systematically investigates the transport of platelets, considering the interaction between flow-mediated mass transfer mechanisms and reaction kinetics as a function of clot permeability. A two-dimensional finite element model is developed to replicate static blood flow, platelet transport, and adhesion on a semi-elliptical and semi-circular structure representing permeable clots. The platelet-clot interface interactions are extensively investigated using a hindered transport model, focusing on clot permeabilities, reaction rates, and flow conditions. In the case of clots with highly reactive surfaces, an increase in clot permeability can lead up to four-fold increase in total platelet flux compared to non-permeable clots due to differences in transport environments.

Key influencers in an aneurysmal thrombosis model: A sensitivity analysis and validation study

Thrombosis is a biological response closely related to intracranial aneurysms, and the formation of thrombi inside the aneurysm is an important determinant of outcome after endovascular therapy. As the regulation of thrombosis is immensely complicated and the mechanisms governing thrombus formation are not fully understood, mathematical and computational modeling has been increasingly used to gain insight into thrombosis over the last 30 years. To have a robust computational thrombosis model for possible clinical use in the future, it is essential to assess the model's reliability through comprehensive sensitivity analysis of model parameters and validation studies based on clinical information of real patients. Here, we conduct a global sensitivity analysis on a previously developed thrombosis model, utilizing thrombus composition, the flow-induced platelet index, and the bound platelet concentration as output metrics. These metrics are selected for their relevance to thrombus stability. The flow-induced platelet index quantifies the effect of blood flow on the transport of platelets to and from the site of thrombus formation and thus on the final platelet content of the formed thrombus. The sensitivity analysis of the thrombus composition indicates that the concentration of resting platelets most influences the final thrombus composition. Then, for the first time, we validate the thrombosis model based on a real patient case using patient-specific resting platelet concentration and two previously calibrated trigger thresholds for thrombosis initiation. We show that our thrombosis model is capable of predicting thrombus formation both before and after endovascular treatment.

A Randomized, Controlled Trial of Continuous Heparin Infusion to Prevent Asymptomatic Catheter-related Thrombosis at Discharge in Infants After Cardiac Surgery: The CHIP-CRT Trial

OBJECTIVES

There are conflicting results in preventing catheter-related thrombosis (CRT). Continuing infusion of unfractionated heparin (UFH) was a potential option for CRT. This study was to determine the effect of continuous UFH infusion on asymptomatic CRT at discharge in infants after cardiac surgery.

STUDY DESIGN

This study was a randomized, placebo-controlled, clinical trial at a single center. All infants with central venous catheters after cardiac surgery, below 3 months of age, were eligible. Stratified by CRT, infants were randomly assigned to the UFH group or the normal saline group. UFH was initiated at a speed of 10 to 15 units/kg/h for infants with CRT and 2 to 3 units/kg/h without CRT. The primary outcome was to determine the rate of CRT at discharge. The secondary outcomes included thrombosis 6 months after surgery, adverse events of UFH, and post-thrombotic symptoms.

RESULTS

Due to slow recruitment during the COVID-19 pandemic, this trial was prematurely stopped. Only 35 infants were randomly assigned to the UFH or control groups. There was no statistically significant difference in CRT rate at discharge ( P =0.429) and 6 months after surgery ( P =1.000) between groups. All CRTs except one disappeared at discharge. No thrombosis or post-thrombotic symptom was reported at follow-up evaluation. There was no difference between groups in duration of thrombus ( P =0.088), D dimer ( P =0.412), catheter in situ days ( P =0.281), and post-thrombotic syndrome ( P =1.000), except for activated partial thromboplastin time ( P =0.001).

CONCLUSIONS

With the early stop of this trial and limited data, it is difficult to draw a definitive conclusion about the efficacy of UFH on CRT. Meanwhile, considering the data from 6 months follow-up, in this population, asymptomatic CRT might resolve with no intervention.

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.

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.