A predictive multiscale model for simulating flow-induced platelet activation: Correlating in silico results with in vitro results

Platelet Biorheology and Mechanobiology in Thrombosis and Hemostasis: Perspectives from Multiscale Computation

Thrombosis is the pathological clot formation under abnormal hemodynamic conditions, which can result in vascular obstruction, causing ischemic strokes and myocardial infarction. Thrombus growth under moderate to low shear (<1000 s-1) relies on platelet activation and coagulation. Thrombosis at elevated high shear rates (>10,000 s-1) is predominantly driven by unactivated platelet binding and aggregating mediated by von Willebrand factor (VWF), while platelet activation and coagulation are secondary in supporting and reinforcing the thrombus. Given the molecular and cellular level information it can access, multiscale computational modeling informed by biology can provide new pathophysiological mechanisms that are otherwise not accessible experimentally, holding promise for novel first-principle-based therapeutics. In this review, we summarize the key aspects of platelet biorheology and mechanobiology, focusing on the molecular and cellular scale events and how they build up to thrombosis through platelet adhesion and aggregation in the presence or absence of platelet activation. In particular, we highlight recent advancements in multiscale modeling of platelet biorheology and mechanobiology and how they can lead to the better prediction and quantification of thrombus formation, exemplifying the exciting paradigm of digital medicine.

von Willebrand factor unfolding mediates platelet deposition in a model of high-shear thrombosis

Thrombosis under high-shear conditions is mediated by the mechanosensitive blood glycoprotein von Willebrand factor (vWF). vWF unfolds in response to strong flow gradients and facilitates rapid recruitment of platelets in flowing blood. While the thrombogenic effect of vWF is well recognized, its conformational response in complex flows has largely been omitted from numerical models of thrombosis. We recently presented a continuum model for the unfolding of vWF, where we represented vWF transport and its flow-induced conformational change using convection-diffusion-reaction equations. Here, we incorporate the vWF component into our multi-constituent model of thrombosis, where the local concentration of stretched vWF amplifies the deposition rate of free-flowing platelets and reduces the shear cleaning of deposited platelets. We validate the model using three benchmarks: in vitro model of atherothrombosis, a stagnation point flow, and the PFA-100, a clinical blood test commonly used for screening for von Willebrand disease (vWD). The simulations reproduced the key aspects of vWF-mediated thrombosis observed in these experiments, such as the thrombus location, thrombus growth dynamics, and the effect of blocking platelet-vWF interactions. The PFA-100 simulations closely matched the reported occlusion times for normal blood and several hemostatic deficiencies, namely, thrombocytopenia, vWD type 1, and vWD type 3. Overall, this multi-constituent model of thrombosis enables macro-scale 3D simulations of thrombus formation in complex geometries over a wide range of shear rates and accounts for qualitative and quantitative hemostatic deficiencies in patient blood.

A fibrin enhanced thrombosis model for medical devices operating at low shear regimes or large surface areas

Over the past decade, much of the development of computational models of device-related thrombosis has focused on platelet activity. While those models have been successful in predicting thrombus formation in medical devices operating at high shear rates (> 5000 s⁻¹), they cannot be directly applied to low-shear devices, such as blood oxygenators and catheters, where emerging information suggest that fibrin formation is the predominant mechanism of clotting and platelet activity plays a secondary role. In the current work, we augment an existing platelet-based model of thrombosis with a partial model of the coagulation cascade that includes contact activation of factor XII and fibrin production. To calibrate the model, we simulate a backward-facing-step flow channel that has been extensively characterized in-vitro. Next, we perform blood perfusion experiments through a microfluidic chamber mimicking a hollow fiber membrane oxygenator and validate the model against these observations. The simulation results closely match the time evolution of the thrombus height and length in the backward-facing-step experiment. Application of the model to the microfluidic hollow fiber bundle chamber capture both gross features such as the increasing clotting trend towards the outlet of the chamber, as well as finer local features such as the structure of fibrin around individual hollow fibers. Our results are in line with recent findings that suggest fibrin production, through contact activation of factor XII, drives the thrombus formation in medical devices operating at low shear rates with large surface area to volume ratios.

Patients treated with blood-contacting medical devices suffer from clotting complications. Over the past decades, a great effort has been made to develop computational tools to predict and prevent clot formation in these devices. However, most models have focused on platelet activity and neglected other important parts of the problem such as the coagulation cascade reactions that lead to fibrin formation. In the current work, we incorporate this missing element into a well-established and validated model for platelet activity. We then use this novel approach to predict thrombus formation in two experimental configurations. Our results confirm that to accurately predict the clotting process in devices where surface area to volume ratios are large and flow velocity and shear stresses remain low, coagulation reactions and subsequent fibrin formation must be considered. This new model could have great implications for the design and optimization of medical devices such as blood oxygenators. In the long term, the model could evolve into a functional tool to inform anticoagulation therapies for these patients.

Uncertainty quantification of a thrombosis model considering the clotting assay PFA-100®

Mathematical models of thrombosis are currently used to study clinical scenarios of pathological thrombus formation. As these models become more complex to predict thrombus formation dynamics high computational cost must be alleviated and inherent uncertainties must be assessed. Evaluating model uncertainties allows to increase the confidence in model predictions and identify avenues of improvement for both thrombosis modeling and anti-platelet therapies. In this work, an uncertainty quantification analysis of a multi-constituent thrombosis model is performed considering a common assay for platelet function (PFA-100®). The analysis is facilitated thanks to time-evolving polynomial chaos expansions used as a parametric surrogate for the full thrombosis model considering two quantities of interest; namely, thrombus volume and occlusion percentage. The surrogate is thoroughly validated and provides a straightforward access to a global sensitivity analysis via computation of Sobol' coefficients. Six out of 15 parameters linked to thrombus consitution, vWF activity, and platelet adhesion dynamics were found to be most influential in the simulation variability considering only individual effects; while parameter interactions are highlighted when considering the total Sobol' indices. The influential parameters are related to thrombus constitution, vWF activity, and platelet to platelet adhesion dynamics. The surrogate model allowed to predict realistic PFA-100® closure times of 300,000 virtual cases that followed the trends observed in clinical data. The current methodology could be used including common anti-platelet therapies to identify scenarios that preserve the hematological balance.

Models of Shear-Induced Platelet Activation and Numerical Implementation With Computational Fluid Dynamics Approaches

Shear-induced platelet activation is one of the critical outcomes when blood is exposed to elevated shear stress. Excessively activated platelets in the circulation can lead to thrombus formation and platelet consumption, resulting in serious adverse events such as thromboembolism and bleeding. While experimental observations reveal that it is related to the shear stress level and exposure time, the underlying mechanism of shear-induced platelet activation is not fully understood. Various models have been proposed to relate shear stress levels to platelet activation, yet most are modified from the empirically calibrated power-law model. Newly developed multiscale platelet models are tested as a promising approach to capture a single platelet's dynamic shape during activation, but it would be computationally expensive to employ it for a large-scale analysis. This paper summarizes the current numerical models used to study the shear-induced platelet activation and their computational applications in the risk assessment of a particular flow pattern and clot formation prediction.

An Accelerated Thrombosis Model for Computational Fluid Dynamics Simulations in Rotary Blood Pumps

Purpose

Thrombosis ranks among the major complications in blood-carrying medical devices and a better understanding to influence the design related contribution to thrombosis is desirable. Over the past years many computational models of thrombosis have been developed. However, numerically cheap models able to predict localized thrombus risk in complex geometries are still lacking. The aim of the study was to develop and test a computationally efficient model for thrombus risk prediction in rotary blood pumps.

Methods

We used a two-stage approach to calculate thrombus risk. The first stage involves the computation of velocity and pressure fields by computational fluid dynamic simulations. At the second stage, platelet activation by mechanical and chemical stimuli was determined through species transport with an Eulerian approach. The model was compared with existing clinical data on thrombus deposition within the HeartMate II. Furthermore, an operating point and model parameter sensitivity analysis was performed.

Results

Our model shows good correlation (R² > 0.93) with clinical data and identifies the bearing and outlet stator region of the HeartMate II as the location most prone to thrombus formation. The calculation of thrombus risk requires an additional 10–20 core hours of computation time.

Conclusion

The concentration of activated platelets can be used as a surrogate and computationally low-cost marker to determine potential risk regions of thrombus deposition in a blood pump. Relative comparisons of thrombus risk are possible even considering the intrinsic uncertainty in model parameters and operating conditions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13239-021-00606-y.

Highly resilient, biocompatible, and antibacterial carbon nanotube/hydroxybutyl chitosan sponge dressing for rapid and effective hemostasis

Uncontrolled hemorrhage is the leading cause of trauma death. The development of safe and efficient hemostatic agents that can rapidly and effectively control bleeding is of great significance to rescue the injured. However, the mechanical, absorptive, and antibacterial properties of conventional two-dimensional hemostatic agents are not satisfactory. Herein, a series of effective three-dimensional hemostatic dressings (JWCNT/HBC sponges) are developed by chemical modification of joint-welded carbon nanotube (JWCNT) sponges with hydroxybutyl chitosan (HBC) for hemorrhage hemostasis. The JWCNT/HBC sponges exhibit high elasticity, porous structure, and suitable blood-absorption and blood-maintaining performance. Moreover, the introduction of HBC endows the JWCNT/HBC sponges with favorable blood compatibility and good antibacterial activity. The sponge treated with 0.5% HBC (JWCNT/0.5%HBC sponge) displays better antiseptic capability, faster blood clotting ability in vitro and shorter hemostasis time in vivo than the commercial gelatin sponge. The JWCNT/HBC sponges combine the advantages of JWCNT sponges and HBC in the adhesion and activation of platelets and red blood cells, thus becoming a good medical material for trauma hemostasis.

In Vitro Measurements of Shear-Mediated Platelet Adhesion Kinematics as Analyzed through Machine Learning

Platelet adhesion to blood vessel walls in shear flow is essential to initiating the blood coagulation cascade and prompting clot formation in vascular disease processes and prosthetic cardiovascular devices. Validation of predictive adhesion kinematics models at the single platelet level is difficult due to gaps in high resolution, dynamic morphological data or a mismatch between simulation and experimental parameters. Gel-filtered platelets were perfused at 30 dyne/cm² in von Willebrand Factor (vWF)-coated microchannels, with flipping platelets imaged at high spatial and temporal resolution. A semi-unsupervised learning system (SULS), consisting of a series of convolutional neural networks, was used to segment platelet geometry, which was compared with expert-analyzed images. Resulting time-dependent rotational angles were smoothed with wavelet-denoising and shifting techniques to characterize the rotational period and quantify flipping kinematics. We observed that flipping platelets do not follow the previously-modeled modified Jefferey orbit, but are characterized by a longer lift-off and shorter reattachment period. At the juncture of the two periods, rotational velocity approached 257.48 ± 13.31 rad/s. Our SULS approach accurately segmented large numbers of moving platelet images to identify distinct adhesive kinematic characteristics which may further validate the physical accuracy of individual platelet motion in multiscale models of shear-mediated thrombosis.