An integrated fluid-structure interaction and thrombosis model for type B aortic dissection

False lumen thrombosis (FLT) in type B aortic dissection has been associated with the progression of dissection and treatment outcome. Existing computational models mostly assume rigid wall behavior which ignores the effect of flap motion on flow and thrombus formation within the FL. In this study, we have combined a fully coupled fluid-structure interaction (FSI) approach with a shear-driven thrombosis model described by a series of convection-diffusion reaction equations. The integrated FSI-thrombosis model has been applied to an idealized dissection geometry to investigate the interaction between vessel wall motion and growing thrombus. Our simulation results show that wall compliance and flap motion can influence the progression of FLT. The main difference between the rigid and FSI models is the continuous development of vortices near the tears caused by drastic flap motion up to 4.45 mm. Flap-induced high shear stress and shear rates around tears help to transport activated platelets further to the neighboring region, thus speeding up thrombus formation during the accelerated phase in the FSI models. Reducing flap mobility by increasing the Young's modulus of the flap slows down the thrombus growth. Compared to the rigid model, the predicted thrombus volume is 25% larger using the FSI-thrombosis model with a relatively mobile flap. Furthermore, our FSI-thrombosis model can capture the gradual effect of thrombus growth on the flow field, leading to flow obstruction in the FL, increased blood viscosity and reduced flap motion. This model is a step closer toward simulating realistic thrombus growth in aortic dissection, by taking into account the effect of intimal flap and vessel wall motion.

An integrated fluid-chemical model toward modeling the thrombus formation in an idealized model of aortic dissection

Type B aortic dissection is a major aortic catastrophe that can be acutely complicated by rapid expansion, rupture, and malperfusion syndromes. The separation of the intima from aortic walls will form a second blood-filled lumen defined as "false lumen (FL)", where the thrombus is more likely to form due to the local stasis hemodynamic conditions. Complete thrombosis of FL is associated with a beneficial outcome while patency and partial thrombosis will lead to later complications. However, the thrombosis mechanism is still unclear and little is known about the impact of chemical species transported by blood flow on this process. The proteins involved in the coagulation cascade (CC) may play an important role in the process of thrombosis, especially in the activation and stabilization of platelets. Based on this hypothesis, a reduced-order fluid-chemical model was established to simulate CC in an aortic dissection phantom with two tears. A high level of fibrin is continuously observed at the top of the FL and some time-varying areas between two tears, indicating a high likelihood of thrombus formation there. This finding is consistent with the clinical observation. The time evolution of coagulation factors is greatly affected by local hemodynamics, especially in the high disturbance zone where the evolution has characteristics of periodic changes consistent with the flow field. The ability of the proposed model to reproduce the CC response provides a potential application to integrate with a model that can simulate platelet activities, forming a biochemical-based model which would help unveil the mechanisms of thrombosis in FL and the clinical decision of appropriate treatment.

Recent advances in computational modeling of fibrin clot formation: A review

The field of thrombosis and hemostasis is crucial for understanding and developing new therapies for pathologies such as deep vein thrombosis, diabetes related strokes, pulmonary embolisms, and hemorrhaging related diseases. In the last two decades, an exponential growth in studies related to fibrin clot formation using computational tools has been observed. Despite this growth, the complete mechanism behind thrombus formation and hemostasis has been long and rife with obstacles; however, significant progress has been made in the present century. The computational models and methods used in this context are diversified into different spatiotemporal scales, yet there is no single model which can predict both physiological and mechanical properties of fibrin clots. In this review, we list the major strategies employed by researchers in modeling fibrin clot formation using recent and existing computational techniques. This review organizes the computational strategies into continuum level, system level, discrete particle (DPD), and multi-scale methods. We also discuss strengths and weaknesses of various methods and future directions in which computational modeling of fibrin clots can advance.

COMPUTATIONAL INVESTIGATION OF THROMBIN CONCENTRATION IN CEREBRAL ANEURYSMS TREATED WITH FLOW-DIVERTING STENTS

Flow-diverting stent is an ongoing embolization device to treat cerebral aneurysms, and it diverts the flow direction to reduce the flow velocity inside the aneurysmal sacs and promote the thrombus formation. However, its effect for aneurysm embolization is controversial. A hemodynamic-biomedical coupling model was constructed to describe the generation and transport of thrombin in arteries, and the model was applied to investigate the variation of thrombin concentration, which plays a key role in thrombus formation, in two patient-specific cerebral aneurysm models when they are treated with Pipeline flow diverting stents. It is observed from computational fluid dynamics simulations that thrombin concentration in the aneurysmal sac without collateral artery increases significantly after Pipeline implantation, however, it has hardly any variation in the aneurysmal sac without collateral artery or in the giant aneurysmal sac after Pipeline implantation. Therefore, we believe that single Pipeline is very effective to embolize a small aneurysm without collateral artery, but cannot embolize a giant aneurysm or a small aneurysm with a collateral artery on its sac effectively.

Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review

Thrombosis is a condition closely related to cerebral aneurysms and controlled thrombosis is the main purpose of endovascular embolization treatment. The mechanisms governing thrombus initiation and evolution in cerebral aneurysms have not been fully elucidated and this presents challenges for interventional planning. Significant effort has been directed towards developing computational methods aimed at streamlining the interventional planning process for unruptured cerebral aneurysm treatment. Included in these methods are computational models of thrombus development following endovascular device placement. The main challenge with developing computational models for thrombosis in disease cases is that there exists a wide body of literature that addresses various aspects of the clotting process, but it may not be obvious what information is of direct consequence for what modeling purpose (e.g., for understanding the effect of endovascular therapies). The aim of this review is to present the information so it will be of benefit to the community attempting to model cerebral aneurysm thrombosis for interventional planning purposes, in a simplified yet appropriate manner. The paper begins by explaining current understanding of physiological coagulation and highlights the documented distinctions between the physiological process and cerebral aneurysm thrombosis. Clinical observations of thrombosis following endovascular device placement are then presented. This is followed by a section detailing the demands placed on computational models developed for interventional planning. Finally, existing computational models of thrombosis are presented. This last section begins with description and discussion of physiological computational clotting models, as they are of immense value in understanding how to construct a general computational model of clotting. This is then followed by a review of computational models of clotting in cerebral aneurysms, specifically. Even though some progress has been made towards computational predictions of thrombosis following device placement in cerebral aneurysms, many gaps still remain. Answering the key questions will require the combined efforts of the clinical, experimental and computational communities.

In vitro measurement of platelet adhesion to intact endothelial cells under low shear conditions

BACKGROUND

Prediction of thrombus formation at intact arterial walls under low shear flow conditions is clinically important particularly for better prognoses of embolisation in cerebral aneurysms. Although a new mathematical model for this purpose is necessary, little quantitative information has been known about platelet adhesion to intact endothelial cells.

OBJECTIVE

The objective of this study is to measure the number of platelets adhering to intact endothelial cells with a focus upon the influence of the shear rate.

METHODS

Endothelial cells disseminated in μ-slides were exposed to swine whole blood at different shear rates. Adenosine diphosphate (ADP) was used as an agonist. Adherent platelets were counted by means of scanning electron microscopy.

RESULTS

At an ADP concentration of 1 µM, 20.8 ± 3.1 platelets per 900 µm2 were observed after 30-minute perfusion at a shear rate of 0.8 s-1 whereas only 3.0 ± 1.4 per 900 µm2 at 16.8 s-1.

CONCLUSIONS

The number of adherent platelets is determined by a balance between the shear and the degree of stimulation by the agonist. At an ADP concentration of 1 µM, a limit to the shear rate at which platelets can adhere to intact endothelial cells is considered to be slightly higher than 16.8 s-1.

Predicting false lumen thrombosis in patient-specific models of aortic dissection

Aortic dissection causes splitting of the aortic wall layers, allowing blood to enter a ‘false lumen’ (FL). For type B dissection, a significant predictor of patient outcomes is patency or thrombosis of the FL. Yet, no methods are currently available to assess the chances of FL thrombosis. In this study, we present a new computational model that is capable of predicting thrombus formation, growth and its effects on blood flow under physiological conditions. Predictions of thrombus formation and growth are based on fluid shear rate, residence time and platelet distribution, which are evaluated through convection–diffusion–reaction transport equations. The model is applied to a patient-specific type B dissection for which multiple follow-up scans are available. The predicted thrombus formation and growth patterns are in good qualitative agreement with clinical data, demonstrating the potential applicability of the model in predicting FL thrombosis for individual patients. Our results show that the extent and location of thrombosis are strongly influenced by aortic dissection geometry that may change over time. The high computational efficiency of our model makes it feasible for clinical applications. By predicting which aortic dissection patient is more likely to develop FL thrombosis, the model has great potential to be used as part of a clinical decision-making tool to assess the need for early endovascular intervention for individual dissection patients.

Virtual endovascular treatment of intracranial aneurysms: models and uncertainty

Virtual endovascular treatment models (VETMs) have been developed with the view to aid interventional neuroradiologists and neurosurgeons to pre-operatively analyze the comparative efficacy and safety of endovascular treatments for intracranial aneurysms. Based on the current state of VETMs in aneurysm rupture risk stratification and in patient-specific prediction of treatment outcomes, we argue there is a need to go beyond personalized biomechanical flow modeling assuming deterministic parameters and error-free measurements. The mechanobiological effects associated with blood clot formation are important factors in therapeutic decision making and models of post-treatment intra-aneurysmal biology and biochemistry should be linked to the purely hemodynamic models to improve the predictive power of current VETMs. The influence of model and parameter uncertainties associated to each component of a VETM is, where feasible, quantified via a random-effects meta-analysis of the literature. This allows estimating the pooled effect size of these uncertainties on aneurysmal wall shear stress. From such meta-analyses, two main sources of uncertainty emerge where research efforts have so far been limited: (1) vascular wall distensibility, and (2) intra/intersubject systemic flow variations. In the future, we suggest that current deterministic computational simulations need to be extended with strategies for uncertainty mitigation, uncertainty exploration, and sensitivity reduction techniques. WIREs Syst Biol Med 2017, 9:e1385. doi: 10.1002/wsbm.1385 For further resources related to this article, please visit the WIREs website.

A computational model based on fibrin accumulation for the prediction of stasis thrombosis following flow-diverting treatment in cerebral aneurysms

Flow diverters, the specially designed low porosity stents, have been used to redirect blood flow from entering aneurysm, which induces flow stasis in aneurysm and promote thrombosis for repairing aneurysm. However, it is not clear how thrombus develops following flow-diversion treatment. Our objective was to develop a computation model for the prediction of stasis-induced thrombosis following flow-diversion treatment in cerebral aneurysms. We proposed a hypothesis to initiate coagulation following flow-diversion treatment. An experimental model was used by ligating rat's right common carotid artery (RCCA) to create flow-stasis environment. Thrombus formed in RCCA as a result of flow stasis. The fibrin distributions in different sections along the axial length of RCCA were measured. The fibrin distribution predicted by our computational model displayed a trend of increase from the proximal neck to the distal tip, consistent with the experimental results on rats. The model was applied on a saccular aneurysm treated with flow diverter to investigate thrombus development following flow diversion. Thrombus was predicted to form inside the sac, and the aneurysm was occluded with only a small remnant neck remained. Our model can serve as a tool to evaluate flow-diversion treatment outcome and optimize the design of flow diverters.

Mathematical modeling of thrombus formation in idealized models of aortic dissection: initial findings and potential applications

Aortic dissection is a major aortic catastrophe with a high morbidity and mortality risk caused by the formation of a tear in the aortic wall. The development of a second blood filled region defined as the “false lumen” causes highly disturbed flow patterns and creates local hemodynamic conditions likely to promote the formation of thrombus in the false lumen. Previous research has shown that patient prognosis is influenced by the level of thrombosis in the false lumen, with false lumen patency and partial thrombosis being associated with late complications and complete thrombosis of the false lumen having beneficial effects on patient outcomes. In this paper, a new hemodynamics-based model is proposed to predict the formation of thrombus in Type B dissection. Shear rates, fluid residence time, and platelet distribution are employed to evaluate the likelihood for thrombosis and to simulate the growth of thrombus and its effects on blood flow over time. The model is applied to different idealized aortic dissections to investigate the effect of geometric features on thrombus formation. Our results are in qualitative agreement with in-vivo observations, and show the potential applicability of such a modeling approach to predict the progression of aortic dissection in anatomically realistic geometries.

Computational modelling of clot development in patient-specific cerebral aneurysm cases

ESSENTIALS: Clotting in cerebral aneurysms is a process that can either stabilize the aneurysm or lead to rupture. A patient-specific computational model capable of predicting cerebral aneurysm thrombosis is presented. The different clotting outcomes highlight the importance of personalization of treatment. Once validated, the model can be used to tailor treatment and to clarify clotting processes in aneurysms.

BACKGROUND

In cerebral aneurysms, clotting can either stabilize the aneurysm sac via aneurysm occlusion, or it can have a detrimental effect by giving rise to embolic occlusion.

OBJECTIVE

The work presented in this study details the development of an in silico model that combines all the salient, clinically relevant features of cerebral aneurysm clotting. A comprehensive computational model of clotting that accounts for biochemical complexity coupled with three-dimensional hemodynamics in image-derived patient aneurysms and in the presence of virtually implanted interventional devices is presented.

METHODS

The model is developed and presented in two stages. First, a two-dimensional computational model of clotting is presented for an idealized geometry. This enables verification of the methods with existing, physiological data before the pathological state is considered. This model is used to compare the results predicted by two different underlying biochemical cascades. The two-dimensional model is then extended to image-derived, three-dimensional aneurysmal topologies by incorporating level set methods, demonstrating the potential use of this model.

RESULTS AND CONCLUSION

As a proof of concept, comparisons are then made between treated and untreated aneurysms. The prediction of different clotting outcomes for different patients demonstrates that with further development, refinement and validation, this methodology could be used for patient-specific interventional planning.

A continuum model for platelet plug formation, growth and deformation

A numerical framework for modelling platelet plug dynamics is presented in this work. It consists of an extension of a biochemical and plug growth model with a solid mechanics model for the plug coupled with a fluid-structure interaction model for the blood flow-plug system. The platelet plug is treated as a neo-Hookean elastic solid, of which the implementation is based on an updated Lagrangian approach. The framework is applied to different haemodynamic configurations coupled with different shear moduli of the plug. Results about plug growth, shape and size, as well as the stress distribution, are shown. Based on the simulations performed, we conclude that the deformability of the platelet plug is essential for its growth.

Where do the platelets go? A simulation study of fully resolved blood flow through aneurysmal vessels

Despite the importance of platelets in the formation of a thrombus, their transport in complex flows has not yet been studied in detail. In this paper we simulated red blood cells and platelets to explore their transport behaviour in aneurysmal geometries. We considered two aneurysms with different aspect ratios (AR = 1.0, 2.0) in the presence of fast and slow blood flows (Re = 10, 100), and examined the distributions of the cells. Low velocities in the parent vessel resulted in a large stagnation zone inside the cavity, leaving the initial distribution almost unchanged. In fast flows, an influx of platelets into the aneurysm was observed, leading to an elevated concentration. The connection of the platelet-rich cell-free layer (CFL) with the outer regions of the recirculation zones leads to their increased platelet concentration. These platelet-enhanced recirculation zones produced a diverse distribution of cells inside the aneurysm, for the different aspect ratios. A thin red blood CFL that was occupied by platelets was observed on the top of the wide-necked aneurysm, whereas a high-haematocrit region very close to the vessel wall was present in the narrow-necked case. The simulations revealed that non-trivial distributions of red blood cells and platelets are possible inside aneurysmal geometries, giving rise to several hypotheses on the formation of a thrombus, as well as to the wall weakening and the possible rupture of an aneurysm.

Virtual treatment of basilar aneurysms using shape memory polymer foam

Numerical simulations are performed on patient-specific basilar aneurysms that are treated with shape memory polymer (SMP) foam. In order to assess the post-treatment hemodynamics, two modeling approaches are employed. In the first, the foam geometry is obtained from a micro-CT scan and the pulsatile blood flow within the foam is simulated for both Newtonian and non-Newtonian viscosity models. In the second, the foam is represented as a porous media continuum, which has permeability properties that are determined by computing the pressure gradient through the foam geometry over a range of flow speeds comparable to those of in vivo conditions. Virtual angiography and additional post-processing demonstrate that the SMP foam significantly reduces the blood flow speed within the treated aneurysms, while eliminating the high-frequency velocity fluctuations that are present within the pre-treatment aneurysms. An estimation of the initial locations of thrombus formation throughout the SMP foam is obtained by means of a low fidelity thrombosis model that is based upon the residence time and shear rate of blood. The Newtonian viscosity model and the porous media model capture similar qualitative trends, though both yield a smaller volume of thrombus within the SMP foam.

A review of macroscopic thrombus modeling methods

Hemodynamics applied to mechanobiology offers powerful means to predict thrombosis, and to understand the kinetics of thrombus formation on areas of vascular damage in blood flowing through the human circulatory system. Specifically, the advances in computational processing and the progress in modeling complex biological processes with spatio-temporal multi-scale methods have the potential to shift the way in which cardiovascular diseases are diagnosed and treated. This article systematically surveys the state of the art of macroscopic computational fluid dynamics (CFD) Computational fluid dynamics techniques for modeling thrombus formation, highlighting their strengths and weaknesses. In particular, a comprehensive and systematic revision of the hemodynamics models and methods is given, and the strengths and weaknesses of those employed for studying thrombus formation are highlighted.

Using computational fluid dynamics to evaluate a novel venous cannula (Smart canula) for use in cardiopulmonary bypass operating procedures

Peripheral access cardiopulmonary bypass (CPB) is initiated with percutaneous cannulae (CTRL) and venous drainage is often impeded due to smaller vessel and cannula size. A new cannula (Smartcanula, SC) was developed which can change shape in situ and, therefore, may improve venous drainage. Its performance was evaluated using a 2-D computational fluid dynamics (CFD) model. The Navier-Stokes equations could be simplified due to the fact that we use a steady state and a 2-dimensional system while the equation of continuity (p constant) was also simplified. We compared the results of the SC to the CTRL using CFDRC (Version 6.6, CFDRC research corporation, Huntsville, USA) at two preloads (300 and 700 Pa). The SC's mass flow rate outperformed the CTRL by 12.1% and 12.2% at a pressures of 300 and 700 Pa, respectively. At 700 Pa, a pressure gradient of 50% was measured for the CTRL and 11% for the SC. The mean velocity at the 700 Pa for the CTRL was 1.0 m.s(-1) at exit while the SC showed an exit velocity of 1.3 m.s(-1). Shear rates inside the cannulae were similar between the two cannulae. In conclusion, the prototype shows greater mass flow rates compared to the classic cannula; thus, it is more efficient. This is also advocated by a better pressure gradient and higher average velocities. By reducing cannula-tip surface area or increasing hole surface area, greater flow rates are achieved.