Computational modeling of thrombosis as a tool in the design and optimization of vascular implants

Fibrin polymerization simulation using a reactive dissipative particle dynamics method

The study on the polymerization of fibrinogen molecules into fibrin monomers and eventually a stable, mechanically robust fibrin clot is a persistent and enduring topic in the field of thrombosis and hemostasis. Despite many research advances in fibrin polymerization, the change in the structure of fibrin clots and its influence on the formation of a fibrous protein network are still poorly understood. In this paper, we develop a new computational method to simulate fibrin clot polymerization using dissipative particle dynamics simulations. With an effective combination of reactive molecular dynamics formularies and many body dissipative particle dynamics principles, we constructed the reactive dissipative particle dynamics (RDPD) model to predict the complex network formation of fibrin clots and branching of the fibrin network. The 340 kDa fibrinogen molecule is converted into a spring-bead coarse-grain system with 11 beads using a topology representing network algorithm, and using RDPD, we simulated polymerization and formation of the fibrin clot. The final polymerized structure of the fibrin clot qualitatively agrees with experimental results from the literature, and to the best of our knowledge this is the first molecular-based study that simulates polymerization and structure of fibrin clots.

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.

Device thrombosis and pre-clinical blood flow models for assessing antithrombogenic efficacy of drug-device combinations

Thrombosis associated with blood-contacting devices is a complex process involving several component interactions that have eluded precise definition. Extensive investigations of individual biological modules such as protein adsorption, coagulation cascade activation and platelet activation/adhesion/aggregation have provided an initial foundation for developing biomaterials for blood-contacting devices, but a material that is intrinsically non-thrombogenic is yet to be developed. The well-recognized association between fluid dynamics parameters such as shear stress, vortices, stagnation and thrombotic processes such as platelet aggregation and coagulation aggravate thrombosis on most device geometries that elicit these flow disturbances. Thus, antithrombotic drugs that were developed to treat thrombosis associated with vascular diseases such as atherosclerosis have also been adapted to mitigate the risk of device thrombosis. However, balancing the risk of bleeding with the antithrombotic efficacy of these drugs continues to be a challenge, and surface modification of devices with these drug molecules to mitigate device thrombosis locally has been explored. Pre-clinical blood flow models to test the effectiveness of these drug-device combinations have also evolved and several in-vitro, ex-vivo, and in-vivo test configurations are available with their attendant merits and limitations. Despite considerable efforts toward iterative design and testing of blood contacting devices and antithrombogenic surface modifications, device thrombosis remains an unsolved problem.

Towards the patient-specific design of flow diverters made from helix-like wires: an optimization study

Background

Flow diverter (FD) intervention is an emerging endovascular technique for treating intracranial aneurysms. High flow-diversion efficiency is desired to accelerate thrombotic occlusion inside the aneurysm; however, the risk of post-stenting stenosis in the parent artery is posed when flow-diversion efficiency is pursued by simply decreasing device porosity. For improving the prognosis of FD intervention, we develop an optimization method for the design of patient-specific FD devices that maintain high levels of porosity.

Methods

An automated structure optimization method for FDs with helix-like wires was developed by applying a combination of lattice Boltzmann fluid simulation and simulated annealing procedure. Employing intra-aneurysmal average velocity as the objective function, the proposed method tailored the wire structure of an FD to a given vascular geometry by rearranging the starting phase of the helix wires.

Results

FD optimization was applied to two idealized (S and C) vascular models and one realistic (R) model. Without altering the original device porosity of 80%, the flow-reduction rates of optimized FDs were improved by 5, 2, and 28% for the S, C, and R models, respectively. Furthermore, the aneurysmal flow patterns after optimization exhibited marked alterations. We confirmed that the disruption of bundle of inflow is of great help in blocking aneurysmal inflow. Axial displacement tests suggested that the optimal FD implanted in the R model possesses good robustness to tolerate uncertain axial positioning errors.

Conclusions

The optimization method developed in this study can be used to identify the FD wire structure with the optimal flow-diversion efficiency. For a given vascular geometry, custom-designed FD structure can maximally reduce the aneurysmal inflow with its porosity maintained at a high level, thereby lowering the risk of post-stenting stenosis. This method facilitates the study of patient-specific designs for FD devices.

Mechanical Circulatory Support for Advanced Heart Failure: Are We about to Witness a New "Gold Standard"?

The impact of left ventricular assist devices (LVADs) for the treatment of advanced heart failure has played a significant role as a bridge to transplant and more recently as a long-term solution for non-eligible candidates. Continuous flow left ventricular assist devices (CF-LVADs), based on axial and centrifugal design, are currently the most popular devices in view of their smaller size, increased reliability and higher durability compared to pulsatile flow left ventricular assist devices (PF-LVADs). The trend towards their use is increasing. Therefore, it has become mandatory to understand the physics and the mathematics behind their mode of operation for appropriate device selection and simulation set up. For this purpose, this review covers some of these aspects. Although very successful and technologically advanced, they have been associated with complications such as pump thrombosis, haemolysis, aortic regurgitation, gastro-intestinal bleeding and arterio-venous malformations. There is perception that the reduced arterial pulsatility may be responsible for these complications. A flow modulation control approach is currently being investigated in order to generate pulsatility in rotary blood pumps. Thrombus formation remains the most feared complication that can affect clinical outcome. The development of a preoperative strategy aimed at the reduction of complications and patient-device suitability may be appropriate. Patient-specific modelling based on 3D reconstruction from CT-scan combined with computational fluid dynamic studies is an attractive solution in order to identify potential areas of stagnation or challenging anatomy that could be addressed to achieve the desired outcome. The HeartMate II (axial) and the HeartWare HVAD (centrifugal) rotary blood pumps have been now used worldwide with proven outcome. The HeartMate III (centrifugal) is now emerging as the new promising device with encouraging preliminary results. There are now enough pumps on the market: it is time to focus on the complications in order to achieve the full potential and selling-point of this type of technology for the treatment of the increasing heart failure patient population.

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.

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 comprehensive study on different modelling approaches to predict platelet deposition rates in a perfusion chamber

Thrombus formation is a multiscale phenomenon triggered by platelet deposition over a protrombotic surface (eg. a ruptured atherosclerotic plaque). Despite the medical urgency for computational tools that aid in the early diagnosis of thrombotic events, the integration of computational models of thrombus formation at different scales requires a comprehensive understanding of the role and limitation of each modelling approach. We propose three different modelling approaches to predict platelet deposition. Specifically, we consider measurements of platelet deposition under blood flow conditions in a perfusion chamber for different time periods (3, 5, 10, 20 and 30 minutes) at shear rates of 212 s⁻¹, 1390 s⁻¹ and 1690 s⁻¹. Our modelling approaches are: i) a model based on the mass-transfer boundary layer theory; ii) a machine-learning approach; and iii) a phenomenological model. The results indicate that the three approaches on average have median errors of 21%, 20.7% and 14.2%, respectively. Our study demonstrates the feasibility of using an empirical data set as a proxy for a real-patient scenario in which practitioners have accumulated data on a given number of patients and want to obtain a diagnosis for a new patient about whom they only have the current observation of a certain number of variables.

Animals Used in Research and Education, 1966-2016: Evolving Attitudes, Policies, and Relationships

Since the inception of the Association of American Veterinary Medical Colleges (AAVMC), the use of animals in research and education has been a central element of the programs of member institutions. As veterinary education and research programs have evolved over the past 50 years, so too have societal views and regulatory policies. AAVMC member institutions have continually responded to these events by exchanging best practices in training their students in the framework of comparative medicine and the needs of society. Animals provide students and faculty with the tools to learn the fundamental knowledge and skills of veterinary medicine and scientific discovery. The study of animal models has contributed extensively to medicine, veterinary medicine, and basic sciences as these disciplines seek to understand life processes. Changing societal views over the past 50 years have provided active examination and continued refinement of the use of animals in veterinary medical education and research. The future use of animals to educate and train veterinarians will likely continue to evolve as technological advances are applied to experimental design and educational systems. Natural animal models of both human and animal health will undoubtedly continue to serve a significant role in the education of veterinarians and in the development of new treatments of animal and human disease. As it looks to the future, the AAVMC as an organization will need to continue to support and promote best practices in the humane care and appropriate use of animals in both education and research.

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.

Modelling the influence of endothelial heterogeneity on the progression of arterial disease: application to abdominal aortic aneurysm evolution

We sophisticate a fluid-solid growth computational framework for modelling aneurysm evolution. A realistic structural model of the arterial wall is integrated into a patient-specific geometry of the vasculature. This enables physiologically representative distributions of haemodynamic stimuli, obtained from a rigid-wall computational fluid dynamics analysis, to be linked to growth and remodelling algorithms. Additionally, a quasistatic structural analysis quantifies the cyclic deformation of the arterial wall so that collagen growth and remodelling can be explicitly linked to the cyclic deformation of vascular cells. To simulate aneurysm evolution, degradation of elastin is driven by reductions in wall shear stress (WSS) below homeostatic thresholds. Given that the endothelium exhibits spatial and temporal heterogeneity, we propose a novel approach to define the homeostatic WSS thresholds: We allow them to be spatially and temporally heterogeneous. We illustrate the application of this novel fluid-solid growth framework to model abdominal aortic aneurysm (AAA) evolution and to examine how the influence of the definition of the WSS homeostatic threshold influences AAA progression. We conclude that improved understanding and modelling of the endothelial heterogeneity is important for modelling aneurysm evolution and, more generally, other vascular diseases where haemodynamic stimuli play an important role.