An innovative approach to simulate thrombosis with smoothed particle hydrodynamics

La trombosi è una patologia che porta alla formazione di coaguli, che possono provocare ostruzioni arteriose e, infine, migrano attraverso il sistema cardiocircolatorio causando infarto, ictus o embolia polmonare. Il processo è abbastanza complesso ed il suo meccanismo non è ancora chiaro, essendo il risultato dell’interazione tra diversi fattori, compresa l'attivazione e l'aggregazione piastrinica, le reazioni chimiche e l'emodinamica.È fondamentale considerare e ridurre al minimo la formazione di trombi nella progettazione e realizzazione di organi artificiali, come valvole cardiache artificiali o protesi. Lo studio dell'emodinamica può fornire un supporto efficace per identificare e prevenire il rischio di trombosi.A causa della mancanza di soluzioni analitiche adeguate e della complessità degli studi sperimentali, la ricerca evolve sempre più verso l’utilizzo delle simulazioni numeriche Questa tesi mira a modellare la formazione, la crescita e l'evoluzione del trombo mediante il metodo numerico accoppiato Smoothed Particle Hydrodynamics (SPH) usando un modello di interazione fluido-struttura (FSI). Il modello proposto descrive le principali fasi della cascata coagulativa attraverso l'equilibrio di quattro specie biochimiche e tre tipologie di piastrine. Le particelle SPH possono passare dalla fase fluida a quella solida se sono soddisfatte delle specifiche condizioni biochimiche e fisiche. L'accoppiamento fluido-solido è modellato introducendo legami elastici tra le particelle solide senza nessuna interfaccia. Per raggiungere questo obiettivo, in primo luogo il modello viene validato confrontando i risultati numerici con i dati sperimentali disponibili in letteratura, in secondo luogo, il nuovo codice numerico è applicato per descrivere la trombosi in appendice atriale in caso di fibrillazione o come trombosi indotta in aneurismi cerebrali.Thrombosis is a pathology leading to the formation of clots, that can result in arterial obstructions and, eventually, migrate through the cardiocirculatory system causing heart attack, stroke or pulmonary embolism. The process is complex and its mechanism is still unclear, being the result of the interaction between various factors, including platelet activation and aggregation, chemical reactions, and hemodynamics.It is crucial to consider and minimise thrombosis in the design and implementation of artificial organs, such as artificial heart valves, and vascular prostheses. The study of hemodynamics can provide effective support to identify and prevent the risk of thrombosis.Due to the lack of adequate analytical solutions and the complexity of experimental studies, research increasingly evolves towards the use of computational methods.This thesis aims at modelling the formation, growth and evolution of thrombus by means of a Smoothed Particle Hydrodynamics (SPH) numerical method coupled with a fluid-structure interaction (FSI) model. The proposed model describes the main phases of the coagulative cascade through the balance of four biochemical species and three types of platelets. SPH particles can switch from fluid to solid phase whenspecific biochemical and physical conditions are satisfied. Fluid-solid coupling is modelled by introducing elastic binds between solid particles, without requiring detention and management of the interface between the two media.In order to reach this goal, firstly the model is validated by comparing the numerical prediction with experimental data available in the literature, secondly, it is applied to describe thrombosis formation due to relevant pathologies such as atrial fibrillation and cerebral aneurysms where the insertion of flow diverter creates thrombogenic stasis zone

Numerical study of a thrombus migration risk in aneurysm after coil embolization in patient cases: FSI modelling

Purpose There are still many challenges for modelling a thrombus migration process in aneurysms. The main novelty of the present research lies in the modelling of aneurysm clot migration process in a realistic cerebral aneurysm, and the analysis of forces sufered by clots inside an aneurysm, through transient FSI simulations. Methods The blood fow has been modelled using a Womersley velocity profle, and following the Carreau viscosity model. Hyperelastic Ogden model has been used for clot and isotropic linear elastic model for the artery walls. The FSI coupled model was implemented in ANSYS® software. The hemodynamic forces sufered by the clot have been quantifed using eight diferent clot sizes and positions inside a real aneurysm. Results The obtained results have shown that it is almost impossible for clots adjacent to aneurysm walls, to leave the aneurysm. Nevertheless, in clots positioned in the centre of the aneurysm, there is a real risk of clot migration. The risk of migration of a typical post-coiling intervention clot in an aneurysm, in contact with the wall and occupying a signifcant percentage of its volume is very low in the case studied, even in the presence of abnormally intense events, associated with sneezes or impacts. Conclusions The proposed methodology allows evaluating the clot migration risk, vital for evaluating the progress after endovascular interventions, it is a step forward in the personalized medicine, patient follow-up, and helping the medical team deciding the optimal treatment.Universidade de Vigo/CISU

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-silico clinical trials for assessment of intracranial flow diverters

In-silico trials refer to pre-clinical trials performed, entirely or in part, using individualised computer models that simulate some aspect of drug effect, medical device, or clinical intervention. Such virtual trials reduce and optimise animal and clinical trials, and enable exploring a wider range of anatomies and physiologies. In the context of endovascular treatment of intracranial aneurysms, in-silico trials can be used to evaluate the effectiveness of endovascular devices over virtual populations of patients with different aneurysm morphologies and physiologies. However, this requires (i) a virtual endovascular treatment model to evaluate device performance based on a reliable performance indicator, (ii) models that represent intra- and inter-subject variations of a virtual population, and (iii) creation of cost-effective and fully-automatic workflows to enable a large number of simulations at a reasonable computational cost and time. Flow-diverting stents have been proven safe and effective in the treatment of large wide-necked intracranial aneurysms. The presented thesis aims to provide the ingredient models of a workflow for in-silico trials of flow-diverting stents and to enhance the general knowledge of how the ingredient models can be streamlined and accelerated to allow large-scale trials. This work contributed to the following aspects: 1) To understand the key ingredient models of a virtual treatment workflow for evaluation of the flow-diverter performance. 2) To understand the effect of input uncertainty and variability on the workflow outputs, 3) To develop generative statistical models that describe variability in internal carotid artery flow waveforms, and investigate the effect of uncertainties on quantification of aneurysmal wall shear stress, 4) As part of a metric to evaluate success of flow diversion, to develop and validate a thrombosis model to assess FD-induced clot stability, and 5) To understand how a fully-automatic aneurysm flow modelling workflow can be built and how computationally inexpensive models can reduce the computational costs

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.138

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