Hemodynamic study in a real intracranial aneurysm: an in vitro and in silico approach

Mestrado de dupla diplomação com o Centro Federal de Educação Tecnológica Celso Suckow da Fonseca - Cefet/RJIntracranial aneurysm (IA) is a cerebrovascular disease with high rates of mortality and morbidity when it ruptures. It is known that changes in the intra-aneurysmal hemodynamic load play a significant factor in the development and rupture of IA. However, these factors are not fully understood. In this sense, the main objective of this work is to study the hemodynamic behavior during the blood analogues flow inside an AI and to determine its influence on the evolution of this pathology. To this end, experimental and numerical studies were carried out, using a real AI model obtained using computerized angiography. In the experimental approach, it was necessary, in the initial phase, to develop and manufacture biomodels from medical images of real aneurysms. Two techniques were used to manufacture the biomodels: rapid prototyping and gravity casting. The materials used to obtain the biomodels were of low cost. After manufacture, the biomodels were compared to each other for their transparency and final structure and proved to be suitable for testing flow visualizations. Numerical studies were performed with the aid of the Ansys Fluent software, using computational fluid dynamics (CFD), using the finite volume method. Subsequently, flow tests were performed experimentally and numerically using flow rates calculated from the velocity curve of a patient's doppler test. The experimental and numerical tests, in steady-state, made it possible to visualize the three-dimensional behavior of the flow inside the aneurysm, identifying the vortex zones created throughout the cardiac cycle. Correlating the results obtained in the two analyzes, it was possible to identify that the areas of vortexes are characterized by low speed and with increasing the fluid flow, the vortexes are positioned closer to the wall. These characteristics are associated with the rupture of an intracranial aneurysm. There was also a good qualitative correlation between numerical and experimental results.O aneurisma intracraniano (AI) é uma patologia cerebrovascular com altas taxas de mortalidade e morbidade quando se rompe. Sabe-se que alterações na carga hemodinâmica intra-aneurismática exerce um fator significativo no desenvolvimento e ruptura de AI, porém, esses fatores não estão totalmente compreendidos. Nesse sentido, o objetivo principal deste trabalho é o de estudar o comportamento hemodinâmico durante o escoamento de fluidos análogos do sangue no interior de um AI e determinar a sua influência na evolução da patologia. Para tal, foram realizados estudos experimentais e numéricos, utilizando um modelo de AI real obtido por meio de uma angiografia computadorizada. Na abordagem experimental foi necessário, na fase inicial, desenvolver e fabricar biomodelos a partir de imagens médicas de um aneurisma real. No fabrico dos biomodelos foram utilizadas duas técnicas: a prototipagem rápida e o vazamento por gravidade. Os materiais utilizados para a obtenção dos biomodelos foram de baixo custo. Após a fabricação, os biomodelos foram comparados entre si quanto à sua transparência e estrutura final e verificou-se serem adequados para testes de visualizações do fluxo. Os estudos numéricos foram realizados com recurso ao software Ansys Fluent, utilizando a dinâmica dos fluidos computacional (CFD), através do método dos volumes finitos. Posteriormente, foram realizados testes de escoamento experimentais e numéricos, utilizando caudais determinados a partir da curva de velocidades do ensaio doppler de um paciente. Os testes experimentais e numéricos, em regime permanente, possibilitaram a visualização do comportamento tridimensional do fluxo no interior do aneurisma, identificando as zonas de vórtices criadas ao longo do ciclo cardíaco. Correlacionando os resultados obtidos nas duas análises, foi possível identificar que as áreas de vórtices são caracterizadas por uma baixa velocidade e com o aumento do caudal os vórtices posicionam-se mais próximos da parede. Essas características apresentadas estão associadas com a ruptura de aneurisma intracraniano. Verificou-se, também, uma boa correlação qualitativa entre os resultados numéricos e experimentais

Decomposition of Velocity Field Along a Centerline Curve Using Frenet-Frames: Application to Arterial Blood Flow Simulations

This paper presents a novel method for the evaluation of three-dimensional blood-flow simulations based, on the decomposition of the velocity field into localized coordinate systems along the vessels centerline. The method is based on the computation of accurate centerlines with the Vascular Modeling Toolkit (VMTK) library, to calculate the localized Frenet-frames along the centerline and the morphological features, namely the curvature and torsion. Using the Frenet-frame unit vectors, the velocity field can be decomposed into axial, circumferential and radial components and visualized in a diagram along the centerline. This paper includes case studies with four idealized geometries resembling the carotid siphon and two patient-specific cases to demonstrate the capability of the method and the connection between morphology and flow. The proposed evaluation method presented in this paper can be easily extended to other derived quantities of the velocity fields, such as the wall shear stress field. Furthermore, it can be used in other fields of engineering with tubular cross-sections with complex torsion and curvature distribution

Atrial Fibrillation and Cognitive Decline: a Computational Hemodynamics Investigation

Background: Atrial fibrillation (AF) is a prevalent cardiac disease which has been associated with increased risk of dementia and cognitive decline. We hypothesize that atrial fibrillation leads to regional transient hypoperfusion events in the brain, and that geometric variations in the arterial structure called the Circle of Willis (CoW) play a role in these events. Methods: A computational model was developed to simulate cerebral blood flow in six common variations of the CoW. Risk was assessed based on frequency of beat-wise regional hypoperfusion events during AF, and sensitivity analysis was performed with respect to this model output. Results: A key artery in the CoW, called the A1 segment, was found to play the most important role in cerebral perfusion. Intrinsic heart rate was also found to influence the frequency of hypoperfusion events. Conclusions: Our results suggest that heart rate and CoW geometry play important roles influencing cerebral hemodynamics during AF

Novel Algorithms for Merging Computational Fluid Dynamics and 4D Flow MRI

Time-resolved three-dimensional spatial encoding combined with three-directional velocity-encoded phase contrast magnetic resonance imaging (termed as 4D flow MRI), can provide valuable information for diagnosis, treatment, and monitoring of vascular diseases. The accuracy of this technique, however, is limited by errors in flow estimation due to acquisition noise as well as systematic errors. Furthermore, available spatial resolution is limited to 1.5mm - 3mm and temporal resolution is limited to 30-40ms. This is often grossly inadequate to resolve flow details in small arteries, such as those in cerebral circulation. Recently, there have been efforts to address the limitations of the spatial and temporal resolution of MR flow imaging through the use of computational fluid dynamics (CFD). While CFD is capable of providing essentially unlimited spatial and temporal resolution, numerical results are very sensitive to errors in estimation of the flow boundary conditions. In this work, we present three novel techniques that combine CFD with 4D flow MRI measurements in order to address the resolution and noise issues. The first technique is a variant of the Kalman Filter state estimator called the Ensemble Kalman Filter (EnKF). In this technique, an ensemble of patient-specific CFD solutions are used to compute filter gains. These gains are then used in a predictor-corrector scheme to not only denoise the data but also increase its temporal and spatial resolution. The second technique is based on proper orthogonal decomposition and ridge regression (POD-rr). The POD method is typically used to generate reduced order models (ROMs) in closed control applications of large degree of freedom systems that result from discretization of governing partial differential equations (PDE). The POD-rr process results in a set of basis functions (vectors), that capture the local space of solutions of the PDE in question. In our application, the basis functions are generated from an ensemble of patient-specific CFD solutions whose boundary conditions are estimated from 4D flow MRI data. The CFD solution that should be most closely representing the actual flow is generated by projecting 4D flow MRI data onto the basis vectors followed by reconstruction in both MRI and CFD resolution. The rr algorithm was used for between resolution mapping. Despite the accuracy of using rr as the mapping step, due to manual adjustment of a coefficient in the algorithm we developed the third algorithm. In this step, the rr algorithm was substituded with a dynamic mode decomposition algorithm to preserve the robustness. These algorithms have been implemented and tested using a numerical model of the flow in a cerebral aneurysm. Solutions at time intervals corresponding to the 4D flow MRI temporal resolution were collected and downsampled to the spatial resolution of the imaging data. A simulated acquisition noise was then added in k-space. Finally, the simulated data affected by noise were used as an input to the merging algorithms. Rigorous comparison to state-of-the-art techniques were conducted to assess the accuracy and performance of the proposed method. The results provided denoised flow fields with less than 1\% overall error for different signal-to-noise ratios. At the end, a small cohort of three patients were corrected and the data were reconstructed using different methods, the wall shear stress (WSS) was calculated using different reconstructed data and the results were compared. As it has been shown in chapter 5, the calculated WSS using different methods results in mutual high and low shear stress regions, however, the exact value and patterns are significantly different

Computational investigations of a shape‐memory polymer foam embolization device for intracranial aneurysms

The objective of this research is to determine the efficacy of an intracranial aneurysm treatment option. An open‐source computational fluid dynamics software is used to simulate blood flow through 6 patient‐specific intracranial aneurysm geometries for 42 different cases. Virtual shape memory polymer foam embolization devices are created and implanted into the geometries. Different porous media parameters are considered for the embolic devices, and it is found that devices with a permeability of ∼5e-9 m2 can reduce aneurysmal inflow by 90% for various geometries of the treated aneurysm and its surrounding parent arterial vessel. For a wide‐necked aneurysm, devices with a permeability of 60%, indicating that they may be able to provide that level of performance for most aneurysm morphologies. As such, a permeability range of 5e-9–5e-8 m2 is recommended for the device. Furthermore, material removal from the center of the device is found to be feasible for larger aneurysm devices if compressibility is deemed a concern. For a high‐inflow case, the average aneurysmal velocity reduction is within 2% of the uncored device for all cored devices with a material thickness of at least 1.5 mm occluding the inlet area. Convective heat transfer is also modeled to determine the safety of the thermally stimulated shape memory polymer device. Steady‐state simulations identify the worst‐case geometry, a deep aneurysm with little opportunity for convection. Transient heat transfer during the device deployment process for 2 stimulus temperatures is modeled with this aneurysm, demonstrating that the vessel walls can reach the stimulus temperature of 40 °C and 45 °C within seconds and take over a minute to cool back to near body temperature. The threshold for brain tissue damage is not reached, but nonetheless, it is suggested that the temperature and heating time be kept as low as possible. Full model validation is not available, but general verification of the flow fields in untreated aneurysms is achieved by comparing simulation results to those obtained by other research groups in a modeling competition

Lattice-Boltzmann simulations of cerebral blood flow

Computational haemodynamics play a central role in the understanding of blood behaviour in the cerebral vasculature, increasing our knowledge in the onset of vascular diseases and their progression, improving diagnosis and ultimately providing better patient prognosis. Computer simulations hold the potential of accurately characterising motion of blood and its interaction with the vessel wall, providing the capability to assess surgical treatments with no danger to the patient. These aspects considerably contribute to better understand of blood circulation processes as well as to augment pre-treatment planning. Existing software environments for treatment planning consist of several stages, each requiring significant user interaction and processing time, significantly limiting their use in clinical scenarios. The aim of this PhD is to provide clinicians and researchers with a tool to aid in the understanding of human cerebral haemodynamics. This tool employs a high performance fluid solver based on the lattice-Boltzmann method (coined HemeLB), high performance distributed computing and grid computing, and various advanced software applications useful to efficiently set up and run patient-specific simulations. A graphical tool is used to segment the vasculature from patient-specific CT or MR data and configure boundary conditions with ease, creating models of the vasculature in real time. Blood flow visualisation is done in real time using in situ rendering techniques implemented within the parallel fluid solver and aided by steering capabilities; these programming strategies allows the clinician to interactively display the simulation results on a local workstation. A separate software application is used to numerically compare simulation results carried out at different spatial resolutions, providing a strategy to approach numerical validation. This developed software and supporting computational infrastructure was used to study various patient-specific intracranial aneurysms with the collaborating interventionalists at the National Hospital for Neurology and Neuroscience (London), using three-dimensional rotational angiography data to define the patient-specific vasculature. Blood flow motion was depicted in detail by the visualisation capabilities, clearly showing vortex fluid ow features and stress distribution at the inner surface of the aneurysms and their surrounding vasculature. These investigations permitted the clinicians to rapidly assess the risk associated with the growth and rupture of each aneurysm. The ultimate goal of this work is to aid clinical practice with an efficient easy-to-use toolkit for real-time decision support

Modeling and hexahedral meshing of cerebral arterial networks from centerlines

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both the geometric and topological information and facilitates manual editing. In this work, we propose an automatic method to generate a structured hexahedral mesh suitable for CFD directly from centerlines. We addressed both the modeling and meshing tasks. We proposed a vessel model based on penalized splines to overcome the limitations inherent to the centerline representation, such as noise and sparsity. The bifurcations are reconstructed using a parametric model based on the anatomy that we extended to planar n-furcations. Finally, we developed a method to produce a volume mesh with structured, hexahedral, and flow-oriented cells from the proposed vascular network model. The proposed method offers better robustness to the common defects of centerlines and increases the mesh quality compared to state-of-the-art methods. As it relies on centerlines alone, it can be applied to edit the vascular model effortlessly to study the impact of vascular geometry and topology on hemodynamics. We demonstrate the efficiency of our method by entirely meshing a dataset of 60 cerebral vascular networks. 92% of the vessels and 83% of the bifurcations were meshed without defects needing manual intervention, despite the challenging aspect of the input data. The source code is released publicly

IMPACT OF HEMODYNAMIC VORTEX SPATIAL AND TEMPORAL CHARACTERISTICS ON ANALYSIS OF INTRACRANIAL ANEURYSMS

Subarachnoid hemorrhage is a potentially devastating pathological condition in which bleeding occurs into the space surrounding the brain. One of the prominent sources of subarachnoid hemorrhage are intracranial aneurysms (IA): degenerative, irregular expansions of area(s) of the cerebral vasculature. In the event of IA rupture, the resultant subarachnoid hemorrhage ends in patient mortality occurring in ~50% of cases, with survivors enduring significant neurological damage with physical or cognitive impairment. The seriousness of IA rupture drives a degree of clinical interest in understanding these conditions that promote both the development and possible rupture of the vascular malformations. Current metrics for the assessment of this pathology rely on measuring the geometric characteristics of a patient\u27s vessel and/or IA, as well as the hemodynamic stressors existing along the vessel wall. Comparatively less focus has been granted toward understanding the characteristics of much of the bulk-flow within the vasculature and how it may play a role in IAs. Specifically, swirling hemodynamic flow (vortices) have been suggested as a condition which exacerbates vascular changes leading to IAs, yet quantified measurements of the spatial and temporal characteristics of vortices remain overlooked. This dissertation studies the role of the spatial and temporal characteristics of vortex flow and how it plays a role on IA pathology. Its chapters are a collection of five (5) works into this matter. First, established methods for the identification of vortices was investigated, and a novel method for vortex identification and quantification of their characteristics was developed to overcome the limitations of previous methods. Second, the developed method for vortex identification/quantification was then applied to a simulation study to improve predictive models aimed at predicting areas of IA development from those unlikely to suffer this pathology. Third, assessing how the simulated repair of one IA impacts changes to hemodynamic conditions within other nearby un-repaired IAs in a multiple IA system. Fourth, it was determined if vortex identification/quantification improved predictive models aimed at differentiation ruptured from unruptured IAs. Fifth, impart vortical flow of differing characteristics onto cultured vascular cells to determine if vortex stability imparts varied levels of cellular changes