Heterogeneous Porous Media Simulation

Intracranial aneurysms are vascular disorders in which weakness in the wall of a cerebral artery or vein causes a localized dilation of the blood vessel. Flow diversion is an endovascular technique where a flow diverter stent is placed in the parent blood vessel to divert blood flow away from the aneurysm itself. Simulation by computational fluid dynamics is an attractive method to study flow diverters, particularly to model the small gaps between stent struts as a porous media. In many cases obstructions are not equal across the free medium and the porous one must be heterogeneous. Finite Volume Method solves numerical problems of computational fluid dynamics, splitting the region of interest in cells of small volumes. Porous media are usually modeled as a set of simulation cells described in a dictionary with constant porosity parameters (Homogeneous medium). An heterogeneous medium can be described as multiple homogeneous media, one by one. However, creating multiple homogeneous porous media is a tedious job if each simulation cell requires different parameters. Also, porous medium sets creates overheads on memory and processor load. The open source tool OpenFOAM is a open source C++ toolbox for field operations and partial differential equations solving using Finite Volume Method, including computational fluid dynamics. The tool is well prepared to describe heterogeneous fields. In this work, porous media coefficients are described as tensor fields. A steady state flow solver considering this fields is developed. The fidelity of the solver is then studied qualitatively and quantitatively.Fil: Dazeo, Nicolás Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Dottori, Javier Alejandro. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Boroni, Gustavo Adolfo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Larrabide, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentin

Which spring is the best? Comparison of methods for virtual stenting.

This paper presents a methodology for modeling the deployment of implantable devices used in minimally invasive vascular interventions. Motivated by the clinical need to perform preinterventional rehearsals of a stent deployment, we have developed methods enabling virtual device placement inside arteries, under the constraint of real-time application. This requirement of rapid execution narrowed down the search for a suitable method to the concept of a dynamic mesh. Inspired by the idea of a mesh of springs, we have found a novel way to apply it to stent modeling. The experiments conducted in this paper investigate properties of the stent models based on three different spring types: lineal, semitorsional, and torsional springs. Furthermore, this paper compares the results of various deployment scenarios for two different classes of devices: a stent graft and a flow diverter. The presented results can be of a high-potential clinical value, enabling the predictive evaluation of the outcome of a stent deployment treatment

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

The effects of stent porosity on the endovascular treatment of intracranial aneurysms located near a bifurcation

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Machine learning and reduced order modelling for the simulation of braided stent deployment

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages. It consists of a first classification step to determine a priori whether a simulation will be successful (good conformity between stent and vessel) or not from a clinical perspective, followed by a regression step that provides an approximated solution of the deployed stent configuration. The latter is achieved using a non-intrusive reduced order modelling scheme that combines the proper orthogonal decomposition algorithm and Gaussian process regression. The workflow was validated on an idealised intracranial artery with a saccular aneurysm and the effect of six geometrical and surgical parameters on the outcome of stent deployment was studied. The two-step workflow allows the classification of deployment conditions with up to 95% accuracy and real-time prediction of the stent deployed configuration with an average prediction error never greater than the spatial resolution of 3D rotational angiography (0.15 mm). These results are promising as they demonstrate the ability of these techniques to achieve simulations within a few milliseconds while retaining the mechanical realism and predictability of the stent deployed configuration

Modeling, Simulation and Validation of a Bio-Inspired and Self-Powered Miniature Pressure Sensing System for Monitoring Cerebral Intra Aneurysmal Pressure

Intracranial aneurysm rupture is one of the main cause for the intracranial bleeding. A brain aneurysm is an abnormal focal bulging of the arteries in the brain. As an aneurysm grows, its wall becomes thinner and weaker, which is more prone to rupture. Rupture of the intracranial aneurysm leads to releasing blood into the spaces around the brain - called a subarachnoid hemorrhage (SAH). 10 to 15% of the patients with subarachnoid hemorrhage die immediately. To prevent aneurysmal bleeding, it is essential to seclude the aneurysm from the blood circulation. This can be done with open craniotomy with microsurgical clipping and minimally invasive endovascular surgery. One of endovascular surgical technique is to place stent/flow-diverter across the neck of the aneurysm. The stent across the aneurysm reduces the flow within the aneurysm and help to form the thrombus within the aneurysm. However, approximately 3% people with the flow- diverter treatment may have delayed aneurysm bleeding after the stent placement. Short-term studies show that the stents can reduce the flow within the aneurysm but not the pressure. Currently there is no other device available to measure the intracranial intraaneurysmal pressure. This work is on designing a bio-inspired, self-powered, passively operated PVDF pressure sensor that can be deployed within the aneurysm, during flow diverting endovascular treatment that is very sensitive to small changes in pressure. The design utilizes the ear mechanics benefits by consisting of the circular vibrating membrane which vibrates based on the intraaneursymal pressure changes. This mimic the tympanic membrane part of the ear. The design continues to follow the middle ear’s mechanical advantage mechanism by incorporating the surface area increase and leverage mechanism, by the other side of the vibrating membrane been connected to three pole-links structures similar to the three bones of the middle ear to perform the middle ear’s amplification mechanism. This is followed by a composite cantilever beam structure with the sensor strips, which mimics the coiled cochlea of the inner ear in elongated form. This piezoelectric sensor strips are responsible for the passive mechanoelectrical conversion and generation of electric voltage, for the intraaneursymal pressure change application. Simulation, experiments and analysis at every level are done. Simulation and experimental result correlate and match the modeling

Understanding the role of hemodynamics in the initiation, progression, rupture, and treatment outcome of cerebral aneurysm from medical iamge-based computational studies

About a decade ago, the first image-based computational hemodynamic studies of cerebral aneurysms were presented. Their potential for clinical applications was the results of a right combination of medical image processing, vascular reconstruction, and grid generation techniques used to reconstruct personalziaed domains for computational fluid and solid dynamics solvers and data analysis and visualization techniques. A considerable number of studies have captivated the attention of clinicians, neurosurgeons, and neuroradiologists, who realized the ability of those tools to help in understanding the role played by hemodynamics in the natural history and management of intracranial aneurysms. This paper intends to summarize the most relevant results in the filed reported during the last years.Fil: Castro, Marcelo Adrian. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Computational Fluid Dynamics in Cardiovascular Disease

Computational fluid dynamics (CFD) is a mechanical engineering field for analyzing fluid flow, heat transfer, and associated phenomena, using computer-based simulation. CFD is a widely adopted methodology for solving complex problems in many modern engineering fields. The merit of CFD is developing new and improved devices and system designs, and optimization is conducted on existing equipment through computational simulations, resulting in enhanced efficiency and lower operating costs. However, in the biomedical field, CFD is still emerging. The main reason why CFD in the biomedical field has lagged behind is the tremendous complexity of human body fluid behavior. Recently, CFD biomedical research is more accessible, because high performance hardware and software are easily available with advances in computer science. All CFD processes contain three main components to provide useful information, such as pre-processing, solving mathematical equations, and post-processing. Initial accurate geometric modeling and boundary conditions are essential to achieve adequate results. Medical imaging, such as ultrasound imaging, computed tomography, and magnetic resonance imaging can be used for modeling, and Doppler ultrasound, pressure wire, and non-invasive pressure measurements are used for flow velocity and pressure as a boundary condition. Many simulations and clinical results have been used to study congenital heart disease, heart failure, ventricle function, aortic disease, and carotid and intra-cranial cerebrovascular diseases. With decreasing hardware costs and rapid computing times, researchers and medical scientists may increasingly use this reliable CFD tool to deliver accurate results. A realistic, multidisciplinary approach is essential to accomplish these tasks. Indefinite collaborations between mechanical engineers and clinical and medical scientists are essential. CFD may be an important methodology to understand the pathophysiology of the development and progression of disease and for establishing and creating treatment modalities in the cardiovascular field

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