Using Flow Feature to Extract Pulsatile Blood Flow from 4D Flow MRI Images

4D flow MRI images make it possible to measure pulsatile blood flow inside deforming vessel, which is critical in accurate blood flow visualization, simulation, and evaluation. Such data has great potential to overcome problems in existing work, which usually does not reflect the dynamic nature of elastic vessels and blood flows in cardiac cycles. However, the 4D flow MRI data is often low-resolution and with strong noise. Due to these challenges, few efforts have been successfully conducted to extract dynamic blood flow fields and deforming artery over cardiac cycles, especially for small artery like carotid. In this paper, a robust flow feature, particularly the mean flow intensity is used to segment blood flow regions inside vessels from 4D flow MRI images in whole cardiac cycle. To estimate this flow feature more accurately, adaptive weights are added to the raw velocity vectors based on the noise strength of MRI imaging. Then, based on this feature, target arteries are tracked in at different time steps in a cardiac cycle. This method is applied to the clinical 4D flow MRI data in neck area. Dynamic vessel walls and blood flows are effectively generated in a cardiac cycle in the relatively small carotid arteries. Good image segmentation results on 2D slices are presented, together with the visualization of 3D arteries and blood flows. Evaluation of the method was performed by clinical doctors and by checking flow volume rates in the vertebral and carotid arteries

Patient-specific analysis of the hemodynamic performance of surgical and transcatheter aortic valve replacements

Aortic valve (AV) diseases are life-threatening conditions which affect millions of people worldwide and, if left untreated, can lead to death a few years after symptom onset. Patients affected by AV diseases are commonly referred to surgical AV replacement (SAVR). However, more than 30% of patients are not suitable for SAVR. For this reason, transcatheter aortic valve implantation (TAVI) has been attracting growing interest. Several clinical studies compared the outcomes of these techniques, showing that TAVI could be a valid alternative to SAVR. However, there is a lack of detailed knowledge about changes in the aortic hemodynamic conditions following these procedures. The main aim of this thesis is to develop efficient and robust methodologies to study and compare the influences of different AV replacement procedures on aortic hemodynamics. An image-based patient-specific computational model has been developed, which uses magnetic resonance images (MRI) acquired from patients to obtain realistic geometry and boundary conditions (BCs) for computational fluid dynamics (CFD) analysis. The implemented physiological BCs were compared with the most commonly used inlet and outlet BCs, and showed the best agreement with in vivo data. The model was then applied to study and compare SAVR, TAVI and aortic root replacement using a variety of prostheses. In addition, an experimental set-up was designed to further study TAVI hemodynamics by combining 3D-printing, 4D flow MRI and CFD. Finally, a preliminary analysis of valve leaflet thrombosis was conducted. It has been shown that both TAVI and SAVR are able to greatly improve the aortic hemodynamics, but this often deviates from conditions in healthy volunteers, with the extent of abnormalities strongly dependent on the type of prostheses or valve disease. The work also demonstrated the feasibility of predicting valve leaflet thrombosis using a shear-driven model for thrombus formation and growth.Open Acces

Image Segmentation, Parametric Study, and Supervised Surrogate Modeling of Image-based Computational Fluid Dynamics

Indiana University-Purdue University Indianapolis (IUPUI)With the recent advancement of computation and imaging technology, Image-based computational fluid dynamics (ICFD) has emerged as a great non-invasive capability to study biomedical flows. These modern technologies increase the potential of computation-aided diagnostics and therapeutics in a patient-specific environment. I studied three components of this image-based computational fluid dynamics process in this work. To ensure accurate medical assessment, realistic computational analysis is needed, for which patient-specific image segmentation of the diseased vessel is of paramount importance. In this work, image segmentation of several human arteries, veins, capillaries, and organs was conducted to use them for further hemodynamic simulations. To accomplish these, several open-source and commercial software packages were implemented. This study incorporates a new computational platform, called InVascular, to quantify the 4D velocity field in image-based pulsatile flows using the Volumetric Lattice Boltzmann Method (VLBM). We also conducted several parametric studies on an idealized case of a 3-D pipe with the dimensions of a human renal artery. We investigated the relationship between stenosis severity and Resistive index (RI). We also explored how pulsatile parameters like heart rate or pulsatile pressure gradient affect RI. As the process of ICFD analysis is based on imaging and other hemodynamic data, it is often time-consuming due to the extensive data processing time. For clinicians to make fast medical decisions regarding their patients, we need rapid and accurate ICFD results. To achieve that, we also developed surrogate models to show the potential of supervised machine learning methods in constructing efficient and precise surrogate models for Hagen-Poiseuille and Womersley flows

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