Non-invasive detection and assessment of coronary stenosis from blood mean residence times.

Coronary artery stenosis is an abnormal narrowing of a coronary artery caused by an atherosclerotic lesion that reduces lumen space. Fractional flow reserve (FFR) is the gold standard method to determine the severity of coronary stenosis based on the determination of rest and hyperemic pressure fields, but requires an invasive medical procedure. Normal FFR is 1.0 and FFR RT, to account for varying volume and flow rate of individual segments. BloodRT was computed in 100 patients who had undergone the pressure-wire FFR procedure, and a threshold for BloodRT was determined to assess the physiological significance of a stenosis, analogous to the diagnostic threshold for FFR. The threshold exhibited excellent discrimination in detecting significant from non-significant stenosis compared to the gold standard pressure-wire FFR, with sensitivity of 98% and specificity of 96%. When applied to clinical practice, this could potentially allow practicing cardiologists to accurately assess and quantify the severity of coronary stenosis without resorting to invasive catheter-based techniques. The first 100 patient study required a clinically determined blood flow rate as a key model input. To create a more non-invasive process, a multiple linear regression approach was employed to determine blood flow rate entering a given artery segment. To validate this method, BloodRT was computed for a new set of 100 patients using the regression derived blood flow rate. The sensitivity and specificity were 95% and 97%, respectively, indicating similar discrimination compared to the clinically derived flow rate. The method was also applied to a succession of stenosis in series. When BloodRT of each individual stenosis was well above the threshold for significance, the cumulative effect of all stenoses led to an overall BloodRT below the threshold of hemodynamic significance

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

Dual Antibody Functionalized Polyvinyl Alcohol and Alginate Hydrogels for Synergistic Endothelial Cell Adhesion

Motivated by the need to design minimally-invasive treatments for wide-necked cerebral aneurysms, we used computational modeling to assess aneurysm hemodynamics, examined in vitro cellular responses arising from mechanical and chemical stresses, and designed novel materials that cooperatively adhere to the endothelium. We first hypothesized that because aneurysm geometry plays an important role in hemodynamics, changes in flow patterns may affect the shear stress experienced on the aneurysm wall. We defined flow regimes based on aneurysm hemodynamic and geometric parameters, which may correlate with aneurysm rupture. Because of the direct contact between endothelial cells (ECs) and blood flow, we then evaluated how changes in hemodynamics and inflammatory cytokines affect the expression of cell adhesion molecules (CAMs) and matrix remodeling factors on ECs. We subsequently designed biomaterials that complement the dynamic EC surface and have the ability to conform to any geometry through in situ crosslinking. Antibody-conjugated hydrogels facilitated synergistic EC adhesion using cooperativity as an adhesion strategy. We optimized the presentation of antibodies to inflammatory CAMs on polyvinyl alcohol (PVA) and alginate hydrogels to achieve strong adhesion to inflamed ECs. We synthesized photocrosslinkable, aminated PVA hydrogels and determined the effect of substrate stiffness on cell adhesion. We also evaluated the effects of antibody presentation on cell adhesion strength and dynamics using alginate hydrogels. Taken together, the results of this work may be used to design hydrogels for vascular remodeling applications under shear stress, including embolic agents for cerebral aneurysms.Engineering and Applied Science

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

SOLID-SHELL FINITE ELEMENT MODELS FOR EXPLICIT SIMULATIONS OF CRACK PROPAGATION IN THIN STRUCTURES

Crack propagation in thin shell structures due to cutting is conveniently simulated using explicit finite element approaches, in view of the high nonlinearity of the problem. Solidshell elements are usually preferred for the discretization in the presence of complex material behavior and degradation phenomena such as delamination, since they allow for a correct representation of the thickness geometry. However, in solid-shell elements the small thickness leads to a very high maximum eigenfrequency, which imply very small stable time-steps. A new selective mass scaling technique is proposed to increase the time-step size without affecting accuracy. New ”directional” cohesive interface elements are used in conjunction with selective mass scaling to account for the interaction with a sharp blade in cutting processes of thin ductile shells

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