Turbulence Descriptors in Arterial Flows : Patient-Specific Computational Hemodynamics

Sammanfattning: At this very moment, there are literally millions of people who suffer from various types of cardiovascular diseases (CVDs), many of whom will experience reduced quality of life or premature lift expectancy. The detailed underlying pathogenic processes behind many of these disorders are not well understood, but were abnormal dynamics of the blood flow (hemodynamics) are believed to play an important role, especially atypical flow-mediated frictional forces on the intraluminal wall (i.e. the wall shear stress, WSS). Under normal physiological conditions, the flow is relatively stable and regular (smooth and laminar), which helps to maintain critical vascular functions. When these flows encounter various unfavorable anatomical obstructions, the flow can become highly unstable and irregular (turbulent), giving rise to abnormal fluctuating hemodynamic forces, which increase the bloodstream pressure losses, can damage the cells within the blood, as well as impair essential structural and functional regulatory mechanisms. Over a prolonged time, these disturbed flow conditions may promote severe pathological responses and are therefore essential to foresee as early as possible.Clinical measurements of blood flow characteristics are often performed non-invasively by modalities such as ultrasound and magnetic resonance imaging (MRI). High-fidelity MRI techniques may be used to attain a general view of the overall large-scale flow features in the heart and larger vessels but cannot be used for estimating small-scale flow variations nor capture the WSS characteristics. Since the era of modern computers, fluid motion can now also be predicted by computational fluid dynamics (CFD)simulations, which can provide discrete mathematical approximations of the flow field with much higher details (resolution) and accuracy compared to other modalities. CFD simulations rely on the same fundamental principles as weather forecasts, the physical laws of fluid motion, and thus can not only be used to assess the current flow state but also to predict (foresee) important outcome scenarios in e.g. intervention planning. To enable blood flow simulations within certain cardiovascular segments, these CFD models are usually reconstructed from MRI-based anatomical and flow image-data. Today, patient-specific computational hemodynamics are essentially only performed within the research field, where much emphasis is dedicated towards understanding normal/abnormal blood flow physiology, developing better individual-based diagnostics/treatments, and evaluating the results reliability/generality in order to approach clinical applicability.In this thesis, advanced CFD methods were adopted to simulate realistic patient-specific turbulent hemodynamics in constricted arteries reconstructed from MRI data. The main focus was to investigate novel, comprehensive ways to characterize these abnormal flow conditions, in the pursuit of better clinical decision-making tools; from more in-depth analyzes of various turbulence-related tensor characteristics to descriptors that evaluate the hemodynamics more globally in the domain. Results from the studies in this thesis suggest that these turbulence descriptors can be useful to: i) target cardiovascular sites prone to specific turbulence characteristics, both in the bulk flow and on the intraluminal wall, ii) provide a more extensive view of the general flow severity within malformed vascular regions, and iii) evaluated and potentially improve cardiovascular modeling strategies and MRI-measured turbulence data.The benefit of these descriptors is that they all, in principle, can be measured by different MRI procedures, making them more accessible from a clinical perspective. Although the significance of these suggested flow-mediated phenotypes has not yet been evaluated clinically, this work opens many doors of opportunities for making more thorough and longitudinal patient-specific studies, including large cohorts of patients with various CVDs susceptible to turbulent-like conditions, as well as performing more in-depth CFD-MRI validation analyzes.