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Title: Analysis of morphological and blood flow characteristics of the human thoracic aorta
Author: Fatona, Oluwatoyin Fadeke
ISNI:       0000 0004 7228 9368
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2017
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The human aorta is often affected by many cardiovascular diseases, including atherosclerosis, aneurysm and dissection. There is considerable evidence suggesting that these diseases are associated with the morphology and haemodynamic functions of the aorta, but not all these parameters can be measured directly in vivo. In particular, the helical flow characteristics and haemodynamic wall parameters can only be evaluated from quantitative information on a flow field resolved both in space and time. This study provides a comprehensive analysis of geometric and haemodynamic characteristics of the human aorta through subject-specific simulations of blood flow based on medical images. Computational fluid dynamics (CFD) models of the thoracic aorta were developed based on in vivo anatomical and flow data acquired using magnetic resonance imaging (MRI). In order to capture potential transitional and turbulent flow in the aorta, the correlation based shear stress transporttransitional (SST-Trans) turbulence model was employed. Detailed flow analyses were performed on multiple cases of normal thoracic aortas with a tricuspid aortic valve (TAV) and abnormal aorta with a bicuspid aortic valve (BAV). Results obtained from this study gave quantitative insights into the flow distributions and wall shear stress (WSS) patterns in normal and abnormal aortas. Morphological features and flow patterns of the TAV and BAV aortas were compared. In addition to standard flow parameters, specific indices were evaluated to allow for direct comparisons between the two groups; these included flow reversal ratio (FRR), helicity flow index (HFI) and shear range index (SRI). The results showed that all examined aortas tapered from the proximal ascending segment to the distal descending segment, with the BAV aorta showing a more distinct tapering. Although flow patterns were qualitatively similar in the TAV and BAV aortas, there were substantial quantitative variations. Highly disturbed flow was observed in all examined aortas during part of the cycle, mostly in the systolic deceleration phase. Predicted WSS was higher in the TAV aorta than in the BAV aorta, with the highest WSS occurring in regions around the major arch branches. Comparisons between the predicted and measured velocities showed a good agreement, demonstrating that MR image-based CFD modelling methodology can be used to obtain reliable haemodynamic parameters that are important in clinical assessment and management of aortic diseases.
Supervisor: Xu, Yun Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral