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Title: Characterization of flow dynamics in vessels with complex geometry using Doppler optical coherence tomography
Author: Bonesi, Marco
ISNI:       0000 0001 3469 8468
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2008
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The study of flow dynamics in complex geometry vessels is highly important in many biomedical applications where the knowledge of the mechanic interactions between the moving fluid and the housing media plays a key role for the determination of the parameters of interest, including the effect of blood flow on the possible rupture of atherosclerotic plaques. Doppler Optical Coherence Tomography (DOCT) is an optic, non-contact, non-invasive technique able to achieve detailed analysis of the flow/vessel interactions, allowing simultaneously high resolution imaging of the morphology and composition of the vessel and of the flow velocity distribution along the measured cross-section. DOCT system was developed to image high-resolution one-dimensional and multi-dimensional velocity distribution profiles of Newtonian and non-Newtonian fluids flowing in vessels with complex geometry, including Y-shaped and T-shaped vessels, vessels with aneurism, bifurcated vessels with deployed stent and scaffolds. The phantoms were built to study the interaction of the flow dynamics with different channel geometries and to map the related velocity profiles at several inlet volume flow rates. Feasibility studies for quantitative observation of the turbulence of flows arising within the complex geometry vessels are discussed. In addition, optical clearing of skin tissues has been utilized to achieve DOCT imaging of human blood vessels in vivo, at a depth up to 1.7 mm. Two-dimensional OCT images of complex flow velocity profiles in blood vessel phantom and in vivo subcutaneous human skin tissues are presented. The effect of optical clearing on in vivo images is demonstrated and discussed. DOCT was also applied for imaging scaffold structures and for mapping flow distributions within the scaffold.
Supervisor: Meglinski, Igor Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available