Computer-Aided Analysis of PCMRI Flow Data

  • Magnetic resonance imaging (MRI) has firmly established itself as one of the leading tools in clinical diagnostics and radiology. However, its full potential still remains to be utilized in clinical routine. Apart from imaging the anatomy, MRI can also be used for obtaining functional and even molecular information in vivo. One such functional technique is phase contrast MRI (PCMRI). With PCMRI, it is possible to capture time-resolved three-dimensional velocity information. This is especially useful for quantifying cardiac function and hemodynamics of larger vessels, as PCMRI can reconstruct a full velocity field v(x,t) during one heart cycle along with morphological information. Velocity-encoded 4D PCMRI flow measurements have revealed a wealth of in vivo flow patterns in healthy volunteers as well as in patients. There are strong hints that hemodynamic flow patterns are correlated to various vascular pathological phenomena like atherosclerosis, plaques and aneurysms. This motivates the computer-aided characterization, detection, and quantification of flow patterns from 4D PCMRI flow measurements. This thesis explores the possibilities of a comprehensive characterization of in vivo hemodynamics from PCMRI data. The focus is on the hemodynamic parameters influencing the genesis, progression, and rupture of aortic plaques. Such plaques develop as the thickening of the vessel wall; they contain lipids (cholesterol etc.) and are prone to calcification and rupture. The rupture of an aortic plaque may finally result in a stroke. Further applications of 4D PCMRI velocity mapping are aneurysms and their risk assessment, planning and follow up of surgery for congenital heart defects, analysis of flow through artificial heart valves, and stenosis, among others.

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Meta data
Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Johann Drexl
Referee:Tobias Preusser
Advisor:Horst Hahn
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1008552
Document Type:PhD Thesis
Date of Successful Oral Defense:2017/06/01
Date of First Publication:2019/02/18
Academic Department:Computer Science & Electrical Engineering
PhD Degree:Computer Science
Focus Area:Mobility
Other Countries Involved:United States of America
Other Organisations Involved:Northwestern University
Call No:2017/54

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