Abstract
Magnetic Resonance Imaging offers the possibility to noninvasively assess blood flow. Different diseases in the cardiovascular system are closely linked to pathological flow and information about the flow can be employed to diagnose and investigate such diseases.
There exist wellestablished methods to measure the mean velocity of blood flow, and recently a technique to assess turbulence intensity was proposed. All these approaches suffer from high sensitivity to chosen scan parameters and noise. In this work a new method is presented which combines highly accelerated measurements with a Bayesian approach. PhaseContrast Magnetic Resonance Imaging is employed using different encoding velocities. Coherent motion leads to a velocity depending phase, and velocity fluctuations caused by turbulence lead to a decrease in signal magnitude. These effects in combination with statistical methods result in a posterior probability of the mean velocity and turbulence intensity. This probability is then maximized to obtain an estimate of these parameters.
The technique proposed has shown promising results regarding the accuracy compared to conventional methods, especially in the low SNR regime. The practicability was demonstrated using in vitro as well as in vivo measurements, including pathological flow situations. Further investigation is required to improve speed and to validate the results of turbulence intensities.
There exist wellestablished methods to measure the mean velocity of blood flow, and recently a technique to assess turbulence intensity was proposed. All these approaches suffer from high sensitivity to chosen scan parameters and noise. In this work a new method is presented which combines highly accelerated measurements with a Bayesian approach. PhaseContrast Magnetic Resonance Imaging is employed using different encoding velocities. Coherent motion leads to a velocity depending phase, and velocity fluctuations caused by turbulence lead to a decrease in signal magnitude. These effects in combination with statistical methods result in a posterior probability of the mean velocity and turbulence intensity. This probability is then maximized to obtain an estimate of these parameters.
The technique proposed has shown promising results regarding the accuracy compared to conventional methods, especially in the low SNR regime. The practicability was demonstrated using in vitro as well as in vivo measurements, including pathological flow situations. Further investigation is required to improve speed and to validate the results of turbulence intensities.
Original language  English 

Qualification  Master of Science 
Awarding Institution 

Supervisors/Advisors 

Publication status  Published  2011 
Keywords
 Magnetic Resonance Imaging
 phasecontrast velocity mapping
 turbulence intensity
 Bayesian approach
 accelerated imaging