Improved Wall And Lumen Image Acquistion And Processing For Cardiac And Peripheral Magnetic Resonance
Magnetic Resonance Imaging (MRI) is regularly used for routine diagnostics in clinical medicine today. It is a versatile imaging modality that can be tailored to provide anatomical and functional information for clinicians to assess a vast range of diseases without surgical or invasive interventions. Over the last several decades, over thousands of clinical MRI techniques have been developed for the advancement of medicine. Post-processing of routinely acquired MR image or data is one area where such innovation happens. Specifically, these methods use dedicated methods or algorithms to extract clinically relevant parameters that can aid in the diagnostics of diseases. In cardiac MRI, processing of cinematic images of left ventricular motion throughout the cardiac cycle was considered to be challenging, as it required the manual segmentation of the left ventricular blood volume and myocardium from over 200 images - from 8-10 slices over 20-28 temporal frames. In this case, an automated segmentation algorithm of the LV allow s rapid generation of volumetric filling curves, which can be further analyzed to assess the presence or absence of diastolic dysfunction. Another example of MR technology development happens in pulse sequence design, where novel acquisition methods are programmed to allow imaging tailored to a specific anatomy, such as the arterial vessel wall in the peripheral arteries. Vessel walls are difficult to visualize using standard MRI approaches, and novel pulse sequence components have been explored to provide a black-blood effect, which provides improved contrast between the vessel wall and the darkened blood signal. Finally, technology development on the MRI scanner to enable real-time feedback during data acquisition is a challenging, yet an exciting area of research with tremendous potential applications in the clinical arena. One such example is in coronary artery imaging, which faces the challenges of acquiring high-quality images of the moving heart. In this work, a 2D fat image snapshot - called a navigator - is developed to directly monitor the epicardial fat surrounding the coronary arteries at every heartbeat, and is incorporated into a real-time interactive software that allows rapid setup and efficient motion extraction on a standard clinical scanner.
Magnetic Resonance Imaging; Cardiovascular Imaging; Novel Acquisition
Doerschuk, Peter; Christini, David
Ph.D. of Biomedical Engineering
Doctor of Philosophy
dissertation or thesis