Collections > Electronic Theses and Dissertations > ARFI Ultrasound for the Detection and Characterization of Atherosclerosis in an FH Pig Model

Stroke is the third leading cause of death in the United States, with a large percentage of strokes caused by atherosclerotic rupture. Current methods of atherosclerotic detection include invasive techniques such as coronary angiography and intravascular ultrasound (IVUS), as well as noninvasive techniques such as magnetic resonance angiography and duplex ultrasound. These methods are known to be effective for detecting occlusive plaques associated with pronounced narrowing of the vessel lumen and/or blood flow obstruction. However, they are not effective for detecting nonstenotic plaques or for characterizing plaque composition. This lack of plaque compositional information prevents these imaging techniques from detecting plaque rupture risk. To accurately assess atherosclerotic plaques most vulnerable to rupture, novel detection and characterization techniques are needed. Acoustic radiation force impulse (ARFI) ultrasound, one of several elastographic techniques under development to meet this need, uses high intensity acoustic impulses to remotely displace tissue. By assessing ARFI-induced displacement and subsequent tissue recovery, the mechanical properties of tissue can be assessed and used to characterize atherosclerosis. In order to ensure the best possible plaque detection capability, the most appropriate beam sequences must be used. Following ex vivo and in vivo demonstration of ARFI capability for atherosclerotic plaque detection and characterization, a statistical reader study of ARFI beam sequences is performed in phantoms as well as ex vivo and in vivo in an FH pig model. Finally, a serial study of ARFI is performed to assess ARFI repeatability and potential for early plaque detection. This dissertation supports the hypothesis: in vivo, transcutaneous ARFI ultrasound will detect occlusive and nonocclusive plaques in peripheral arteries, assess plaque composition and structure and detect changes in atherosclerotic status over time.