Identifying Vulnerable Plaques with Acoustic Radiation Force Impulse Imaging
The rupture of arterial plaques is the most common cause of ischemic complications including stroke, the fourth leading cause of death and number one cause of long term disability in the United States. Unfortunately, because conventional diagnostic tools fail to identify plaques that confer the highest risk, often a disabling stroke and/or sudden death is the first sign of disease. A diagnostic method capable of characterizing plaque vulnerability would likely enhance the predictive ability and ultimately the treatment of stroke before the onset of clinical events.
This dissertation evaluates the hypothesis that Acoustic Radiation Force Impulse (ARFI) imaging can noninvasively identify lipid regions, that have been shown to increase a plaque's propensity to rupture, within carotid artery plaques <italic>in vivo</italic>. The work detailed herein describes development efforts and results from simulations and experiments that were performed to evaluate this hypothesis.
To first demonstrate feasibility and evaluate potential safety concerns, finite-element method simulations are used to model the response of carotid artery plaques to an acoustic radiation force excitation. Lipid pool visualization is shown to vary as a function of lipid pool geometry and stiffness. A comparison of the resulting Von Mises stresses indicates that stresses induced by an ARFI excitation are three orders of magnitude lower than those induced by blood pressure. This thesis also presents the development of a novel pulse inversion harmonic tracking method to reduce clutter-imposed errors in ultrasound-based tissue displacement estimates. This method is validated in phantoms and was found to reduce bias and jitter displacement errors for a marked improvement in image quality <italic>in vivo</italic>. Lastly, this dissertation presents results from a preliminary <italic>in vivo</italic> study that compares ARFI imaging derived plaque stiffness with spatially registered composition determined by a Magnetic Resonance Imaging (MRI) gold standard in human carotid artery plaques. It is shown in this capstone experiment that lipid filled regions in MRI correspond to areas of increased displacement in ARFI imaging while calcium and loose matrix components in MRI correspond to uniformly low displacements in ARFI imaging.
This dissertation provides evidence to support that ARFI imaging may provide important prognostic and diagnostic information regarding stroke risk via measurements of plaque stiffness. More generally, the results have important implications for all acoustic radiation force based imaging methods used clinically.
Biomedical engineering
Acoustics
acoustic radiation force
atherosclerosis
harmonic tracking
plaque
stroke
ultrasound elasticity imaging

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