Echo Particle Image/Tracking Velocimetry: Technical Development and In Vivo Applications in Cardiovascular and Cerebrovascular Flows

Contrast-enhanced ultrasound (CEUS) imaging utilizes intravascular echogenic microbubbles (1-5μm in diameter) to visualize the blood flow in various organs. In this dissertation, we develop and implement techniques for analyzing the motions of microbubbles to quantify cardiovascular and cerebrovascular flows. Obtaining accurate bubble center locations from noisy CEUS images is a primary challenge. Since the bubble trace is typically modeled as a point scatter convolved with a point spread function (PSF), techniques including blind deconvolution, supervised, and self-supervised learning are introduced and calibrated for identifying the PSF and locating the bubble center. The enhanced CEUS images enable echo particle image velocimetry (echo-PIV) for characterizing 2D cardiovascular flows, and the global-optimized Kalman filter-based echo particle tracking velocimetry (echo-PTV) for determining bubble trajectories which are subsequently used for mapping the cerebral and ocular microcirculation at a spatial resolution of 20μm. These techniques are applied to two applications. First, echo-PIV is used for monitoring the aortic root flow in an adult pig undergoing veno-arterial extracorporeal membrane oxygenation (VA-ECMO), a life support technology whose parameters can be optimized based on the aortic root hemodynamics. Phase-averaged and instantaneous flow fields show that, for the pig with severe myocardial ischemia, the cardiac ejection velocity, velocity-time integral, and mean arterial pressure (MAP) reach their peak at an ECMO flow rate of 3.0L/min, indicating an optimal flow rate that provides adequate support. Second, we investigate non-invasive methods for estimating intracranial pressure (ICP), a critical parameter for hydrocephalus patients that cannot be invasively measured safely. Echo-PTV is used to map cerebral and ocular microcirculation of pediatric hydrocephalus porcine models for inferring ICP. Results show that accounting for pulse pressure, highly correlated relationships between ICP and cortical microcirculation density are obtained with correlation coefficients beyond 0.85. For cerebral ischemia, nondimensionalized cortical micro-perfusion decreases by an order of magnitude when the ICP exceeds 50% of MAP. Moreover, retinal microcirculation also shows a highly correlated relationship with ICP when accounting for pulse pressure. These findings suggest that CEUS-based microcirculation measurement is a plausible noninvasive method for evaluating the ICP and detecting brain ischemia