High-Frame-Rate Ultrasound Characterization of Carotid Pulse Waves to Assess Cerebrovascular Resistance

Abstract

Objective: Devise an ultrasound imaging framework for cerebrovascular resistance assessment by characterization of carotid pulse waves. Background: The resistance of cerebrovasculature regulates blood flow to the brain that could serve as a biomarker for detection of early dementia. The onset of dementia, leading to higher cerebrovascular resistance (CVR), is theorized as the cerebrovascular damage due to elevated pulse pressure, one heartbeat at a time. The increased pulse pressure causes mechanical stress to the cerebral microvasculature as it propagates into the brain and alters cerebral hemodynamics. This change in cerebral hemodynamics can be explained from the classical Ohm’s law, whereby resistance is the ratio of potential difference (pressure) to current (blood flow). In fact, early dementia patients were identified with higher CVR in several brain regions. CVR can be assessed by measuring the pulse pressure wave and blood flow wave present in the carotid artery during each cardiac contraction. The forward pulse wave propagates along the carotid artery to the brain and is partially reflected back to the heart when encountering a change in resistance in the brain. Higher CVR affects the reflected pulse wave and, accordingly, alters the measured pulse wave in the carotid artery with distinct characteristics such as greater amplitude, broader peak, and higher pulse wave velocity. By examining the forward and reflected pulse wave, pressure and flow information can be acquired and in turn assess CVR. Proposed Solution: To assess CVR from the carotid, an ultrasound imaging framework is proposed due to its low-cost and high accessibility compared to fMRI and PET. This ultrasound framework is developed based on high-frame-rate ultrasound (HiFRUS) paradigm with frame rate up to 10k frame per second. HiFRUS enables the estimation of blood flow velocity and the capture of transient pressure dynamics in the carotid artery where conventional ultrasound cannot achieve. To realize the innovation, four research modules will be pursued: (1) to separate the pulse waves into forward and reflected pulse wave, a wave separation algorithm is developed. (2) to characterize the separated pulse waves, a sensitive analysis was performed by manipulating downstream resistance in vitro study. (3) to transit in vitro to in vivo study, a motion-compensation algorithm was developed. (4) to assess CVR by the pulse wave in the carotid artery, an in-vivo study will be conducted. Impact: This thesis establishes the feasibility of assessing CVR through our proposed pulse wave analysis platform, providing a new method for researchers to investigate new possibilities in the dementia fields. Future work will benchmark our approach against the established imaging methods.