ECE PhD Dissertation Defense: Bingxue Liu

ECE PhD Dissertation Defense: Bingxue Liu

Title: Speckle decorrelation-based techniques for measuring cerebral dynamics with ultrasound and optics

Presenter: Bingxue Liu

Date: Tuesday, October 15th, 2024

Time: 10:15am to 12:15pm

Location: PHO 339

Advisor: Professor David A. Boas

Chair: TBA

Committee: Professor David A. Boas, Professor Xiaojun Cheng, Professor Jerome Mertz, Professor Anna Devor, Professor Irving Bigio, Professor Lei Tian

Google Scholar Link: ‪https://scholar.google.com/citations?user=9TKKpAQAAAAJ&hl=en&oi=ao

Abstract: Cerebral hemodynamics and cellular dynamics are crucial for maintaining brain health and function. Dysregulation of these processes is implicated in various neurological conditions, such as stroke and neurodegenerative diseases. Non-invasive imaging techniques, including functional ultrasound (fUS) and laser speckle contrast imaging (LSCI), have shown great promise for monitoring cerebral blood flow (CBF) in preclinical animal studies, offering high spatiotemporal resolution over a large field of view. However, both methods face limitations in their ability to accurately quantify physiological parameters. fUS, typically relying on power Doppler signals as an indicator of cerebral blood volume (CBV), is often affected by system noise and motion artifacts, while color Doppler-based fUS is limited to detecting axial blood flow, resulting in incomplete assessments of cerebral blood flow speed (CBFspeed). Similarly, conventional LSCI models assume that speckle dynamics arise solely from blood flow, neglecting the potential for measuring cellular dynamics in brain tissue.

To address these limitations, this thesis focuses on applying speckle decorrelation-based methods in both fUS and LSCI to improve the quantitative measurement of brain dynamics. First, we introduce an ultrasound speckle decorrelation-based timelagged functional ultrasound technique (tl-fUS) for the quantification of the relative changes in CBFspeed, CBV and CBF during functional stimulations. Numerical simulations, phantom validations, and in vivo mouse brain experiments were performed to test the capability of tl-fUS in accurately parsing and quantifying these hemodynamic parameters, demonstrating superior performance compared to conventional Doppler-based fUS techniques.

Next, we developed a multi-dynamics laser speckle contrast model that incorporates both fast blood flow dynamics and slow tissue dynamics. To enhance the sensitivity to slow tissue dynamics, we built a short-separation speckle contrast optical spectroscopy (ss-SCOS) system with point illumination and point detection using linear fiber arrays. Finally, an epi-illumination-based wide-field LSCI system was developed to map both fast and slow speckle dynamics. The system was demonstrated in transient and permanent stroke models, indicating slow tissue dynamics as a novel and an important biomarker for studying stroke evolution and recovery.