Hongting Zhao
BME PhD Proposal Presentation

Date:2022-02-22
Time: 2PM-4PM
Location / Meeting Link: https://us04web.zoom.us/j/75778395604?pwd=o8e-_7MWVZSYV1dnBSt9iJMW9vVfBR.1

Committee Members:
Prof. Erin M. Buckley, PhD (Advisor) Prof. Levi Wood, PhD Prof. Shella Keilholz, PhD Prof. Eva Dyer, PhD Prof. Dobromir Rahnev PhD


Title: Improving the accuracy of diffuse correlation spectroscopy measurements of cerebral blood flow

Abstract: Adequate cerebral blood flow (CBF) is critical for the delivery of oxygen and nutrients necessary to maintain neuronal health and function. Diffuse correlation spectroscopy (DCS) is an emerging noninvasive optical modality for measuring CBF. By measuring the temporal correlation of the intensity fluctuations of multiple-scattered near-infrared light detected at the tissue surface, DCS provides information about the motion of red blood cells in the underlying tissue. DCS has the potential to fill the gap of an inexpensive (around $50k) and portable beside microvascular CBF monitor (unlike MRI). In addition, DCS does not expose patients to ionizing radiation (unlike CT), and it is sensitive to microvascular instead of macrovascular blood flow (unlike Doppler ultrasound). DCS has been successfully applied in monitoring of cerebral hemodynamics on both animals and humans. However, there are currently two primary limitations of DCS for accurate bedside CBF monitoring: (1) Reliance on independent assessment of patient-specific optical properties for accurate blood flow estimation. Blood flow estimation with DCS requires knowledge of the optical properties of the tissue (i.e., the absorption and reduced scattering coefficients). To quantify optical properties, diffuse optical spectroscopy is typically employed, but this approach adds extra cost and hardware complexity to the overall system. (2) Signal contamination from extracerebral layers. By the nature of the measurement, detected photons have traveled through both scalp and skull before detection, thus DCS measurements of “cerebral” blood flow can be significantly confounded by contributions of these superficial layers (e.g., scalp and skull). These contributions can be particularly appreciable in adults wherein the scalp and skull are thicker than children, making it difficult to quantify absolute cerebral blood flow. Given the considerable advantages of DCS for non-invasive bedside CBF monitoring, this proposal aims to develop advanced data analysis algorithms to improve estimation accuracy and depth penetration of existing DCS systems. To address limitation (1), I propose to develop stand-alone system can measure both oxygen saturation, blood flow and metabolism (Aim1). To address limitation (2), I propose to investigate and improve the accuracy of a novel multi-layer DCS method (Aim2).