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NSFDirectorate for Engineering

CAREER: Wearable opto-electronic sensor for quantitative, noninvasive imaging of cerebral blood flow in humans

Active
Institution
University of South Florida, FL
Principal investigator
Ashwin Bharadwa Parthasarathy
Funding
$513K
Duration
2023–2028
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Abstract

The human brain receives up to 20% of the body's blood supply, despite accounting for only 2% of the human body's mass; a true testament to the vital function that it provides. Nevertheless, blood flow to the brain is tightly controlled by a mechanism called autoregulation, because even momentary disruptions in blood flow can lead to strokes, while excess blood flow can result in brain bleeds. Due to this critical role, quantitative measurements of autoregulation and brain blood flow can be used to detect brain injuries, monitor treatment, and even predict recovery. Unfortunately, there is currently no portable, easy-to-use instrument that physicians can use to quantitatively and continuously image brain blood flow at a patient's bedside. To address this technology gap, this project will develop the first wearable optical imaging instrument for bedside, noninvasive imaging of brain blood flow and autoregulation dynamics in humans. In addition to helping clinicians manage brain injuries, this imaging instrument will improve our understanding of critical brain function and will help identify undiagnosed local brain injuries. The educational and outreach goal of this project is to develop and distribute modular electronic-lego kits that will foster fun, experiential learning of electronic design for all ages. Cerebrovascular autoregulation (CVAR) is an important homeostatic mechanism that controls cerebral blood flow (CBF) during changes in arterial blood pressure and metabolic demand. Since disruption of this autonomic process is strongly indicative of disease, quantitative measurements of CVAR dynamics are functional biomarkers for brain injuries including ischemic strokes, traumatic brain injuries and Alzheimer's disease. Unfortunately, the state of current clinical monitoring is limited to CBF measurements at a few locations in the head, forcing CVAR metrics to be characterized as a single global number that ignores spatial distributions, potentially leading to undiagnosed local injuries. To address this technical limitation, this project will develop new portable optical technology to quantitatively measure cerebral blood flow with Diffuse Correlation Spectroscopy (DCS). Specifically, (1) this project will build the world's first wearable optical device for quantitative monitoring blood flow, featuring technical innovations that dramatically shrink the footprint of a DCS blood flow monitor from a large briefcase to a 1 sq. in. optical probe. (2) The project will then adapt this wearable blood flow sensor for use over the entire human head for non-invasive imaging of cerebral blood flow (CBF) in humans. Rigorous experiments will be conducted on tissue-simulating phantoms, and in humans, to characterize the accuracy, sensitivity, and noise performance of the CBF imager. The devices developed in this project are unique for the broader neuroimaging community. With appropriate dissemination and commercialization of this technology, this first-of-its kind CBF imager can help a broad cohort of researchers who study the brain including neurologists, neuroscientists, phycologists, and behavioral scientists, and can also be adapted for other tissue types. The proposal was co-funded by the Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET) in the Directorate of Engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Directorate for EngineeringCAREER-Faculty Erly Career DevSensor TechnologyUnallocated Program CostsCCSS-Comms Circuits & Sens SysDisability & Rehab EngineeringRESEARCH TO AID THE DISABLEDBioP-Biophotonicsinjurieswearableautoregulationblood flowcbfcerebral bloodbrain injuriesflow

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