Mapping cerebral hemodynamics during pediatric critical care

Mentor: Adam Eggebrecht, Assistant Professor of Radiology

Lab description: Our Brain Light Lab of the Biophotonics Research Center, is a diverse and interdisciplinary team whose research focuses on developing novel tools that extend mapping of brain function beyond current limitations. We harness the power of diffuse optics to create portable and wearable systems for minimally constrained imaging of brain function. This technology facilitates mapping brain function in participants who are especially challenging to study with fMRI such as toddlers and children with autism and patients undergoing surgery or intensive care. Our efforts are focused on three broad areas: hardware development, software and algorithm development, and applications from basic science to clinical care. Hardware development projects concentrate on optimizing signal-to-noise, image quality, subject comfort, and portability. Software and algorithm projects include Finite Element Modeling of light propagation, image reconstruction speed and accuracy, spatial registration of multiple data types, and development of a self-contained toolbox, NeuroDOT (https://www.nitrc.org/projects/neurodot/), for acquisition and analysis of diffuse optical tomography data and extensions for uncovering statistically meaningful relationships between metrics of brain function and behavior. Current funded applications of focus include childhood development of brain function and behavior as it relates to autism spectrum disorder and congenital heart disease.

Project: While mortality rates have improved for children born with congenital heart disease, morbidity rates for patients who undergo corrective surgery and/or extracorporeal membrane oxygenation (ECMO) can have life-long effects. Current neuromonitoring technologies that can be deployed at the bedside have low sensitivity and predictive value for detecting changes in physiology that may underlie deleterious outcomes. The summer project provides opportunities for data collection during surgery and/or ECMO maintenance with our custom bedside neuroimaging device. Additionally, the project would involve opportunities for data analyses including the development of new strategies to relate variability in physiological status and brain networks with outcomes. The student would interact with team members from a variety of disciplines, work with state-of-the-art technology, and obtain computational experience.