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Investigation of Light Propagation and Detection in a Human Head in Healthy and Clinical Settings

Tuesday, October 16, 2018

11:00 AM-1:00 PM

BIOMED PhD Research Proposal

Investigation of Light Propagation and Detection in a Human Head in Healthy and Clinical Settings

Lei Wang, PhD Candidate, School of Biomedical Engineering, Science and Healthy Systems, Drexel University

Hasan Ayaz, PhD, Associate Professor, School of Biomedical Engineering, Science and Healthy Systems, Drexel University

Meltem Izzetoglu, PhD, Research Professor, College of Engineering, Villanova University

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging modality that allows investigation of brain tissue oxygenation non-invasively. It is widely used to measure changes in the concentration of oxy-hemoglobin and deoxy-hemoglobin in tissue. Infrared light emitted from a source placed over scalp propagates through the tissue and eventually part of it is back-scattered and collected by photodetector. The attenuated light received at the detector encodes the information about brain activity as a consequence of absorption and scattering dominated light tissue interaction.

Understanding and modeling light tissue interaction is critical for developing next generation fNIRS systems. Several photon migration models have been proposed to investigate light tissue interaction through computerized Monte Carlo (MC) simulations. Using these, a set of fNIRS system parameters have already been explored, such as wavelength selection, source-detector (SD) separation, depth of penetration, and effect of layers’ thickness.  Among those simulation studies, most have not declared the detector or fiber size clearly, also the selection of core system parameters remains controversial, like SD separation. More importantly, all these studies were performed only under healthy settings, no clinical conditions were taken into consideration. With numerous applications of fNIRS technology in the assessment of brain function under various clinical conditions caused by traumatic brain injury (TBI) or stroke indicate the importance of study and evaluation of light tissue interaction under such conditions.

In this proposal, we aim to develop a reconfigurable and adaptive digital head model for healthy and clinical conditions that can be used to study diverse fNIRS parameters for optimization. The proposed thesis will provide several novel contributions to the knowledge base that can further optical neuroimaging research applications, technology and algorithm development. First, it investigates new system parameters in digital head phantom, such as detector surface area and SD separation associated with wide range of different wavelengths, which are potential sources of system error in calculating hemoglobin concentrations. Secondly, several clinical conditions such as cerebral hematoma and edema development will be modeled in silico, their effect on fNIRS measurements and parameters will be demonstrated with modeling for the first time. Such modeling and evaluation of neurological conditions and their effect on optical parameters and measurements can further help in the development of advanced algorithms for fNIRS to provide more accurate hematoma and edema detection. Furthermore, an MC simulation approach for continuous wave fNIRS systems will be developed and evaluated in comparison to real measurements on physical phantom models. The findings of this research can be used to optimize fNIRS sensors and provide guidance for the design of next generation optical brain imaging systems for the monitoring of brain activity under healthy and clinical conditions.

Contact Information

Ken Barbee

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