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Development of a Hyperspectral NIRS System for Functional Imaging of the Brain and for Cerebral Status Monitoring During Cardiac Surgery

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posted on 2023-07-27, 14:04 authored by Ermias Woldemichael
Hyperspectral near infrared spectroscopy (hNIRS) is a noninvasive, real-time imaging modality with an improved quantitative accuracy and increased number of detectable chromophores. It uses the broadband spectrum of light wavelengths in the range of 700 – 1100 nm and is based on the unique absorbance property of molecules and the fact that all biological tissues are relatively transparent to these wavelengths which allow for measuring concentrations of light absorbing molecules such as the Oxy- and Deoxy- hemoglobin and Cytochrome C Oxidase. As opposed to fMRI, PET and SPECT, hNIRS is inexpensive and portable. The purpose of this thesis project was to employ advantages of hNIRS by developing the multichannel hNIRS set-up for the simultaneous assessment of multiple areas of the brain and to test the system in clinical applications. To achieve these goals, I developed a new optical fiber bundle design providing improvement of the optical power throughput into the hNIRS light detectors. I also developed a novel probe for measurements on hairy areas of the human head. To validate the hNIRS system I used it simultaneously with fMRI, which revealed a good correlation of hNIRS and fMRI BOLD signals from the brain. The multichannel hNIRS set up with the increased signals due to the novel optical fiber bundles was then used during various brain activation protocols, which in the future can allow for the assessment of patients with mild traumatic brain injuries (mTBI). Finally, the hNIRS system with the new fiber bundles was compared with a commercial NIRS system in clinical setting for brain monitoring of patients during the transcatheter aortic valve implantation operation (TAVI).

History

Language

English

Degree

  • Master of Science

Program

  • Biomedical Physics

Granting Institution

Ryerson University

LAC Thesis Type

  • Thesis

Year

2017

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    Biomedical Physics (Theses)

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