Novel applications and improvements to the diffuse correlation spectroscopy technique

Binner, Philip (2024) Novel applications and improvements to the diffuse correlation spectroscopy technique. PhD thesis, University of Glasgow.

Abstract

Diffuse correlation spectroscopy (DCS) is an optical technique that measures the temporal autocorrelation of scattered light. It is a well-known technique in the biomedical imaging community and is currently popular for live brain activation measurements based on blood flow rate. Although famous for blood flow measurements, its measurement parameter, the speckle decorrelation time, has been shown to linearly correlate with tissue stiffness. In this thesis, I apply DCS to two biomedical applications, from the remote sensing of neurodegeneration to cancerous tumour imaging.

For the remote sensing of neurodegeneration, we measure the speckle decorrelation time of ex vivo mouse brain samples afflicted by prion disease, a neurodegenerative disease similar to Alzheimer’s, Parkinson’s, and Huntington’s disease. Using statistical significance tests and classifiers to determine healthy and diseased brain populations, we determine DCS to be sensitive to neurodegeneration based on brain stiffness changes.

For cancerous tumour imaging, we develop a novel DCS implementation that can capture relative stiffness differences of tissue in wide-field. We test our device on a hidden tumour proxy made by stiffening healthy brain tissue with a fixative. We obtain a ground truth of the fixed tissue by fluorescent tagging the fixed tissue regions, which correlates well with our DCS method.

In the final part of the thesis, improvements to our current DCS techniques are outlined. DCS in the context of sensing and imaging tissue, requires long acquisition times, and to speed the process of DCS up, we developed a machine learning (ML)-DCS model and experiment with speckle contrast imaging that can both image a tumour proxy at medically relevant times of 1 s.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: Q Science > QC Physics
• Colleges/Schools: College of Science and Engineering > School of Physics and Astronomy
• Funder's Name: Engineering and Physical Sciences Research Council (EPSRC)
• Supervisor's Name: Faccio, Professor Daniele and Tobin, Professor Andrew B.
• Date of Award: 2024
• Depositing User: Theses Team
• Unique ID: glathesis:2024-84773
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 20 Dec 2024 12:31
• Last Modified: 24 Nov 2025 14:10
• Thesis DOI: 10.5525/gla.thesis.84773
• URI: https://theses.gla.ac.uk/id/eprint/84773

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