University of Toronto
Development of Quantitative Optical Coherence Tomography Methods for Cell Death Detection
Abstract
dc:description.abstractCurrent clinical cancer treatment monitoring methods rely largely on measurements of tumour volume to assess treatment efficacy several weeks to months after the start of therapy. The development of early monitoring methods to determine a patientâ s response within the first days of a new treatment could significantly impact the overall outcome. Treatment induced cancer cell death occurs before changes in tumour volume. Cell death is characterized by a series of predictable and organized subcellular morphological changes. Light scattering theory predicts that changes in the size, shape, number density and spatial organization of subcellular structures will affect light backscattered from tissues. The objective of this thesis was to develop quantitative methods using optical coherence tomography (OCT) to non-invasively detect cell death in tissues undergoing cancer therapy. Data acquisition and analysis methods were designed to measure variations in the OCT signal resulting from morphological changes in dying cells. Specifically, parameters were developed to measure changes in the speckle intensity statistics, spectral characteristics and the temporal intensity fluctuations of the OCT signal. In a series of in vitro experiments it was demonstrated that the quantitative OCT parameters are sensitive to morphological changes related to cell death. Measured changes in the quantitative parameters 24 to 48 hours after the induction of cell death were linked to structural changes observed in the cell nucleus using light microscopy. Based on the known kinetics of cell death, early variations in the spectral parameters of the OCT signal and decorrelation rate of the speckle intensities were linked to mitochondrial morphology. Finally, preliminary studies using mouse tumour models demonstrated the feasibility of using these parameters to detect cell death in vivo.
Degree
thesis:*- Department dc:contributor.department
- Medical Biophysics
- Year dc:date.issued
- 2016
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Farhat, Golnaz
- Advisors dc:contributor.advisor
-
- Czarnota, Gregory J
- Kolios, Michael C
Subjects
dc:subject × 6Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1807/76406
- OAI identifier oai:identifier
- oai:utoronto.scholaris.ca:1807/76406