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Identification of qualitative and quantitative features in wide-field in vivo oral optical coherence tomography.

University of British Columbia

Optical coherence tomography (OCT), the optical analogue of ultrasound with resolution approaching that of histology, has shown great potential in the detection of pre-cancerous and cancerous lesions in the oral cavity. The objective of this thesis is to identify qualitative and quantitative features from OCT that are associated with normal, benign, pre-cancerous and cancerous lesions. In this work, OCT images were acquired from patients in vivo during their visits to the oral pathology clinic. The data were then analyzed both qualitatively and quantitatively. In the qualitative analysis, structural changes in tissue, associated with abnormalities, were compared and matched between their appearance in OCT and the corresponding histology images. In the quantitative analysis, MATLAB was used to automate extraction of numerical values associated with the structural changes, present in the OCT images. As a result of the qualitative analysis, it was found that a set of five features — epithelium thickness, epithelium stratification, rete-ridges visibility, basement membrane presence, and connective tissue appearance relative to the epithelium — can together qualitatively help to identify normal as well as various benign, pre-cancerous and cancerous conditions. To the best of my knowledge, this is the first time that epithelium stratification and high-resolution rete-ridges visibility have been presented as OCT features relevant for cancer detection. Furthermore, quantitative analysis revealed that the numerical values of two of the features — epithelium thickness and stratification — significantly vary going from normal tissue to benign and finally to pre-cancers and cancer. As a result, this work lays the ground work for showing the potential of OCT as a biopsy guidance tool, that can be used in vivo, to find regions of severe abnormalities and thus minimize multiple and unnecessary biopsies.

Text

2019-01-02

Attribution-NonCommercial 4.0 International

http://hdl.handle.net/2429/68141

Biomedical Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc/4.0/