Lung cancer is the leading cause of death from cancer in Canada and is typically treated with surgical resection of the tumor. To ensure good prognosis and limit metastases no cancer cells can be left behind during resection. This project uses time-resolved fluorescence and diffuse reflectance to differentiate cancerous and non-cancerous lung tissue. These differences could be used during surgical resection of tumor to ensure no positive margins are present. Using a bi-modal spectroscopy device, BEAR, optical properties were determined for 36 tumor, 36 fibrotic and 9 normal lung tissue samples. Most optical parameters showed statistically significant differences between tumor and other tissue types. Metabolic based optical parameters showed statistically significant differences between fibrotic and normal tissue while non-metabolic based parameters showed no difference. As surgical margins are likely to be between tumor and fibrotic tissue the results demonstrate success and promise for implementing this system. Future work using fresh samples would develop the system further and would be a step closer to in vivo use during surgery. / Thesis / Master of Science (MSc) / Lung cancer is the leading cause of death from cancer and is typically treated by surgically removing the tumor. To improve survival all cancer cells must be removed which can be challenging. This project uses light to extract properties that can differentiate cancerous and non-cancerous lung tissue. These differences could be used during surgery to ensure no cancer cells remain. The project tests this system on 36 tumor, 36 fibrotic and 9 normal lung tissue samples. Most parameters showed significant differences between tumor and other tissue types. Given that often times the surgical boundaries are between tumor and fibrotic tissue the results demonstrate promise in implementing this system. Future work using fresh samples would develop the system further and bring it one step closer to being used during surgery.
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/28706 |
Date | January 2023 |
Creators | Costa, Sarah |
Contributors | Farquharson, Michael, Medical Physics |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
Type | Thesis |
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