Oral cancer accounts for an estimated 650,000 new cases annually with a high mortality rate of approx. 50%. Oral cancer is typically treated with a combination of surgery, radiation and chemotherapy, but patients suffer from high recurrence rates due to delayed detection and invasiveness of the disease. Surgical standards require surgeons to resect a margin of healthy tissue surrounding cancerous tissue in order to reduce the rate of recurrence. Frozen section (FS) analysis is a common intraoperative technique for examination of surgical margins, but is limited in its sensitivity of detecting positive margins of resected tissue (especially in deep margins where most positive sites originate). Elastic Scattering Spectroscopy (ESS) is a fiber optic based backscattering optical technique which utilizes a small source detector separation allowing for examination of subcellular changes in tissue. In addition, ESS is a point measurement technique making it impossible to take a grid of coordinated measurements over a tissue surface. ESS has been used extensively for the classification of cancerous tissue in vivo, but current instrumentation limits the physical and financial availability of ESS devices across various clinical studies. The goal of this thesis is the design and implementation of a low cost, portable and modular ESS device that allows for scanning across an area of tissue for the quantification and assessment of deep margins of resected oral cancer samples. A low-cost ESS device has been developed and validated for use across various clinical studies which utilize ESS. A scanning module has been developed to allow for imaging of resected tissue over an area of 1cm2 with a pixel resolution down to 100 μm. This system will be utilized in a clinical study to assess deep margins of resected oral cancer tissue to test the feasibility for using ESS as an adjunct for FS.
Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/41922 |
Date | 22 January 2021 |
Creators | Gray, Alexander James |
Contributors | Bigio, Irving, Roblyer, Darren |
Source Sets | Boston University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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