<p> Oral cavity cancer (OCC) is a type of cancer of the lip, tongue, salivary glands and other sites in the mouth <i>(buccal or oral cavity)</i> and is the sixth leading cause of cancer worldwide. Patients with OCC are treated based on a staging system: low-stage patients typically receive less aggressive therapy compared to high-stage patients. Unfortunately, low-stage patients are sometimes at risk for locoregional recurrence. Recently, a semi-quantitative risk scoring system has been developed to assess the locoregional recurrence risk for low-stage patients. This risk scoring system is based on tissue characteristics determined on 2D histopathology images under a microscope. This modality limits the appreciation of the 3D architecture of the tumor and its associated morphological features. This thesis aims to visualize 3D models of the tumor-host interface reconstructed from serially-sectioned histopathology slides and quantify their clinically validated morphological features to predict locoregional recurrence after treatment. The 3D models are developed and quantified for 6 patient cases using readily available tools. This pilot study provides a framework for an automated diagnostic technique for 3D visualization and morphological analysis of tumor biology which is traditionally done using 2D analysis.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10127616 |
| Date | 23 June 2016 |
| Creators | Lakhotia, Kritika |
| Publisher | State University of New York at Buffalo |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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