Dissertation/Thesis Abstract

Visualization and quantification of 3D tumor-host interface architecture reconstructed from digital histopathology slides
by Lakhotia, Kritika, M.S., State University of New York at Buffalo, 2016, 53; 10127616
Abstract (Summary)

Oral cavity cancer (OCC) is a type of cancer of the lip, tongue, salivary glands and other sites in the mouth (buccal or oral cavity) 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.

Indexing (document details)
Advisor: Doyle, Scott
Commitee: Sarder, Pinaki
School: State University of New York at Buffalo
Department: Biomedical Engineering
School Location: United States -- New York
Source: MAI 55/05M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Biomedical engineering, Medical imaging
Keywords: 3d modeling, Histopathology, Oral cavity cancer, Quantitative risk modeling, Registration, Tumor-host interface quantification
Publication Number: 10127616
ISBN: 978-1-339-85648-3
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