Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia

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dc.contributor.advisorRichards-Kortum, Rebecca Rae
dc.creatorRosbach, Kelsey Jane
dc.date.accessioned2013-03-08T00:38:10Z
dc.date.available2013-03-08T00:38:10Z
dc.date.issued2011
dc.description.abstractThis thesis develops and evaluates three approaches for quantitative molecularly-targeted optical imaging of neoplasia. The first approach focuses on widefield imaging of biomarkers near the tissue surface for early detection applications; this approach is demonstrated in freshly resected oral tissue. Most oral cancers are not detected until the disease has spread, but topical application of targeted imaging agents allows rapid visualization of biomarker expression, giving real-time, objective information. Epidermal growth factor receptor (EGFR) expression was quantified in patient samples using fluorescent epidermal growth factor. Dysplasia (n=4) and cancer (n=13) had an average 2.3-fold and 3.8-fold increase in signal compared to normal tissue. EGFR expression was assessed along with metabolic activity using a fluorescent glucose analog, 2-NBDG, in 9 patient samples. A classification algorithm using quantitative image features resulted in an area under the curve (AUC) of 0.83, though the main advantage of this technique may be to understand spatial heterogeneity of biomarker expression and how this correlates with disease. The next approach focuses on high-resolution optical imaging through a needle to detect metastases in lymphoid tissue for clinical staging applications; this approach is demonstrated in resected lymph nodes from breast cancer patients. These patients often require removal of nodes, but an optical imaging strategy using topical application of imaging agents in vivo may classify nodes as normal or metastatic, thus reducing unnecessary removal of normal nodes and improving metastasis detection. Proflavine, a nuclear dye, was topically applied to 43 nodes. A classification algorithm developed from quantitative image features distinguished normal lymphoid tissue from metastases with an AUC of 0.84. Because optical imaging is depth limited, the final approach combines high-resolution optical imaging with magnetic resonance imaging (MRI) for multimodal evaluation of deep tissue. An imaging agent functional in both optical and MRI was developed by co-loading fluorescent EGFR antibodies and gadolinium-based contrast agents in silicon discs. These discs accumulate in tumors, resulting in localized delivery of imaging agents. The research presented here can be applied to understanding tumor biology and biomarker heterogeneity, with the future clinical goal of improving identification of disease and determination of appropriate therapy for cancer patients.
dc.format.extent156 p.en_US
dc.format.mimetypeapplication/pdf
dc.identifier.callnoTHESIS BIOENG. 2011 ROSBACH
dc.identifier.citationRosbach, Kelsey Jane. "Development and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia." (2011) Diss., Rice University. <a href="https://hdl.handle.net/1911/70415">https://hdl.handle.net/1911/70415</a>.
dc.identifier.digitalRosbachKen_US
dc.identifier.urihttps://hdl.handle.net/1911/70415
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectHealth sciences
dc.subjectEnvironmental science
dc.subjectApplied sciences
dc.subjectPure sciences
dc.subjectImage classification
dc.subjectOral cancer
dc.subjectOptical imaging
dc.subjectBiomarkers
dc.subjectNeoplasia
dc.subjectBiomedical engineering
dc.subjectMedical imaging
dc.subjectOptics
dc.subjectOncology
dc.titleDevelopment and Evaluation of Approaches for Quantitative Optical Molecular Imaging of Neoplasia
dc.typeThesis
dc.type.materialText
thesis.degree.departmentBioengineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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