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High resolution retinal imaging to evaluate laser and light safety in the retina for near and long term health effects

The purpose of this research was to investigate detect and monitor laser-tissue interactions at threshold and potentially sub-threshold levels of injury. High resolution imaging modalities can provide a deeper understanding of candidate biomarkers disease and injury at the molecular, cellular, and tissue-levels which can be used to identify and diagnose early stages disease and damage. In addition, multi-scale and multi-modal imaging have also been used to identify inherent biomarkers of retinal disease and injury. Monitoring tissue changes can be mapped back to biological changes at the cellular and sub-cellular level. Diseases often alter tissue on the ultra-structural level yet retinal clinical diagnosis often monitor changes in tissue at the organ level. If injury and disease is detected and diagnosed during an “early” stage of development, treatments and drug interventions may prevent further spread of the pathology. Non-invasive imaging is expected to be a valuable tool for in vivo medical research as well as for the diagnosis and management of disease. In addition to developing new imaging tools and techniques to image the retina, the identification of inherent biomarkers of disease and health using diagnostic methods are almost equally as important.
Using the inherent optical properties of retinal tissue, we can non- invasively quantify differences in the absorption and reflection of light to gauge the risk for visual disability or worse yet irreversible vision loss as a result of retinal disease and chronic light exposure. The research presented with in this dissertation is three separate studies aimed at identifying light injury and potential biomarkers indicating the risk of light mediated development of disease. / text

Identiferoai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-12-6830
Date01 February 2013
CreatorsPocock, Ginger Madeleine
Source SetsUniversity of Texas
LanguageEnglish
Detected LanguageEnglish
Typethesis
Formatapplication/pdf

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