Modeling the Structure-Function Relationship between Retinal Ganglion Cells and Visual Field Sensitivity and the Changes Due to Glaucomatous Neuropathy
By: Ali Syed Raza
Publisher: [publisher not identified]
Published: 2014
Place of publication: [New York, N.Y.?]
Language: eng
Description: Relatively new technology called optical coherence tomography allows direct and non invasive in vivo imaging of retinal anatomy in human subjects. There are several interesting applications of this technique, including testing models relating retinal anatomy (structural measures) to behavioral thresholds of light sensitivity (functional measures). In addition to potentially improving our understanding of this relationship and how it changes during the course of neurodegenerative diseases of the eye such as glaucoma, analyses of these data may allow for early identification of glaucomatous neural damage in the retina, which has considerable clinical relevance. Here, the underlying assumptions and generalization of a previously developed model of the structure function relationship in glaucoma was tested by applying this model to a novel dataset. This model has been influential in the literature because it purports to accurately estimate the number of retinal ganglion cells; however, it was found to have several questionable assumptions and did not generalize well.

Next, a new method of estimating the number of retinal ganglion cells from optical coherence tomography was developed. This method uses fewer and more defensible assumptions and demonstrated good agreement with independent histological estimates. Finally, a new method, using computer simulations, was developed for analyzing data from optical coherence tomography in order to distinguish early signs of glaucomatous changes in retinal anatomy from variability in structure among healthy retinas, and this method performed better than previously published techniques.
Notes: Department: Neurobiology and Behavior.

Thesis advisor: Donald C. Hood.

Thesis (Ph.D.)--Columbia University, 2014.