UC San Diego

Glaucoma is a neurodegenerative disease that affects 65 million people worldwide, causing progressive optic nerve damage over time and irreversible blindness. Elevated intraocular pressure (IOP) in the eye has been considered one of the leading modifiable risk factors of the disease. Standard care relies on indirect eye pressure measurements in a physician’s office as one metric to determine therapeutic treatments. Such infrequent single-point measurements are inadequate to fully represent and characterize the patterns associated with disease. In this dissertation we investigate and develop a novel optical-based pressure sensing system capable of measuring IOP on a frequent or semi-continuous basis.

First, the IOP sensor design requirements were established with the aim of measuring pressure using a passive approach with high sensitivity and repeatability. By using the principle of interferometry and diaphragm deflection, the changes in intraocular pressure were determined through interferometric fringes and maximum diaphragm deflection. Next, studies were conducted to investigate the effects of temperature, incident angle, and substrate coating in order to characterize the behavior of the sensor. In addition, a handheld reader was developed to wirelessly obtain optical information from the sensor. Three generations of handheld readers were developed to enable measurements from live and awake rabbits once the sensor was implanted in vivo. The IOP sensor was evaluated ex vivo using rabbits in order to determine the optimal implant method and anchoring approach. Cataract surgery was performed ex vivo in rabbit eyes to replace the native lens with a modified intraocular lens (IOL) carrying the IOP sensor. Finally, the sensor was further valuated through in vivo studies using New Zealand white rabbits. Cataract surgery was performed on the rabbits to implant the sensor. The study showed that IOP measurements were obtainable in vivo. The presence of the sensor had no observable impact on the rabbits’ inflammatory response, suggesting that the system is biocompatible.

Throughout the study, various image processing algorithms were developed in MATLAB to analyze fringe images by employing mathematical models and built-in image analysis functions.