Enhancing Analysis of Debris Accumulation in the Post-Lens Tear Film for Scleral Lens Wearers using AI-Driven Quantification
Meng C. Lin, Professor
Optometry
Closed. This professor is continuing with Fall 2024 apprentices on this project; no new apprentices needed for Spring 2025.
Scleral lenses, unlike standard contact lenses, are large-diameter rigid lenses that rest on the sclera (white part of the eye) and create a tear-filled reservoir to hydrate the anterior ocular surface. They are primarily recommended for patients with corneal irregularities and dry eye diseases due to their capability to significantly improve vision and comfort. The unique design, featuring a high oxygen-permeable material and a thick fluid reservoir, effectively corrects visual distortions caused by irregular corneas while providing protection and alleviating discomfort for patients suffering from severe dryness. However, a common complication is the accumulation of cellular debris in the fluid reservoir, affecting 26-46% of scleral lens wearers. This buildup can lead to blurry vision, lens fogging, and discomfort, often necessitating frequent lens cleaning and disrupting daily life. Currently, most clinicians rely on subjective grading scales to assess debris severity, lacking standardization. This study aims to develop an objective grading system using AI modeling to analyze high-resolution AS-OCT images, quantifying debris severity over time and location. This will help identify causes of post-lens debris and predict its association with lens-related ocular symptoms and clinical findings.
Role: The undergraduate student will be responsible for the following:
- Understand current study design and study aims
- Assist with developing an AI model to analyze high-resolution AS-OCT images
- Data management
- Help drafting a manuscript for publication upon study completion
This study will be a good opportunity for the student to take part in the process of research planning, data collection, and analysis. The student will gain knowledge in specialty contact lens design, ocular surface physiology, clinical design, and scientific methodology.
Qualifications: It is important that the student has a background in computer science and is familiar with AI coding. The student has good communication skills and is able to work independently and as a team member. The ideal student would also be curious, proactive, and detail-oriented. An interest in biology and research would be beneficial in this role.
Hours: 9-11 hrs
Biological & Health Sciences