Imaging Study to Create an Age-Related Macular Degeneration AMD Dataset in Adults 50 and Older

What this Trial Is About

Researchers aim to create a diverse and detailed dataset of eye images from 1000 participants aged 50 and older, including both healthy individuals and those diagnosed with any stage of Age-Related Macular Degeneration AMD. This dataset will support the development of an Artificial Intelligence AI tool to help screen for early AMD, a condition that can lead to vision loss. The study addresses the challenge of identifying early AMD in primary care settings to help prevent late-stage vision loss. Participants will undergo a single retinal imaging session of both eyes, which includes single field stereo color fundus photography before and after pupil dilation and macular spectral domain-optical coherence tomography. Additional study procedures include collecting patient history such as demographics, smoking, and family history of AMD, a physical exam measuring height and weight, vision testing using Snellen best-corrected visual acuity, and AMD classification using the Beckman scale. The study is observational and cross-sectional, conducted at multiple international sites to ensure a wide representation. During the study, participants will provide detailed imaging and clinical data in one visit. Researchers will collect and annotate images for a reference standard classification of AMD and track participant counts by AMD classification and geographic location over up to 18 months. The study involves no treatment but focuses on data collection to facilitate AI development. Participation involves no therapeutic procedures, and safety monitoring is not required since this is an observational study. Total involvement is limited to the imaging session and consent process.

Age-Related Macular Degeneration Benchmark Imaging Dataset (ABID)