This study is a prospective, multicenter, observational study to assess the safety and efficacy of RETINA-AI Galaxy v2.0 (Galaxy) in screening for diabetic retinopathy in the primary care setting. The study design conforms to an Intent to Screen (ITS) paradigm. The Galaxy is a Software as a Medical Device designed to analyze digital color fundus photographs and rapidly screen for the presence of more than mild diabetic retinopathy and vision-threatening diabetic retinopathy in the primary care setting.~Subjects who meet eligibility criteria will be recruited from Sites staffed by primary care providers. Eligibility will be assessed and informed consent obtained, after which digital color fundus photographs will be taken using U.S. Food and Drug Administration (FDA) cleared non-mydriatic fundus cameras, by an operator using the Galaxy photography manual.~There will be a total of 3 non-mydriatic robotic screening cameras used in the AI system protocol part of the study. There will be a dedicated validation camera used in the Validation Reading Center Protocol part of the study. Primary care clinical staff (e.g. medical assistant) with no prior professional ophthalmic photography experience and only a 4 hour training will operate the RETINA-AI Galaxy v2.0 device and the screening cameras. The Retina Reading Center (RRC)- certified professional ophthalmic photographers will operate the validation fundus cameras according the the 4W-D stereo protocol, and will obtain OCT images of the macula.
Diabetes affects approximately 35 million Americans, each of whom needs at least one retinal exam per year if Type II (and starting at 5th year after disease onset if Type I). However, majority of diabetic patients do not get their eye exam due to multiple prohibitive factors such as cost, transportation, difficulty of taking time off from work, and inconvenience, amongst others. As a result, diabetes is the most common cause of visual impairment and blindness in working age adults in the United States and globally. Early detection via effective screening can prevent diabetes-related blindness. However, there are multiple barriers to screening. This prompted the development of RETINA-AI Galaxy v2.0, an automated Software as a Medical Device that screens for diabetic retinopathy in the primary care setting. This observational study is designed to validate the safety and efficacy of the device.