The objective of this Phase II competitive renewal project is to implement a clinical study to collect data to validate EyeStar(tm), a software system as the basis for comprehensive telescreening for all stages of diabetic retinopathy (DR). According to the CDC, approximately 80 million people in the U.S. have some form of eye disease, including 20 million diabetics at risk for retinopathy. It is estimated that less than hal of those individuals with diabetes are screened periodically for DR. Lack of medical coverage and access to healthcare providers imposes major obstacles for nearly 10 million diabetics. Creating an affordable and accessible solution to providing screening services to these diabetics presents a significant challenge to the healthcare community. The objective of the original Phase II grant was to demonstrate a """"""""top-down"""""""" screening algorithm for triaging normal, i.e. no disease, from suspect retinas using a new technique, amplitude modulation-frequency modulation (AM-FM), to analyze multi-field digital retinal images. As a result of the Phase II grant, the EyeStar(tm) software for diabetic retinopathy screening was developed. In this project, we will perform a clinical validation that will allow us to apply for 510(k) clearance by the Food and Drug Administration (FDA). To meet this goal, we have divided this proposal in three aims.
In Aim #1, we will establish a clinical network and meet the requirements for the number of cases needed to perform a clinical study in order to obtain FDA clearance for our integrated, automatic screening system.
In Aim #2, we will perform an independent validation for purposes of submitting to the FDA a 510(k) clearance application.
In Aim #3, we will operate all the EyeStar(tm) components in a near """"""""real-time"""""""" environment. This project is significant for two main reasons: increase of productivity and safety testing. Firs, by increasing the productivity of DR screening centers through automation, a much larger population of at-risk individuals will have access to this service, leading to improved productivit and quality of life through early detection and treatment. Second, by providing to the FDA a system that is highly effective and sensitive, we will insure that the safety requirements of semi-automatic screening for diabetic retinopathy are met. The FDA-cleared software will be integrated into our existing network of retinal screening sites in Texas and New Mexico as the first step toward commercialization.

Public Health Relevance

According to the CDC, there are over 25 million diabetics in the United States, of which less than 50% get their recommended yearly eye exams. This has resulted in an increase of the incidence of diabetic retinopathy, making it the second leading cause of blindness. Our proposed DR screening system, EyeStar(tm), would allow for an increase in examinations available to millions of Americans at risk, without major impact on our healthcare system. The proposed project will perform the necessary clinical validation of the system for FDA approval..

National Institute of Health (NIH)
National Eye Institute (NEI)
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
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Special Emphasis Panel (ZRG1-ETTN-E (12))
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Wujek, Jerome R
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Visionquest Biomedical, LLC
United States
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Yu, H; Barriga, E S; Agurto, C et al. (2012) Fast localization and segmentation of optic disk in retinal images using directional matched filtering and level sets. IEEE Trans Inf Technol Biomed 16:644-57
Agurto, Carla; Barriga, E Simon; Murray, Victor et al. (2011) Automatic detection of diabetic retinopathy and age-related macular degeneration in digital fundus images. Invest Ophthalmol Vis Sci 52:5862-71
Agurto, Carla; Murray, Victor; Barriga, Eduardo et al. (2010) Multiscale AM-FM methods for diabetic retinopathy lesion detection. IEEE Trans Med Imaging 29:502-12