1853245

This SBIR Phase II project demonstrates and clinically validates a novel, non-invasive imaging technology to detect diabetic retinopathy before structural damage occurs. Diabetic retinopathy is among the leading causes of vision loss in the world. This devastating complication of both type I and II diabetes results in structural damage to the sensitive vasculature of the retina. Once structural damage is inflicted, it is difficult, if not impossible, to ameliorate it. Small changes in the retinal vasculature's oxygen saturation have been shown to be a reliable indicator of diabetic retinopathy before structural damage occurs. Since there is no clinical non-invasive technology capable of detecting these small functional changes, a major need exists for new retinal oximetry technologies. Diabetic retinopathy affects 200 million people worldwide. The American Diabetes Association reports that the cost of diabetes in the US in 2012 was $245 billion, including $69 billion in reduced productivity and $176 billion in medical costs. Since 40% of diabetics are anticipated to develop diabetic retinopathy, the estimated economic cost of diabetic retinopathy is $98 billion annually. By mitigating the occurrence of diabetic retinopathy, this technology will help reduce the cost of diabetic retinopathy treatment, its overall economic burden, and help save the vision of millions of people around the world. The primary technical innovation behind the proposed technology is its use of a novel physics-based model to overcome the challenges of high-resolution retinal imaging. These challenges include the multi-layered structure of the retina, absorbance dynamics, and the need to produce an image in one snapshot to reduce motion artifacts. Compared with existing methods based on structural imaging, the successful outcome of this project will become a commercial technology-of-choice for ophthalmologists around the world, enabling cost-effective detection of early stage diabetic retinopathy or pre-retinopathy. The development of the technology proceeds through iterative optimization between laboratory and real-use environments to generate robust, validated data. Specifically, in Phase II, the research objectives of the project are pursued in two parallel tracks: 1) refinement of the core imaging system, and 2) validation using model and human subjects in a clinical environment. The outcome of this project will be an easy-to-use, reliable diagnostic imaging and monitoring technology with proven clinical utility in detecting the onset of diabetic retinopathy based on functional properties, before structural damage has occurred in the patient. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.