Development of an Advanced Retinal Imaging System
- Technology Benefits
- Non-invasive –A non-invasive instrument for detection of early stage DR and AMD High Resolution –Design provides high imaging speed and localization precision Early Detection –DR and AMD can be treated before irreversible damage occurs More informative –Capable of providing comprehensive physiological information Large patient pool –DR numbers continue to rise; earlier detection is essential for positive outcomes
- Technology Application
- Retinal diseases are the major cause of blindness in developed countries. The accurate diagnosis andmanagement of retinal diseases is highly depend on non‐invasive imaging techniques. Currently, there isno ophthalmic imaging modality suitable for early detection of DR and AMD through quantitative sO2 andRPE imaging. The American Diabetes Association tallied 25.8 million people with diabetes in the UnitedStates in 2011 and many of them are at risk to develop DR. According to the U.S. Centers for DiseaseControl and Prevention, about 5 million people are affected by DR with new cases increasing at 8% eachyear. Up to 50% of patients are not getting their eyes examined or are diagnosed too late for effectivetreatment. DR is the leading cause of blindness in adults aged 20-74 in the U.S. The CDC estimates that1.8 million Americans over age 40 are affected by AMD, and it is expected to reach 2.95 million in 2020.These large populations represent a significant patient pool that would benefit greatly from more routineand reliable testing for early stage DR or AMD. Other potential applications include diseases that can be diagnosed through morphology and function ofthe retinal vessels such as stroke, Alzheimer’s disease, and hypertensive retinopathy. There is also apotential use in the study of glaucoma in which OCT is utilized to diagnose central retinal vein occlusion.
- Detailed Technology Description
- This diagnostic device enables tests for early stagedetection of diabetic retinopathy (DR) and age-relatedmacular degeneration (AMD) through in vivo non‐invasiveimaging of retinal sO2 measurement and retinal pigmentepithelium imaging. The device integrates three imagingmodalities: photoacoustic ophthalmoscopy (PAOM), opticalcoherence tomography (OCT), and auto-fluorescence (AF)on a slit lamp bio‐microscope. Visual and quantitative datais collected in one pass and presented in an integrated viewfor research or diagnostic use.
- Application No.
- Slides
- *Abstract
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The inventors have developed techniques for functionalphotoacoustic ophthalmoscopy (PAOM) of the eye toprovide structural and functional information of the retinalvessels. This method provides a novel non-invasivetechnique to detect and study early development of DR andAMD. Existing technologies are less sensitive and provideonly indirect measurements with less rigorous calculation methods. Dr. Zhang and Jiao’s photoacousticimaging technique is the only single technology that permits direct imaging of both the anatomy and bloodhemoglobin oxygen saturation of the retinal vessels with high spatial resolution.
Visual loss is often considered the most feared complication of human disease, other than death [1].Among all the causes that lead to irreversible vision loss, diabetic retinopathy (DR) remains a leadingcause. DR is a retinal vascular disorder that occurs as a complication of diabetes mellitus (DM). It isestimated that 25.6 million adults 20 years of age and older known to have DM in the U.S. If DR can bedetected, treated, and managed successfully, the economic impact would be tremendous. For example,laser treatment and surgery for DR lead to an annual societal savings of $1.6 billion. The current clinicaltreatment for late stage DR is associated with unavoidable side effects such as diminished peripheral andnight vision and decreased vision sensitivity. Increasing importance has been placed on treatments thatdetect the progression of DR earlier in order to prevent the damage which leads to vision loss.
- *IP Issue Date
- None
- *IP Type
- Download
- *Principal Investigator
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Name: Shuliang Jiao, Associate Professor
Department:
Name: Lihong Wang, Professor
Department:
Name: Hao Zhang, Adjunct Assistant Professor
Department:
- Country/Region
- USA
