Accurately Track Retinopathy Progression
With No Human Grading Needed
Diabetic RetinopathyCurrently diabetic retinopathy (DR) causes 12,000 to 24,000 new cases of blindness each year in the U.S, and is the leading cause of blindness among adults aged 20–74 years. By 2030, an estimated 550 million people across the globe will have diabetes, with half expected to develop some level of retinopathy. In most cases visual loss is preventable through annual screening and early diagnosis. However, due to factors such as lack of awareness, lack of insurance coverage, and lack of access to expert clinicians almost 50% of the people with diabetes in the U.S do not undergo any form of dilated eye exam. Even if the number of people getting screened increased, there are currently not enough qualified eye-care givers to view and diagnose the images from these screenings. In some regions of the Unites States there is a backlog of several thousand patients waiting to see an ophthalmologist, causing very long appointment wait times (often over six months).
What is EyeMark?EyeMark takes fully automated diabetic retinopathy analysis one step beyond imaging, grading and reporting. It is designed to automatically and accurately track disease progression from visit to visit to determine if a patient’s disease has increased, decreased or remained stable. This information augments the “refer/no refer” assessment that is available today and is valuable for disease management.The technology estimates microaneurysm (MA) appearance and disappearance rates (known as turnover rates) for use as a biomarker in monitoring the progression of DR. Microaneurysms are the first sign of DR and are of significant interest to eye care professionals. High MA turnover rates possibly indicates higher risk for DR progression triggering closer monitoring or treatment. Early studies have shown the promise of EyeMark and the technology is under development.
How will EyeMark help?Tracking progression manually today by human graders is time consuming and error-prone, involving careful alignment of images across multiple patient visits, followed by marking and comparison of individual microaneurysms by hand. EyeMark will make tracking progression far more accurate and simple. The technology makes it much easier for physicians to identify patients who are at risk of progressing to severe retinopathy, helping to prevent vision loss by enabling earlier intervention. And it does this all automatically and non-invasively. Previous research on DR has yielded sufficient evidence that MA turnover rates are a good predictor of likelihood of progression to more severe retinopathy, establishing MA turnover as an excellent biomarker for DR. The availability of a reliable tool like EyeMark to measure this biomarker automatically from images will have a highly positive influence on various aspects of DR care, including screening, monitoring progression, drug discovery and clinical research. Early identification is especially important in the face of a long backlog of diabetic patients waiting for an eye exam, and the fact that 90% of vision loss can be saved by early identification. The availability of an effective biomarker will also positively influence the drug discovery process by facilitating early and reliable determination of biological efficacy of potential new therapies.
How does EyeMark work?A visiting patient is imaged by an eye care professional using a commercial fundus camera and the fundus images are input to EyeMark. The software automatically analyzes and grades the images (for current visit and all available previous visits), and issues a simple, quantitative report. The report shows a positive number (MA increase), negative number (MA decrease), or zero (no change). The flexible technology works with image quality common in everyday practice and with any imaging protocol.
Technology behind EyeMark
Presently MA turnover measurement involves two steps: careful alignment of current and baseline images, and marking of individual MAs. This process is very time consuming and prone to error, if done by entirely by human graders. The problem is compounded by the variable image quality and inter- & intra-observer variability between screenings. EyeMark overcomes the above limitations by automating both the steps involved in MA turnover measurement: accurate image registration, and MA detection. EyeMark would also include an end-to-end desktop software for automated computation of MA turnover and also provide intuitive visualization tools for clinicians to more effectively monitor diabetic retinopathy progression.