EyeWorld India December 2020 Issue

DEVICES EWAP DECEMBER 2020 53 S everal experts discussed applications of artificial intelligence (AI) in the retina subspecialty. Anthony Joseph, MD, thinks that the diseases it’s initially going to be most useful for are the ones that make up the majority of the retina practice: macular degeneration, diabetic macular edema, diabetic retinopathy, and vein occlusion. Dr. Joseph thinks AI could play a role in screening and monitoring diseases for those who aren’t to the point of requiring active treatment. It may also help in patients being treated or followed more closely for macular degeneration. “We hope it might be something to help predict when they may convert and develop wet macular degeneration or something that can help measure treatment response or treatment needs,” he said. Allen Ho, MD, thinks AI will be useful for retinal diseases that have rich datasets available to analyze. AI analyzes and discerns information that physicians might not typically see in the dat aset; for example, there are man y structure and function corre lations in the OCT imaging datasets from a variety of common retinal diseases. Color fundus imaging is another rich dataset from which disease prognosis and treatment responsiveness may be refined. Glenn Stoller, MD, thinks the two most obvious applications for AI in retina are for diabetes and macular degeneration. It could also be used for retinopathy of prematurity. AI algorithms have already been shown to be effective at detecting clinically significant macular edema, as well as advanced stages of diabetic retinopathy. It can track disease progression by comparing current images to those that were initially screened, helping to provide insight into the progression of diabetic retinopathy, Dr. Stoller said. He added that there is already a system on the market (IDx-DR, IDx Technologies) that uses deep learning and is able to screen outside the ophthalmologist’s office, helping determine when clinical referral is indicated. In using retinal OCT images, AI systems can be trained to perform a segmentation, Dr. Stoller said. The system has been shown to display a high degree of accuracy in segmenting different layers of the retina. AI may also enable personalized healthcare. He mentioned a home-based OCT device from Notal Vision that uses a m achine learning algorithm. T his machine is intended to help monitor patients from home and determine when someone who has wet macular degeneration will need an injection. The technology is expected to be commercially available in the first half of next year. An AI- based random forest classifier is already being applied to analyze visual field data of the ForeseeHome device (Notal Vision), used to determine when a patient converts from dry to wet macular degeneration. Jennifer Lim, MD, said that AI could help decrease the screening burden of diabetic retinopathy. Many diabetic patients never undergo screening (up to 70%, depending on the population and location studied). “It would help to identify patients at risk of visual loss and hopefully result in referrals for appropriate treatment,” she said. AI facilitating interaction Dr. Lim sees the potential for providers across medical specialties to work together to reinforce the importance of diabetic glucose control, as well as control blood pressure, cholesterol, and lipid levels. All physicians could see the results of the patient in the outputs. The data would be presented to the patient by whomever is seeing the patient next, and all team members could be easily updated, she said. In terms of interaction and collaboration with AI among primary care, endocrinologists, ophthalmologists, and retina specialists, Dr. Joseph said the primary care doctor or endocrinologist may be interacting with patients more frequently at the point- of-care level, especially for those with diabetes. This could be a point where data is gathered for screening, as opposed to patients going into Artificial intelligence in retina by Ellen Stodola Editorial Co-director AT A GLANCE • Physicians said AI may be most applicable to diabetes and macular degeneration in the retina subspecialty. • There may also be opportunity for enhanced collaboration among ophthalmologists, primary care providers, and other specialists when using AI and monitoring patients. • There are some potential concerns, including acceptance by patients and doctors, the potential of being misled by large amounts of data, and the extent to which manpower will still be needed. Contact information Ho: achomd@gmail.com Joseph: aejoseph@eyeboston.com Lim: jennylim@uic.edu Stoller: gstoller@ocli.net This article originally appeared in the August 2020 issue of EyeWorld . It has been slightly modified and appears here with permission from the ASCRS Ophthalmic Services Corp.