PIE magazine’s Daily Congress News on the Posterior Segment
Optimizing Outcomes through AI and AR by Tan Sher Lynn
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xperts discussed how artificial intelligence (AI) and augmented reality (AR) are being used in ophthalmology to optimize surgical procedures and outcomes in a session called Technology Symposium: Updates in Artificial Intelligence (AI), Augmented Reality (AR) and Robotics held on the first day of the (virtual) American Society of Retina Specialists 38th Annual Scientific Meeting (ASRS 2020).
AI for diabetic retinopathy screening It is estimated that 600 million people worldwide will get diabetes by 2040, with a third having diabetic retinopathy (DR).1 With the advent of deep learning, various companies have developed automated artificial intelligence diabetic retinopathy screening systems (AIDRSS) which can help reduce the incidence of preventable blindness worldwide. Dr. Aaron Lee from the University of Washington (USA), and colleagues compared the performance of seven AIDRSS in real-world setting. The five companies which participated in the study are ADCIS (Saint-Contest, France), AirDoc (Beijing, China), Eyenuk (California USA), Retina-AI Health (California, USA) and Retmarker (Coimbra, Portugal). A total of 311,604 retinal images for Seattle and Atlanta, as well as the original VA teleretinal grades, were extracted from the national VA Teleretinal Imaging Screening Program. The dataset were run through seven AI algorithms (labeled A-F) from the five companies and their performances were compared to the original VA grades. “The VA grader has 100% sensitivity for moderate non-proliferative diabetic retinopathy (NPDR), severe NPDR and PDR and results from the arbitrated dataset showed that algorithms E, F, G was statistically similar to VA grader for moderate NPDR or higher,” Dr. Lee said.
“We concluded that algorithms varied in performance despite having regulatory approval and/or being clinically deployed,” he added. It is therefore important, highlighted Dr. Lee, to understand AI models in the context of the underlying prevalence of disease. “We believe that external, independent validation with real-world imaging is critical prior to deployment even after algorithms reach regulatory approval,” he shared.
AR for macular degeneration Age related macular degeneration (AMD) is the most common cause of vision loss in older adults in the United States. There were 13M people with AMD in the US and 30M worldwide in 2019 and this number is predicted to increase up to 22M in the US and 288M worldwide.2-3 The novel augmented reality (AR) headset Oculenz (Ocutrx Vision Technologies, CA, USA) is set to change the lives of these patients. “AR enhances the real world and digital elements overlay real world surroundings. It is ideal for complete user freedom,
high or low light surroundings and applications in low vision, medicine and education,” said Dr Dr. Linda Lam, associate professor of ophthalmology of the USC Keck School of Medicine, USA. Especially designed for patients with advanced macular degeneration with central scotama(s), the Oculenz headset provides a perceived de-emphasis of the scotoma, enhanced reading of letters in a word and improved recognition of familiar faces. “Its simultaneous localization and mapping software offers instant location mapping and object identification with 7 million objects identified,” added Dr. Lam. The device is anticipated to be available in early 2021.
Deep learning applications in retinopathy of prematurity Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide, but screening is labor intensive and clinical diagnosis is subjective and qualitative. Dr. J. Peter Campbell from the Oregon Health & Science University (USA) talked about translational applications of deep learning in ROP.
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