35 EyeWorld Asia-Pacific | March 2025 REFRACTIVE SURGERY Other AI updates Dr. Nallasamy shared some insights on where AI is being applied to other areas of the anterior segment. He said there is currently a clinical trial being led by Maria Woodward, MD, looking at microbial keratitis. The work is developing algorithms to identify key parameters involved in corneal ulcers. This research, he said, could help provide some objectivity in a world that’s usually subjective. “Typically, we’ve done slit lamp exams on these patients. Often we didn’t even take photos, relying on just seeing whether it got better or worse and changing treatment accordingly, but with these tools, we’ll be able to rigorously follow the size and response to treatment and titrate accordingly,” he said. Dr. Nallasamy said his lab is doing work using confocal microscopy and AI to develop a system that can automatically diagnose the type of corneal infection earlier on, rather than just tracking its response to treatment. Separately, Dr. Nallasamy said his lab is also creating an intraoperative decision-making tool for cataract surgery that, using AI, will help the surgeon better understand the likelihood of a patient potentially needing a pupil expansion device during their procedure, based on how the eye is responding in real time to the surgery. Also in the anterior segment, Dr. Nallasamy referenced work being done by Carol Karp, MD, using anterior segment OCT and AI to develop a system that can differentiate OSSN from benign tumors. of sphere, cylinder, and higher order aberrations such as spherical aberration, coma, trefoil and others. With rule-based AI, we can integrate data from the corneal aberrometer and topographer to help not only decide if the patient would benefit from topography-guided treatment but also what is the correct treatment to program into the laser to achieve the most precise outcomes. Postoperative outcome data on visual acuity, refractive error, and higher order aberrations are then input into another AI-driven software to generate nomograms for subsequent patients undergoing treatments.” In the future, Dr. Faktorovich said she envisions AI being used for enhanced diagnostics. Dr. Redd said there are a few things that are needed to bring AI in refractive surgery (and the anterior segment, in general) to the next level. “Deep learning models have been developed to successfully perform image-based diagnosis of several anterior segment diseases, including keratoconus, infectious keratitis, pterygia, and trachoma among many others. AI models have also been trained to provide quantification of various biomarkers of disease severity, allowing more objective monitoring of progression and response to treatment over time,” he said. “However, currently the only FDA-authorized AI-enabled SaMD (software as a medical device) in ophthalmology is for automated diagnosis of diabetic retinopathy. There are many reasons for the gap between the large number of AI models described in the ophthalmology literature and the few that have been implemented clinically, but chief among them are the scarcity of representative datasets for training and evaluating AI models, limited interdisciplinary collaboration, and lack of well-defined reimbursement models.”
RkJQdWJsaXNoZXIy Njk2NTg0