Remidio Medios AI shows Significant Promise in last-mile Screening for Referable Glaucoma
Glaucoma, one of the world’s leading causes of irreversible blindness, is expected to affect an estimated 120 million by 2040, globally. Treatment options for management of Referable Glaucoma (a stage of the disease where immediate treatment can help manage the disease better) exist, but a simple test to screen for this has been elusive. Today, the only way to detect those with Referable Glaucoma is a series of complex investigations often requiring multiple devices handled by Glaucoma Specialists.
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Remidio Innovative Solutions, together with Aravind Eye Hospital (AEH), Pondicherry, and Narayana Nethralaya (NN), Bangalore, announced the results of a landmark clinical trial that can help revolutionize the detection of Referable Glaucoma.
The integrated solution provides an instant report in contexts where there are no specialists. It consists of Remidio’s Fundus on Phone, a retinal imaging device that captures images of the retina without pupil dilation, and Remidio’s Medios Referable Glaucoma AI, an integrated offline AI algorithm that requires no internet for inferencing.
The Medios Referable Glaucoma AI looks beyond the cup-to-disc ratio and detects structural changes in the optic nerve head and surrounding retinal nerve fibre layer. These are critical regions typically assessed by glaucoma specialists during a clinical examination along with an expensive device called Optical Coherence Tomography.
This video shows how technology can screen for Referable Glaucoma in less than 15 seconds.
The diagnostic performance of the Medios Referable Glaucoma AI was validated in a first-ever prospective study. It was simultaneously conducted in a tertiary eye care centre, NN, and in last-mile access contexts called Vision Centres (VCs) of AEH.
Among the 237 study subjects at NN, the AI results were compared against the current standard of care, wherein Glaucoma specialists provided the final diagnosis following a comprehensive glaucoma work-up. The AI algorithm demonstrated a high sensitivity of 93.5% (95% CI: 87.1-96.8%) to detect those with Referable Glaucoma with a specificity of 85.4% (95% CI: 78.3-90.4%). Interestingly, the recall for ‘no glaucoma’ was also high at 94.7% (95% CI: 87.1-97.9%) with a minimal overcall of normal subjects.
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Dr. Rohit Shetty, Vice Chairman at Narayana Nethralaya, said,” Our clinical study at NN, shows that AI can bring in much-needed objectivity in glaucoma screening, especially in contexts where there are no specialists. We also see the power of AI to be used in applications as diverse as outreach screening to personalized care.”
In the multi-centre study at Aravind, among the 299 subjects evaluated at the VCs by resident doctors, 70 were referred to the base hospital. Early results demonstrated a sensitivity of 91.30% (95% CI: 79.2-97.5%) and specificity of 91.67% (95% CI: 73-98.9%). The AI detected glaucoma with a higher sensitivity than the resident doctors and reduced the number of over-referrals. The integrated solution holds promise as an easily deployable tool to detect referable Glaucoma as the results seen in a tertiary eye care centre are also seen in last-mile screening contexts.
Dr. R. Venkatesh, Chief Medical Officer at Aravind Eye Hospital, said, “AI has helped overcome the challenges often presented with Glaucoma screening in the outreach. The reporting of fundus images has gotten much faster and more reliable with AI. It has great promise in VCs as a clinical decision tool for resident doctors to improve their diagnostic consistency.”
Dr. Divya Rao, Glaucoma specialist and Remidio’s Medical Director & Head of AI, said, “Promising results show that our AI can empower healthcare workers and general ophthalmologists to make an objective screening diagnosis, specifically at centres lacking sophisticated diagnostic equipment.”
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