Industry

AI-based DR screening tool comparable to human reading centers

Healio Optometry4d ago1 min read

LAS VEGAS — Ocula360, an AI-based tool for diabetic retinopathy lesion detection, showed efficacy in detecting DR across multiple levels of severity, according to a speaker at Clinical Trials at the Summit.While several automated DR assessment tools have been FDA approved, there are limitations in screening for disease severity, SriniVas R. Sadda, MD, of Doheny Eye Institute, said.“In the ideal world, we would actually automatically detect all of the lesions on these ultra-widefield images, and that could potentially facilitate a quantitative and continuous scoring system for diabetic

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AI Summary

Quick Take

Ocula360, a new AI-based lesion detection tool, has demonstrated efficacy in identifying diabetic retinopathy (DR) across various severity levels, performing comparably to human reading centers. Presented by Dr. SriniVas R. Sadda at Clinical Trials at the Summit, the technology utilizes ultra-widefield imaging to move beyond simple binary screening toward a more nuanced, quantitative assessment of the retina.

Why It Matters

While several automated DR screening tools are already FDA-approved, most are limited to 'refer/no-refer' outputs rather than granular severity grading. The ability to automatically detect and quantify specific lesions on ultra-widefield images could shift the industry toward a continuous scoring system, allowing for more precise monitoring of disease progression. This level of automation is critical for managing the growing diabetic population, as it reduces the burden on human graders while potentially increasing the accuracy of longitudinal care.

Key Findings

Ocula360 demonstrated efficacy in detecting diabetic retinopathy lesions across multiple levels of disease severity.
The tool's performance in lesion detection was found to be comparable to the results provided by professional human reading centers.
The technology is designed to work with ultra-widefield (UWF) images, which capture a significantly larger area of the retina than standard fundus photography.
The platform aims to facilitate a quantitative and continuous scoring system for diabetic eye disease, potentially replacing traditional categorical grading.

Practice Implications

Clinicians should monitor the development of Ocula360 as a potential tool for more granular diabetic retinopathy management beyond basic screening. If integrated into practice, such AI tools could provide quantitative data on lesion counts, helping to identify patients at higher risk of progression who may require more frequent follow-up or earlier intervention.

Who's Affected

Retina SpecialistsOphthalmologistsOptometristsClinical Researchers

What's Next

Further validation of Ocula360's quantitative scoring system is expected as the technology moves toward broader clinical application. Future updates will likely focus on how these continuous scores correlate with long-term clinical outcomes compared to traditional ETDRS grading.

Evidence StrengthPreliminary

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