Study finds value in home OCT monitoring

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A study published in Ophthalmology Science shows that by analyzing daily home OCT images, artificial intelligence (AI) can accurately track disease activity in patients with wet age-related macular degeneration (AMD). This may allow physicians to manage patients by following biomarker trajectories and assessing treatment response.¹

The study evaluated data from 180 wet AMD patients and compared the AI-based Notal OCT Analyzer (NOA)-generated outputs to annotations made by 3 expert graders. The results showed high agreement between NOA and human experts in identifying clinically meaningful changes.

The study also found that using personalized thresholds to identify changes in a patient's retinal anatomy resulted in higher sensitivity than applying a single, fixed threshold across all patients. When physicians set individualized thresholds, sensitivity increased from about 90% to 99.1% without increasing false positives.²

Theodore Leng, MD, FACS, director of clinical and translational research and ophthalmic diagnostics at Stanford's Byers Eye Institute, shared his thoughts on this study in the press release¹, saying, "Home OCT-based monitoring has been validated in large pivotal trials with over 500 patients, which is rare for medical imaging technology. Our study went a step further by showing that home OCT longitudinal data trajectories are clinically valuable and essential in helping retina specialists personalize disease management."

Kester Nahen, PhD, CEO of Notal Vision, also spoke to the potential of this AI solution in the press release¹, saying, "This work is a major step forward in personalized AMD patient care. It shows that home imaging, powered by AI and guided by physicians, can reliably track disease activity and help doctors make informed patient management decisions."

Previous pivotal trials for SCANLY Home OCT demonstrated that home-acquired images are equivalent to in-office OCT for visualizing key biomarkers in wet AMD patients.³ Those trials also validated NOA for estimating hypo-reflective spaces, a key disease biomarker, in a cross-sectional setting.⁴ This latest study is the first to examine NOA's performance in tracking changes over time in a home setting.

The study results will be presented by Leng at the Retina Society meeting in Chicago on September 12, 2025.

References:

1. AI Turns Daily Home OCT Images into Actionable Disease Insights for Retina Specialists. News Release. August 26, 2025. Accessed August 27, 2025. https://finance.yahoo.com/news/ai-turns-daily-home-oct-120000743.html

2. Leng, Theodore, et al. "Longitudinal Validation of the Artificial Intelligence Algorithm in Home OCT for Age-Related Macular Degeneration. Report 3." Ophthalmology Science (2025): 100907.

3. Heier, Jeffrey S., et al. "Pivotal Trial Validating Usability and Visualization Performance of Home OCT in Neovascular Age-related Macular Degeneration. Report 1." Ophthalmology Science, Volume 5, Issue 5, (2025): 100772. https://doi.org/10.1016/j.xops.2025.100772.

4. Schneider, Eric W., et al. "Pivotal Trial Toward Effectiveness of Self-administered OCT in Neovascular Age-related Macular Degeneration. Report 2-Artificial Intelligence Analytics." Ophthalmology Science 5.2 (2025): 100662.