GA Management: AI & Treatment Strategies in US & Europe – 2026 Update

The landscape of geographic atrophy (GA) management is rapidly evolving, with novel therapies emerging alongside advancements in artificial intelligence (AI)-driven imaging technology. While the United States has recently gained access to FDA-approved complement inhibitors for GA, the tools to effectively monitor disease progression – specifically, AI-powered imaging analysis – are still pending approval. Conversely, Europe currently has access to these AI tools, like the RetInSight/Topcon GA Monitor, but awaits broader access to the treatments themselves. This creates a unique situation where both regions can leverage their respective strengths while awaiting full integration of both therapies and diagnostic tools.

Europe: Leveraging AI While Awaiting Treatments

Geographic atrophy, a late-stage form of age-related macular degeneration (AMD), leads to irreversible vision loss. As defined by Healio, effective management requires not only therapeutic intervention but also precise monitoring of disease activity. AI is proving invaluable particularly in analyzing optical coherence tomography (OCT) images to identify subtle changes indicative of disease progression.

Researchers are actively working to demonstrate the clinical benefit of AI in GA analysis through retrospective and prospective studies. Several studies have shown that AI can detect changes in the ellipsoid zone (EZ) and retinal pigment epithelium (RPE) layers on OCT images, correlating these changes with the effects of anti-complement therapy. Retina Consultants of America is currently conducting prospective, IRB-approved patient follow-up to further validate these findings.

A key challenge in GA management is identifying lesions that are actively progressing. In neovascular age-related macular degeneration, fluid on OCT imaging serves as a marker of activity. With GA, researchers have identified EZ layer loss as an objective marker of active disease. However, the EZ is a thin layer, and consistently detecting and measuring its changes requires the precision of AI technology. The GA Monitor, for example, can measure EZ thickness with a precision of 1.5 µm.

Beyond simply detecting EZ loss, the ratio of EZ loss to RPE loss – the EZ-RPE ratio – appears to be a critical indicator of disease aggressiveness. A high EZ-RPE loss ratio suggests faster progression. Correlating EZ thickness with retinal sensitivity, as measured by functional OCT, promises to provide a detailed map of functional loss, potentially replacing the more subjective microperimetry test.

United States: Utilizing Treatments While Awaiting AI Approval

In the United States, the situation is reversed. Two complement inhibitors have received FDA approval for GA treatment, but AI-driven imaging analysis remains limited to clinical research settings. The RetinAI software platform, for example, shows promise but isn’t yet approved for routine clinical use.

Dante J. Pieramici, MD, of California Retina Consultants, highlights the potential of AI to enhance clinical practice. Currently, clinicians often rely on comparing OCT scans from only the most recent visits, lacking the time to analyze trends over longer periods. AI could rapidly and precisely analyze historical data, providing a more comprehensive picture of disease progression and treatment response. This information could be invaluable for both clinicians and patients, offering objective evidence of treatment efficacy and motivating continued adherence.

AI could also streamline patient selection for clinical trials. Currently, screening patients for GA studies is a time-consuming process. AI could quickly identify eligible patients based on OCT imaging criteria, combined with data from electronic medical records.

The FDA approval process for AI-based technologies in the U.S. Is rigorous, requiring demonstration of clinical benefit and improvement in patient outcomes. This includes validation of AI outputs against established standards of care or approved technologies.

The Role of Imaging Biomarkers

Both European and American specialists agree on the importance of identifying biomarkers that can predict disease progression. EZ layer loss, as detected by AI-enhanced OCT imaging, is emerging as a key indicator. The EZ-RPE ratio provides further insight into disease aggressiveness, while EZ thickness may predict the likelihood of developing GA in the first place. Research published in January 2026 demonstrated that EZ thickness is a strong predictor of functional loss.

Looking Ahead

The integration of AI into GA management is not without its challenges. Regulatory hurdles in the U.S. And the need for further validation of AI algorithms are ongoing. However, the potential benefits – improved diagnostic accuracy, personalized treatment strategies, and enhanced patient monitoring – are significant. As both Europe and the United States continue to advance in this field, a collaborative approach to data sharing and research will be crucial to accelerate progress and ultimately improve outcomes for patients with geographic atrophy.

Ursula Schmidt-Erfurth, MD, PhD, of Medical University of Vienna, can be reached at [email protected].

Dante J. Pieramici, MD, of California Retina Consultants, can be reached at [email protected].

For further information on geographic atrophy, consult resources from the American Academy of Ophthalmology and the National Eye Institute.