Heidelberg Engineering announced an advancement in the use of artificial intelligence (AI) for ophthalmic diagnostics, with the publication of the Eye2Gene study in Nature Machine Intelligence. Titled “Next-generation phenotyping of inherited retinal diseases from multimodal imaging with Eye2Gene,” the study highlights the potential of AI-powered analysis of multimodal Spectralis imaging to accelerate genetic diagnosis in patients with inherited retinal diseases (IRDs).

Eye2Gene leverages Fundus Autofluorescence (FAF), Infrared Reflectance (IR), and spectral-domain OCT (SD-OCT) to predict the likely causative gene in IRD cases—providing a non-invasive decision-support tool for clinicians, the company said in a press release. 

According to Heidelberg Engineering, the AI system was trained on 58,030 multimodal retinal scans from 2,451 patients with confirmed genetic diagnoses and further externally validated on 775 patients from 5 sites. Covering 63 disease-associated genes, Eye2Gene captures more than 90% of IRD cases in Europe. 

Particularly noteworthy, the company said, is its superiority in interpreting only FAF images, where it reached an accuracy of 76%, compared to 36% or less by experienced clinicians who took part in the study. These results were consistently reproduced across 5 independent clinical centers—including institutions in Tokyo, Bonn, São Paulo, Oxford, and Liverpool—demonstrating the model’s robustness and generalizability across populations and imaging standards. 

 In more than 75% of tested cases, it outperformed popular phenotyping-only tools in prioritizing disease-causing genetic variants, thereby increasing the likelihood of achieving a definitive diagnosis, the company said in the press release.

At its core, Eye2Gene is powered by an ensemble of 15 convolutional neural networks—5 per imaging modality—which together generate patient-level predictions by averaging across scans and modalities. According to Heidelberg Engineering, this architecture not only improves accuracy but also ensures that the system can adapt to variations in imaging conditions across different sites. 

Eye2Gene supports earlier referrals to genetic testing and clinical trials, assists in complex differential diagnoses, and makes expert-level interpretation accessible in settings where specialist expertise may be limited. In addition, by integrating phenotype data into variant prioritization, Eye2Gene increases the diagnostic yield, improving the likelihood of reaching a genetic diagnosis, the company said.