Predictive Deep Learning Applications in Ophthalmology

Abstract

Therapies for retinal diseases have witnessed remarkable progress, particularly in the domain of drug delivery routes. Intravitreal injections have especially revolutionized the treatment landscape for various proliferative retinopathies. The emergence of suprachoroidal space as a novel drug delivery site is poised to overcome challenges seen in optimizing drug penetration, targeting, and bioavailability. This approach holds promise for delivering various agents, including steroids, anti-vascular endothelial growth factor molecules, gene vectors, and small molecules, with multiple clinical trials demonstrating this delivery method's potential to reduce treatment burdens and optimize visual outcomes. Particularly, small molecule therapy for retinal diseases finds ease of application through the suprachoroidal route in that small molecule agents have a wide range of targets in disease pathway, greater tissue penetration, and cost-effectiveness in production. The suprachoroidal administration of axitinib, a tyrosine kinase inhibitor, has shown promise in the OASIS trial for treating neovascular age-related macular degeneration. Integrin antagonists and plasma Kallikrein-kinin system inhibitors, also delivered suprachoroidally, exhibit targeted distribution and potential for long-acting therapy.

Defining the structure–function relationship of specific lesions in early and advanced age-related macular degeneration

“…With the rapid progress of AI-driven applications, DL models have been developed for the prediction of structure–function correlation in AMD 33 , 34 . Most of these efforts have targeted prediction of VA from OCT images 35 , 36 .…”