Ophthalmology is one of the most imaging-intensive specialties in medicine. Devices such as optical coherence tomography (OCT), fundus cameras, visual field analyzers, and anterior segment imagers generate large volumes of data that are critical to diagnosis, treatment planning, and ongoing disease monitoring. Yet unlike radiology and cardiology — where DICOM-based interoperability is well established — ophthalmic imaging has historically relied on proprietary, manufacturer-specific file formats that do not communicate reliably with one another or with EHR systems.
This fragmentation has significant consequences. Images may be lost when a patient transfers care between providers. Practices using multiple devices from different manufacturers often cannot aggregate imaging data in a single, searchable system. Researchers and AI developers cannot build large, standardized datasets from imaging collected across institutions. And as AI-based diagnostic tools for ophthalmology become increasingly viable, the absence of standardized data threatens to limit their development and real-world utility.
The DICOM standard — used widely in radiology and cardiology — provides a well-established technical framework for addressing these problems in ophthalmology. DICOM supplements for ophthalmic imaging modalities have been developed and are available, but adoption by manufacturers has been slow. Currently, FDA market authorization does not require DICOM compliance for ophthalmic imaging devices, and conformance claims by manufacturers are not independently certified — meaning "DICOM compliant" labels may not reflect full, meaningful implementation.
The Academy and ARVO have called on manufacturers, regulators, and federal agencies to work together to close this gap — through clearer requirements, stronger incentives, and a commitment from the ophthalmic imaging industry to make interoperability a priority.