Cellular-level Vascular Oculomics (CVO) for monitoring systemic vascular health

Cellular-level Vascular Oculomics (CVO) for Monitoring Systemic Vascular Health . Planned activities and achievable goals: Year 1: (1.) Hardware design and implementation (Dubra/Burns) will be completed in the first 6 months to yield (2.) four fully functional devices in 4 clinical sites (Stanford, Indiana, Northwestern, Mount Sinai).

Stanford will develop software to (3.) achieve real time image distortion correction. All sites will share existing datasets with Dr. Garyfallidis to initialize the (4.) training of deep learning AI-based software for real time biomarker annotation. (5.) At the end of this year, the entire team will meet with the advisory committee

to present progress and get scientific feedback on progress and proposed biomarkers. Year 2: (1.) Stanford will develop and share image stabilization software and share with Indiana for (2.) integration in its image acquisition software. Garyfallidis will share the first version of the AI annotation

algorithm with Burns and Dubra for integration into image acquisition software. At the end of this year, all sites will have the ability to image healthy and disease subjects using similar devices and software, allowing (2.) dataset comparisons and (3.) generation of normative CVO data. (4.) At the end of this year, the entire

team will meet with the advisory committee to discuss progress, provide feedback, and identify areas for improvement and overall direction. Year 3: (1.) All sites will recruit subjects with systemic disease and (2.) share feedback to (3.) optimize AI software, (4.) software interface, and selection of (5.) biomarkers of interest. In a final group meeting with the

advisory committee, the team will establish (6.) publication plan and (7.) software sharing platform. Final products: (1.) Novel set of ophthalmoscopes with Integrated hardware and software capable of real time segmentation and quantification of microscopic vascular structure and flow biomarkers, that is, the CVO

instrument, and (2.) modular open-source software for diverse applications to imaging of retinal biomarkers, based on CVO, but adaptable to color photographs, OCT Angiography, Doppler OCT or other devices.