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Optical coherence tomography (OCT) is standard of care technology for ophthalmic diagnostics. It is widely used for managing expensive and complex therapies in age-related macular degeneration (AMD). The extension of the technique for home use has tremendous utility. The high heterogeneity of the patient population requires optimization of expensive and complex treatment protocols that can only be achieved via high-frequency monitoring at home. Extending a complex 3D imaging technology for home use requires innovation at multiple fronts. The technical and usability methods are developed to allow self-imaging in patients with poor vision. Machine learning based techniques are used to manage high throughput of data and extract essential information for the physicians. Patient compliance over an extended period is essential for success of any home monitoring program and that requires a sophisticated support infrastructure. The presentation will discuss results of performing self-imaging using home OCT on over 600 eyes. The machine learning based analysis of the retinal images to quantify fluid in the diseased eyes to understand temporal dynamics will be demonstrated. The performance of the technique in longitudinal studies to demonstrate compliance using infrastructure of home monitoring as a service will be discussed. Home OCT development carries essential lessons for personalizing and decentralizing a number of complex technologies.
Nishant Mohan
"OCT at home: technology, applications, and infrastructure to make it possible", Proc. SPIE PC12369, Optics and Biophotonics in Low-Resource Settings IX, PC123690F (6 March 2023); https://doi.org/10.1117/12.2661106
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Nishant Mohan, "OCT at home: technology, applications, and infrastructure to make it possible," Proc. SPIE PC12369, Optics and Biophotonics in Low-Resource Settings IX, PC123690F (6 March 2023); https://doi.org/10.1117/12.2661106