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Optical Coherence Tomography (OCT) has revolutionized the diagnosis and management of retinal diseases, offering high-resolution, cross-sectional imaging that aids in early detection and continuous monitoring. However, traditional OCT devices are limited to clinical settings and require a technician to operate, which poses accessibility challenges such as a lack of appointment availability, patient and family burden of frequent transportation, and heightened healthcare costs, especially when treatable pathology is undetected. With the increasing global burden of retinal conditions such as age-related macular degeneration (AMD) and diabetic retinopathy, there is a critical need for improved accessibility in the detection of retinal diseases. Advances in biomedical engineering have led to innovations such as portable models, community-based systems, and artificial intelligence-enabled image analysis. The SightSync OCT is a community-based, technician-free device designed to enhance accessibility while ensuring secure data transfer and high-quality imaging (6 × 6 mm resolution, 80,000 A-scans/s). With its compact design and potential for remote interpretation, SightSync widens the possibility for community-based screening for vision-threatening retinal diseases. By integrating innovations in OCT imaging, the future of monitoring for retinal disease can be transformed to reduce barriers to care and improve patient outcomes. This article discusses the evolution of OCT technology, its role in the diagnosis and management of retinal diseases, and how novel engineering solutions like SightSync OCT are transforming accessibility in retinal imaging.
Details
Data transfer (computers);
Accessibility;
Tomography;
Diabetes;
Artificial intelligence;
Deep learning;
Image resolution;
Blood vessels;
Retinopathy;
Diabetic retinopathy;
Disease;
Retina;
Telemedicine;
Medical imaging;
Age;
Disease management;
Diagnosis;
Image processing;
Automation;
Monitoring;
Age related diseases;
Innovations;
Image analysis;
Technicians;
Biomedical engineering;
Edema;
Diabetes mellitus;
Retinal images;
Engineering;
Algorithms;
Patients;
Eye diseases;
Optical Coherence Tomography
; Dogan, Alan B 2
; Sobol, Warren M 3 1 College of Medicine, Northeast Ohio Medical University, Rootstown, OH 44272, USA
2 Virginia Tech Carilion School of Medicine, Roanoke, VA 24016, USA
3 Department of Ophthalmology and Visual Sciences, Case Western Reserve University School of Medicine/University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA; [email protected], Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH 44106, USA