Abstract: Diabetic retinopathy (DR) remains a leading cause of irreversible vision loss in adult populations around the globe. Despite growing evidence of the effectiveness of routine assessments and early intervention, DR screening strategies are not widely implemented largely due to an inadequate availability of resources to cope with the growing burden of diabetes. Advances in technology in the field of DR screening are clearly warranted and the recent emergence of deep learning-based artificial intelligence (AI) grading of retinal pathology offers significant potential benefits including an increased efficiency, accessibility and affordability of screening programmes.
Abstract: Several factors drive the need for increased efficiency in telemedicine screening programs directed toward diabetic retinopathy: continually increasing prevalence of diabetes worldwide, growing awareness among physicians and patients of the importance of early detection of retinal damage, and emerging technology in artificial intelligence that enables rapid identification of vision-threatening fundus features. In this context, optimizing workflows in teleretinopathy programs becomes a priority. Recent work has revealed opportunities for improvement in areas of logistics, in particular in finding the best way to get diabetic patients in front of screening cameras as conveniently as possible, as this improves compliance and, ultimately, achieves the widest reach for detection programs. The present review discusses particular aspects of mobile screening programs in which specialized retinal cameras are deployed in a van or similar type of vehicle so that they can reach patients anywhere in order to reduce barriers to access. The rationale for implementing such programs and practical considerations are presented, along with a view toward future expansion of screening and integration with artificial intelligence platforms. Lacking standardization of format and quality control among smartphone-linked approaches at present, translation of eye clinic-based photographic techniques to community-based screening offers a means of expanding the scope of impactful screening programs without the need for adoption of significantly new technology.
Abstract: The most prominent causes of loss of vision in individuals over 50 years include age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy (DR). While it is important to screen for these diseases effectively, current eye care is not properly doing so for much of the population, resulting in unfortunate visual disability and high costs for patients. Innovative functional testing can be unified with other screening methods for a more robust and safer screening and prediction of disease. The goal in the creation of functional testing modalities is to develop highly sensitive screening tests that are easy to use, accessible to all users, and inexpensive. The tests herein are deployed on an iPad with easily understood and intuitive instructions for rapid, streamlined, and automatic administration. These testing modalities could become highly sensitive screenings for early detection of potentially blinding diseases. The applications from our collaborators at AMA Optics include a cone photostress recovery test for detection of AMD and diabetic macular edema (DME), brightness balance perception for optic nerve dysfunction and especially glaucoma, color vision testing which is a broad screening tool, and visual acuity test. Machine learning with the combined structural and functional data will optimize identification of disease and prediction of outcomes. Here, we review and assess various tests of visual function that are easily administered on a tablet for screening in primary care. These user-friendly and simple screening tests allow patients to be identified in the early stages of disease for referral to specialists, proper assessment and treatment.
Abstract: Navigation technology in ophthalmology, colloquially called “eye-tracking”, has been applied to various areas of eye care. This approach encompasses motion-based navigation technology in both ophthalmic imaging and treatment. For instance, modern imaging instruments use a real-time eye-tracking system, which helps to reduce motion artefacts and increase signal-to-noise ratio in imaging acquisition such as optical coherence tomography (OCT), microperimetry, and fluorescence and color imaging. Navigation in ophthalmic surgery has been firstly applied in laser vision corrective surgery and spread to involve navigated retinal photocoagulation, and positioning guidance of intraocular lenses (IOL) during cataract surgery. It has emerged as one of the most reliable representatives of technology as it continues to transform surgical interventions into safer, more standardized, and more predictable procedures with better outcomes. Eye-tracking is essential in refractive surgery with excimer laser ablation. Using this technology for cataract surgery in patients with high preoperative astigmatism has produced better therapeutic outcomes. Navigated retinal laser has proven to be safer and more accurate compared to the use of conventional slit lamp lasers. Eye-tracking has also been used in imaging diagnostics, where it is essential for proper alignment of captured zones of interest and accurate follow-up imaging. This technology is not routinely discussed in the ophthalmic literature even though it has been truly impactful in our clinical practice and represents a small revolution in ophthalmology.
