A smartphone-based tool for rapid, portable, and automated wide-field retinal imaging

Author:

Kim Tyson N.,Myers Frank,Reber Clay,Loury PJ,Loumou Panagiota,Webster Doug,Echanique Chris,Li Patrick,Davila Jose R.,Maamari Robi N.,Switz Neil A.,Keenan Jeremy,Woodward Maria A.,Paulus Yannis M.,Margolis Todd,Fletcher Daniel A.

Abstract

AbstractPurposeHigh-quality, wide-field retinal imaging is a valuable method to screen preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging.MethodsThe system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multi-colored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by non-ophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity.ResultsThe system automatically generated 100-degree retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for DR screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%.ConclusionsAutomation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening.Translational RelevanceEnhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.

Publisher

Cold Spring Harbor Laboratory

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