A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

Autor:	Kim TN; Department of Ophthalmology and Visual Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA.; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA.; Department of Ophthalmology, University of California, San Francisco, CA, USA., Myers F; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Reber C; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Loury PJ; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Loumou P; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Webster D; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Echanique C; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA., Li P; Department of Ophthalmology and Visual Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA., Davila JR; Department of Ophthalmology and Visual Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA., Maamari RN; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA.; Department of Ophthalmology and Visual Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA., Switz NA; Department of Physics and Astronomy, San José State University, San Jose, CA, USA., Keenan J; Department of Ophthalmology, University of California, San Francisco, CA, USA., Woodward MA; Department of Ophthalmology and Visual Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA., Paulus YM; Department of Ophthalmology and Visual Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA., Margolis T; Department of Ophthalmology and Visual Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA., Fletcher DA; Department of Bioengineering and Biophysics Program, University of California, Berkeley, Berkeley, CA, USA.; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
Jazyk:	angličtina
Zdroj:	Translational vision science & technology [Transl Vis Sci Technol] 2018 Oct 01; Vol. 7 (5), pp. 21. Date of Electronic Publication: 2018 Oct 01 (Print Publication: 2018).
DOI:	10.1167/tvst.7.5.21
Abstrakt:	Purpose: High-quality, wide-field retinal imaging is a valuable method for screening 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. Methods: The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. Results: The system automatically generated 100° 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 diabetic retinopathy (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%. Conclusions: Automation-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 Relevance: Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu