Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on sleep in brain health

LIVE: Thursday 2nd May 2024, 18:00-19:30 (CEST)

Quality sleep is essential for health. But what happens to our brains when sleep patterns are disturbed? Join our experts to explore the interplay between sleep disruption and neurological diseases, and the questions that you need to be asking your patients to help you prevent the harmful effects of sleep deprivation.
ADVANCED SEARCH
Log in
Top
Ophthalmology and Therapy
Published in: Ophthalmology and Therapy 2/2018

Open Access 01-12-2018 | Review

Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review

Authors: Beau J. Fenner, Raymond L. M. Wong, Wai-Ching Lam, Gavin S. W. Tan, Gemmy C. M. Cheung

Published in: Ophthalmology and Therapy | Issue 2/2018

Login to get access

Abstract

Rising prevalence of diabetes worldwide has necessitated the implementation of population-based diabetic retinopathy (DR) screening programs that can perform retinal imaging and interpretation for extremely large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists. While most current screening programs employ mydriatic or nonmydriatic color fundus photography and trained image graders to identify referable DR, new imaging modalities offer significant improvements in diagnostic accuracy, throughput, and affordability. Smartphone-based fundus photography, macular optical coherence tomography, ultrawide-field imaging, and artificial intelligence-based image reading address limitations of current approaches and will likely become necessary as DR becomes more prevalent. Here we review current trends in imaging for DR screening and emerging technologies that show potential for improving upon current screening approaches.
Literature
1.
Cho NH, et al. IDF diabetes atlas. 7th ed. Brussels: International Diabetes Federation; 2015.
2.
3.
Varma R, et al. Prevalence of and risk factors for diabetic macular edema in the United States. JAMA Ophthalmol. 2014;132(11):1334–40.PubMedPubMedCentral
4.
Lee R, Wong TY, Sabanayagam C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis (Lond). 2015;2:17.
5.
Cheung N, Mitchell P, Wong TY. Diabetic retinopathy. Lancet. 2010;376(9735):124–36.PubMed
6.
Aiello LP, et al. Diabetic retinopathy. Diabetes Care. 1998;21(1):143–56.PubMed
7.
Group TDRSR. Photocoagulation treatment of proliferative diabetic retinopathy. Clinical application of Diabetic Retinopathy Study (DRS) findings, DRS Report Number 8. The Diabetic Retinopathy Study Research Group. Ophthalmology. 1981;88(7):583–600.
8.
Group TDRSR. Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. 1991;98(5 Suppl):766–85.
9.
Ross EL, et al. Cost-effectiveness of aflibercept, bevacizumab, and ranibizumab for diabetic macular edema treatment: analysis from the Diabetic Retinopathy Clinical Research Network Comparative Effectiveness Trial. JAMA Ophthalmol. 2016;134(8):888–96.PubMedPubMedCentral
10.
Gangwani RA, et al. Diabetic retinopathy screening: global and local perspective. Hong Kong Med J. 2016;22(5):486–95.PubMed
11.
Stefansson E, et al. Screening and prevention of diabetic blindness. Acta Ophthalmol Scand. 2000;78(4):374–85.PubMed
12.
Tung TH, et al. Economic evaluation of screening for diabetic retinopathy among Chinese type 2 diabetics: a community-based study in Kinmen, Taiwan. J Epidemiol. 2008;18(5):225–33.PubMedPubMedCentral
13.
Lau HC, et al. Mass screening for diabetic retinopathy—a report on diabetic retinal screening in primary care clinics in Singapore. Singap Med J. 1995;36(5):510–3.
14.
Backlund LB, Algvere PV, Rosenqvist U. New blindness in diabetes reduced by more than one-third in Stockholm County. Diabet Med. 1997;14(9):732–40.PubMed
15.
Newcomb PA, Klein R. Factors associated with compliance following diabetic eye screening. J Diabet Complicat. 1990;4(1):8–14.
16.
Thomas RL, et al. Retrospective analysis of newly recorded certifications of visual impairment due to diabetic retinopathy in Wales during 2007–2015. BMJ Open. 2017;7(7):e015024.PubMedPubMedCentral
17.
Wong TY, et al. Guidelines on diabetic eye care: the international council of ophthalmology recommendations for screening, follow-up, referral, and treatment based on resource settings. Ophthalmology. 2018;125(10):1608–22.PubMed
18.
Lian JX, et al. Systematic screening for diabetic retinopathy (DR) in Hong Kong: prevalence of DR and visual impairment among diabetic population. Br J Ophthalmol. 2016;100(2):151–5.PubMed
19.
Prescott G, et al. Improving the cost-effectiveness of photographic screening for diabetic macular oedema: a prospective, multi-centre, UK study. Br J Ophthalmol. 2014;98(8):1042–9.PubMed
20.
Scotland GS, et al. Cost-effectiveness of implementing automated grading within the national screening programme for diabetic retinopathy in Scotland. Br J Ophthalmol. 2007;91(11):1518–23.PubMedPubMedCentral
21.
Kawasaki R, et al. Cost-utility analysis of screening for diabetic retinopathy in Japan: a probabilistic Markov modeling study. Ophthalmic Epidemiol. 2015;22(1):4–12.PubMed
22.
Rachapelle S, et al. The cost-utility of telemedicine to screen for diabetic retinopathy in India. Ophthalmology. 2013;120(3):566–73.PubMed
23.
Lin DY, et al. The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography. Am J Ophthalmol. 2002;134(2):204–13.PubMed
24.
Shi L, et al. Telemedicine for detecting diabetic retinopathy: a systematic review and meta-analysis. Br J Ophthalmol. 2015;99(6):823–31.PubMed
25.
Bernardes R, Serranho P, Lobo C. Digital ocular fundus imaging: a review. Ophthalmologica. 2011;226(4):161–81.PubMed
26.
Li HK, et al. Digital versus film Fundus photography for research grading of diabetic retinopathy severity. Investig Ophthalmol Vis Sci. 2010;51(11):5846–52.
27.
Taylor DJ, et al. Image-quality standardization for diabetic retinopathy screening. Expert Rev Ophthalmol. 2009;4(5):469–76.
28.
Cornsweet T. Pixels in fundus cameras: how many do you need? Int Agency Prev Blindness. 2015(April 3):1–5.
29.
Tyler ME, et al. Characteristics of digital fundus camera system affecting tonal resolution in color retinal images. J Ophthalmic Photo. 2009;31:9–14.
30.
Scanlon PH, et al. Comparison of two reference standards in validating two field mydriatic digital photography as a method of screening for diabetic retinopathy. Br J Ophthalmol. 2003;87(10):1258–63.PubMedPubMedCentral
31.
Scanlon PH, et al. The effectiveness of screening for diabetic retinopathy by digital imaging photography and technician ophthalmoscopy. Diabet Med. 2003;20(6):467–74.PubMed
32.
Murgatroyd H, et al. Effect of mydriasis and different field strategies on digital image screening of diabetic eye disease. Br J Ophthalmol. 2004;88(7):920–4.PubMedPubMedCentral
33.
Group ETDRSR. Grading diabetic retinopathy from stereoscopic color fundus photographs—an extension of the modified Airlie House classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. 1991;98(5 Suppl):786–806.
34.
Zimmer-Galler IE, Zeimer R. Telemedicine in diabetic retinopathy screening. Int Ophthalmol Clin. 2009;49(2):75–86.PubMed
35.
Scanlon PH. The English National Screening Programme for diabetic retinopathy 2003–2016. Acta Diabetol. 2017;54(6):515–25.PubMedPubMedCentral
36.
Wharton H, Gibson J, Dodson P. How accurate are photographic surrogate markers used to detect macular oedema in the English National Screening Programme? In: Royal College of Ophthalmologists Annual Congress. Birmingham: Royal College of Ophthalmologists; 2011. p. 105.
37.
Wong RL, et al. Are we making good use of our public resources? The false-positive rate of screening by fundus photography for diabetic macular oedema. Hong Kong Med J. 2017;23(4):356–64.PubMed
38.
Wang YT, et al. Comparison of prevalence of diabetic macular edema based on monocular fundus photography vs optical coherence tomography. JAMA Ophthalmol. 2016;134(2):222–8.PubMed
39.
O’Halloran RA, Turner AW. Evaluating the impact of optical coherence tomography in diabetic retinopathy screening for an aboriginal population. Clin Exp Ophthalmol. 2018;46(2):116–21.PubMed
40.
Nguyen HV, et al. Cost-effectiveness of a National Telemedicine Diabetic Retinopathy Screening Program in Singapore. Ophthalmology. 2016;123(12):2571–80.PubMed
41.
Bhargava M, et al. Accuracy of diabetic retinopathy screening by trained non-physician graders using non-mydriatic fundus camera. Singap Med J. 2012;53(11):715–9.
42.
McKenna M, et al. Accuracy of trained rural ophthalmologists versus non-medical image graders in the diagnosis of diabetic retinopathy in rural China. Br J Ophthalmol. 2018;102:1471–6.PubMed
43.
Deb N, et al. Screening for diabetic retinopathy in France. Diabetes Metab. 2004;30(2):140–5.PubMed
44.
Owens DR, et al. Screening for diabetic retinopathy. Diabet Med. 1991;8:S4–10.PubMed
45.
Gardner GG, et al. Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool. Br J Ophthalmol. 1996;80(11):940–4.PubMedPubMedCentral
46.
Esteva A, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115–8.PubMedPubMedCentral
47.
Gulshan V, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016;316(22):2402–10.PubMed
48.
Ting DSW, et al. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. JAMA. 2017;318(22):2211–23.PubMedPubMedCentral
49.
Gargeya R, Leng T. Automated identification of diabetic retinopathy using deep learning. Ophthalmology. 2017;124(7):962–9.PubMed
50.
Li Z, et al. Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs. Ophthalmology. 2018;125(8):1199–1206.PubMed
51.
Abramoff MD, et al. Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Investig Ophthalmol Vis Sci. 2016;57(13):5200–6.
52.
Krause J, et al. Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy. Ophthalmology. 2018;125(8):1264–72.PubMed
53.
54.
De Fauw J, et al. Clinically applicable deep learning for diagnosis and referral in retinal disease. Nat Med. 2018;24:1342–50.PubMed
55.
van der Heijden AA, et al. Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System. Acta Ophthalmol. 2018;96(1):63–8.PubMed
56.
Lynch SK, et al. Catastrophic failure in image-based convolutional neural network algorithms for detecting diabetic retinopathy. Investig Ophthalmol Vis Sci. 2017;58:3776.
57.
Choi JY, et al. Multi-categorical deep learning neural network to classify retinal images: a pilot study employing small database. PLoS One. 2017;12(11):e0187336.PubMedPubMedCentral
58.
Silva PS, et al. Peripheral lesions identified on ultrawide field imaging predict increased risk of diabetic retinopathy progression over 4 years. Ophthalmology. 2015;122(5):949–56.PubMed
59.
Silva PS, et al. Diabetic retinopathy severity and peripheral lesions are associated with nonperfusion on ultrawide field angiography. Ophthalmology. 2015;122(12):2465–72.PubMed
60.
Silva PS, et al. Nonmydriatic ultrawide field retinal imaging compared with dilated standard 7-field 35-mm photography and retinal specialist examination for evaluation of diabetic retinopathy. Am J Ophthalmol. 2012;154(3):549–59.PubMed
61.
Wessel MM, et al. Ultra-wide-field angiography improves the detection and classification of diabetic retinopathy. Retina. 2012;32(4):785–91.PubMed
62.
Silva PS, et al. Hemorrhage and/or microaneurysm severity and count in ultrawide field images and early treatment diabetic retinopathy study photography. Ophthalmology. 2017;124(7):970–6.PubMed
63.
Silva PS, et al. Identification of diabetic retinopathy and ungradable image rate with ultrawide field imaging in a National Teleophthalmology Program. Ophthalmology. 2016;123(6):1360–7.PubMed
64.
Hackenthal V. New scan for diabetic eye disease is better, but at a cost. In: Medscape ophthalmology. National Libraries of Medicine. 2016.
65.
Tan ACS, et al. An overview of the clinical applications of optical coherence tomography angiography. Eye (Lond). 2018;32(2):262–86.
66.
Spaide RF, et al. Optical coherence tomography angiography. Prog Retin Eye Res. 2018;64:1–55.PubMed
67.
Krawitz BD, et al. Acircularity index and axis ratio of the foveal avascular zone in diabetic eyes and healthy controls measured by optical coherence tomography angiography. Vis Res. 2017;139:177–86.PubMed
68.
Agemy SA, et al. Retinal vascular perfusion density mapping using optical coherence tomography angiography in normals and diabetic retinopathy patients. Retina. 2015;35(11):2353–63.PubMed
69.
Dupas B, et al. Association between vessel density and visual acuity in patients with diabetic retinopathy and poorly controlled type 1 diabetes. JAMA Ophthalmol. 2018;136(7):721–8.PubMedPubMedCentral
70.
Ting DSW, et al. Optical coherence tomographic angiography in type 2 diabetes and diabetic retinopathy. JAMA Ophthalmol. 2017;135(4):306–12.PubMed
71.
Samara WA, et al. Quantification of diabetic macular ischemia using optical coherence tomography angiography and its relationship with visual acuity. Ophthalmology. 2017;124(2):235–44.PubMed
72.
Lord RK, et al. Novel uses of smartphones in ophthalmology. Ophthalmology. 2010;117(6):1274e3.
73.
Tan GS, et al. Is routine pupil dilation safe among asian patients with diabetes? Investig Ophthalmol Vis Sci. 2009;50(9):4110–3.
74.
Toy BC, et al. Smartphone-based dilated fundus photography and near visual acuity testing as inexpensive screening tools to detect referral warranted diabetic eye disease. Retina. 2016;36(5):1000–8.PubMed
75.
Ryan ME, et al. Comparison among methods of retinopathy assessment (CAMRA) study: smartphone, nonmydriatic, and mydriatic photography. Ophthalmology. 2015;122(10):2038–43.PubMed
76.
Russo A, et al. Comparison of smartphone ophthalmoscopy with slit-lamp biomicroscopy for grading diabetic retinopathy. Am J Ophthalmol. 2015;159(2):360–4.PubMed
77.
Rajalakshmi R, et al. Validation of smartphone based retinal photography for diabetic retinopathy screening. PLoS One. 2015;10(9):e0138285.PubMedPubMedCentral
78.
Wadhwani M, et al. Diabetic retinopathy screening programme utilising non-mydriatic fundus imaging in slum populations of New Delhi, India. Trop Med Int Health. 2018;23(4):405–14.PubMed
79.
Sengupta S, et al. Screening for vision-threatening diabetic retinopathy in South India: comparing portable non-mydriatic and standard fundus cameras and clinical exam. Eye (Lond). 2018;32(2):375–83.
80.
Sharma A. Emerging simplified retinal imaging. Dev Ophthalmol. 2017;60:56–62.PubMed
81.
Matimba A, et al. Tele-ophthalmology: opportunities for improving diabetes eye care in resource- and specialist-limited Sub-Saharan African countries. J Telemed Telecare. 2016;22(5):311–6.PubMed
82.
Rajalakshmi R, et al. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence. Eye (Lond). 2018;32(6):1138–44.
83.
Pieczynski J, Grzybowski A. Review of diabetic retinopathy screening methods and programmes adopted in different parts of the world. Eur Ophthal Rev. 2015;9(1):49–55.
84.
Tozer K, Woodward MA, Newman-Casey PA. Telemedicine and diabetic retinopathy: review of published screening programs. J Endocrinol Diabetes. 2015;2(4):1–10.
85.
Li HK, et al. Telehealth practice recommendations for diabetic retinopathy, second edition. Telemed J E-Health. 2011;17(10):814–37.PubMedPubMedCentral
86.
Zimmer-Galler I, Zeimer R. Results of implementation of the DigiScope for diabetic retinopathy assessment in the primary care environment. Telemed J E Health. 2006;12(2):89–98.PubMed
87.
Cuadros J, Bresnick G. EyePACS: an adaptable telemedicine system for diabetic retinopathy screening. J Diabetes Sci Technol. 2009;3(3):509–16.PubMedPubMedCentral
88.
Massin P, et al. OPHDIAT: a telemedical network screening system for diabetic retinopathy in the Ile-de-France. Diabetes Metab. 2008;34(3):227–34.PubMed
89.
Schulze-Dobold C, et al. Ophdiat((R)): five-year experience of a telemedical screening programme for diabetic retinopathy in Paris and the surrounding area. Diabetes Metab. 2012;38(5):450–7.PubMed
90.
Abramoff MD, Suttorp-Schulten MS. Web-based screening for diabetic retinopathy in a primary care population: the EyeCheck project. Telemed J E Health. 2005;11(6):668–74.PubMed
91.
Sampson CJ, et al. Stratifying the NHS Diabetic Eye Screening Programme: into the unknown? Diabet Med. 2016;33(12):1612–4.PubMed
92.
Sanchez CR, et al. Ocular telemedicine for diabetic retinopathy and the Joslin Vision Network. Semin Ophthalmol. 2010;25(5–6):218–24.PubMed
93.
Aiello LM, et al. Joslin Vision Network Validation Study: pilot image stabilization phase. J Am Optom Assoc. 1998;69(11):699–710.PubMed
94.
Lim MC, et al. Diabetic retinopathy in diabetics referred to a tertiary centre from a nationwide screening programme. Ann Acad Med Singap. 2008;37(9):753–9.PubMed
95.
Nathoo N, et al. The prevalence of diabetic retinopathy as identified by teleophthalmology in rural Alberta. Can J Ophthalmol. 2010;45(1):28–32.PubMed
96.
Ng M, et al. Improving access to eye care: teleophthalmology in Alberta, Canada. J Diabetes Sci Technol. 2009;3(2):289–96.PubMedPubMedCentral
97.
Ting DS, Tay-Kearney ML, Kanagasingam Y. Light and portable novel device for diabetic retinopathy screening. Clin Exp Ophthalmol. 2012;40(1):e40–6.PubMed
98.
Zhang W, et al. Screening for diabetic retinopathy using a portable, noncontact, nonmydriatic handheld retinal camera. J Diabetes Sci Technol. 2017;11(1):128–34.PubMed
Metadata
Title
Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review
Authors
Beau J. Fenner
Raymond L. M. Wong
Wai-Ching Lam
Gavin S. W. Tan
Gemmy C. M. Cheung
Publication date
01-12-2018
Publisher
Springer Healthcare
Published in
Ophthalmology and Therapy / Issue 2/2018
Print ISSN: 2193-8245
Electronic ISSN: 2193-6528
DOI
https://doi.org/10.1007/s40123-018-0153-7

Other articles of this Issue 2/2018

Ophthalmology and Therapy 2/2018 Go to the issue

Review

Latest Clinical Approaches in the Ocular Management of Cystinosis: A Review of Current Practice and Opinion from the Ophthalmology Cystinosis Forum

Commentary

“Doctor, I have a Sulfa Allergy”: Clarifying the Myths of Cross-Reactivity

Review

Iluvien™ (Fluocinolone Acetonide 0.19 mg Intravitreal Implant) in the Treatment of Diabetic Macular Edema: A Review

Original Research

Three-Year Outcomes of Aflibercept Treatment for Neovascular Age-Related Macular Degeneration: Evidence from a Clinical Setting

Original Research

Knowledge, Awareness, and Eye Care-Seeking Behavior in Diabetic Retinopathy: A Cross-Sectional Study in Jeddah, Kingdom of Saudi Arabia

Review

Continuous Transitional Focus (CTF): A New Concept in Ophthalmic Surgery

ACC 2024 Congress Coverage

Heart Failure Video

Year in Review: Heart failure and cardiomyopathies

Watch now

Watch this official video from ACC.24 to hear Dr. Biykem Bozkurt discuss last year's major advances in heart failure and cardiomyopathies.

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits