Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review

References

• Yau JWY, Rogers SL, Kawasaki R, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012;35(3):556–564. doi:10.2337/dc11-1909
   PubMed Web of Science ®Google Scholar
• Sasongko MB, Widyaputri F, Agni AN, et al. Prevalence of diabetic retinopathy and blindness in Indonesian adults with type 2 diabetes. Am J Ophthalmol. 2017;181:79–87.
   PubMed Web of Science ®Google Scholar
• Leasher JL, Bourne RR, Flaxman SR, et al. Global estimates on the number of people blind or visually impaired by diabetic retinopathy: a meta-analysis from 1990 to 2010. Diabetes Care. 2016;39(9):1643–1649.
   PubMed Web of Science ®Google Scholar
• Royle P, Mistry H, Auguste P, et al. Pan-retinal photocoagulation and other forms of laser treatment and drug therapies for non-proliferative diabetic retinopathy: systematic review and economic evaluation. Health Technol Assess. 2015;19(51):v–xxviii, 1–247.
   Web of Science ®Google Scholar
• El Rami H, Barham R, Sun JK, Silva PS. Evidence-based treatment of diabetic retinopathy. Semin Ophthalmol. 2017;32(1):67–74.
   PubMed Web of Science ®Google Scholar
• The Diabetic Retinopathy Study Research Group. Photocoagulation treatment of proliferative diabetic retinopathy. Clinical application of Diabetic Retinopathy Study (DRS) findings, DRS report number 8. Ophthalmology. 1981;88(7):583–600.
   PubMed Web of Science ®Google Scholar
• Wong TY, Sun J, Kawasaki R, 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):1608–1622.
   PubMed Web of Science ®Google Scholar
• American Diabetes Association. Microvascular complications and foot care: standards of medical care in diabetes-2021. Diabetes Care. 2021;44(Suppl 1):S151–S167.
   PubMed Web of Science ®Google Scholar
• Vujosevic S, Aldington SJ, Silva P, et al. Screening for diabetic retinopathy: new perspectives and challenges. Lancet Diabetes Endocrinol. 2020;8(4):337–347.
   PubMed Web of Science ®Google Scholar
• Murthy KR, Murthy PR, Kapur A, Owens DR. Mobile diabetes eye care: experience in developing countries. Diabetes Res Clin Pract. 2012;97(3):343–349.
   PubMed Web of Science ®Google Scholar
• Natarajan S, Jain A, Krishnan R, Rogye A, Sivaprasad S. Diagnostic accuracy of community-based diabetic retinopathy screening with an offline artificial intelligence system on a smartphone. JAMA Ophthalmol. 2019;137(10):1182–1188.
   PubMed Web of Science ®Google Scholar
• Rajalakshmi R, Subashini R, Anjana RM, Mohan V. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence. Eye. 2018;32(6):1138–1144.
   PubMed Web of Science ®Google Scholar
• Bilong Y, Katte JC, Koki G, et al. Validation of smartphone-based retinal photography for diabetic retinopathy screening. Ophthalmic Surg Lasers Imaging Retina. 2019;50(5):S18–S22.
   PubMed Web of Science ®Google Scholar
• Kim TN, Myers F, Reber C, et al. A smartphone-based tool for rapid, portable, and automated wide-field retinal imaging. Transl Vis Sci Technol. 2018;7(5):21.
   PubMed Web of Science ®Google Scholar
• Kanclerz P, Tuuminen R, Khoramnia R. Imaging modalities employed in diabetic retinopathy screening: a review and meta-analysis. Diagnostics. 2021;11(10):154.
   Web of Science ®Google Scholar
• Piyasena M, Murthy GVS, Yip JLY, et al. Systematic review and meta-analysis of diagnostic accuracy of detection of any level of diabetic retinopathy using digital retinal imaging. Syst Rev. 2018;7(1):182.
   PubMedGoogle Scholar
• Tan CH, Kyaw BM, Smith H, Tan CS, Tudor Car L. Use of smartphones to detect diabetic retinopathy: scoping review and meta-analysis of diagnostic test accuracy studies. J Med Internet Res. 2020;22(5):e16658.
   PubMed Web of Science ®Google Scholar
• Prayogo M, Sasongko M, At Thobari J, et al. Accuracy of low-cost smartphone-based screening test for diabetic retinopathy - a systematic review; 2021. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021249746. Accessed July 25, 2023.
   Google Scholar
• Toy BC, Myung DJ, He L, 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):1000–1008.
   PubMed Web of Science ®Google Scholar
• Russo A, Morescalchi F, Costagliola C, Delcassi L, Semeraro F. Comparison of smartphone ophthalmoscopy with slit-lamp biomicroscopy for grading diabetic retinopathy. Am J Ophthalmol. 2015;159(2):360–364 e361.
   PubMed Web of Science ®Google Scholar
• Wintergerst MWM, Mishra DK, Hartmann L, et al. Diabetic retinopathy screening using smartphone-based fundus imaging in India. Ophthalmology. 2020;127(11):1529–1538.
   PubMed Web of Science ®Google Scholar
• Baeza M, Orozco-Beltran D, Gil-Guillen VF, et al. Screening for sight threatening diabetic retinopathy using non-mydriatic retinal camera in a primary care setting: to dilate or not to dilate? Int J Clin Pract. 2009;63(3):433–438.
   PubMed Web of Science ®Google Scholar
• Early Treatment Diabetic Retinopathy Study Research Group. Grading diabetic retinopathy from stereoscopic color fundus photographs--an extension of the modified Airlie House classification. ETDRS report number 10. Ophthalmology. 1991;98(5 Suppl):786–806.
   PubMed Web of Science ®Google Scholar
• Murgatroyd H, Ellingford A, Cox A, et al. Effect of mydriasis and different field strategies on digital image screening of diabetic eye disease. Br J Ophthalmol. 2004;88(7):920–924.
   PubMed Web of Science ®Google Scholar
• Emanuele N, Klein R, Moritz T, et al. Comparison of dilated fundus examinations with seven-field stereo fundus photographs in the Veterans Affairs Diabetes Trial. J Diabetes Complications. 2009;23(5):323–329.
   PubMed Web of Science ®Google Scholar
• Gulshan V, Rajan RP, Widner K, et al. Performance of a deep-learning algorithm vs manual grading for detecting diabetic retinopathy in India. JAMA Ophthalmol. 2019;137(9):987–993.
   PubMed Web of Science ®Google Scholar
• Gulshan V, Peng L, Coram M, et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA. 2016;316(22):2402–2410.
   PubMed Web of Science ®Google Scholar
• Ting DSW, Cheung CY, Lim G, 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):2211–2223.
   PubMed Web of Science ®Google Scholar
• Özbay E. An active deep learning method for diabetic retinopathy detection in segmented fundus images using artificial bee colony algorithm. Artif Intell Rev. 2023;56(4):3291–3318.
   Web of Science ®Google Scholar
• Fenner BJ, Wong RLM, Lam WC, Tan GSW, Cheung GCM. Advances in retinal imaging and applications in diabetic retinopathy screening: a review. Ophthalmol Ther. 2018;7(2):333–346.
   PubMed Web of Science ®Google Scholar
• Scanlon PH. The English National Screening Programme for diabetic retinopathy 2003–2016. Acta Diabetol. 2017;54(6):515–525.
   PubMed Web of Science ®Google Scholar
• von Wendt G, Ronnholm P, Heikkila K, Summanen P. A comparison between one- and two-field 60 degree fundus photography when screening for diabetic retinopathy. Acta Ophthalmol Scand. 2000;78(1):14–20.
   PubMedGoogle Scholar
• Sivaraman A, Nagarajan S, Vadivel S, et al. A novel, smartphone-based, teleophthalmology-enabled, widefield fundus imaging device with an autocapture algorithm. Transl Vis Sci Technol. 2021;10(12):21.
   PubMed Web of Science ®Google Scholar
• Ghasemi Falavarjani K, Tsui I, Sadda SR. Ultra-wide-field imaging in diabetic retinopathy. Vision Res. 2017;139:187–190.
   PubMed Web of Science ®Google Scholar
• Aiello LP, Odia I, Glassman AR, et al. Comparison of early treatment diabetic retinopathy study standard 7-field imaging with ultrawide-field imaging for determining severity of diabetic retinopathy. JAMA Ophthalmol. 2019;137(1):65–73.
   PubMed Web of Science ®Google Scholar
• Pandey R, Morgan MM, Murphy C, et al. Irish National Diabetic RetinaScreen Programme: report on five rounds of retinopathy screening and screen-positive referrals. (INDEAR study report no. 1). Br J Ophthalmol. 2022;106(3):409–414.
   PubMed Web of Science ®Google Scholar
• Sasongko MB, Indrayanti SR, Wardhana FS, et al. Low utility of diabetic eye care services and perceived barriers to optimal diabetic retinopathy management in Indonesian adults with vision-threatening diabetic retinopathy. Diabetes Res Clin Pract. 2021;171:108540.
   PubMed Web of Science ®Google Scholar
• Sasongko MB, Wardhana FS, Febryanto GA, et al. The estimated healthcare cost of diabetic retinopathy in Indonesia and its projection for 2025. Br J Ophthalmol. 2020;104(4):487–492.
   PubMed Web of Science ®Google Scholar
• Yusuf AM, Lusobya RC, Mukisa J, Batte C, Nakanjako D, Juliet-Sengeri O. Validity of smartphone-based retinal photography (PEEK-retina) compared to the standard ophthalmic fundus camera in diagnosing diabetic retinopathy in Uganda: a cross-sectional study. PLoS One. 2022;17(9):e0273633.
   PubMed Web of Science ®Google Scholar
• Prathiba V, Rajalakshmi R, Arulmalar S, et al. Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy. Indian J Ophthalmol. 2020;68(Suppl 1):S42–S46.
   PubMedGoogle Scholar
• Rajalakshmi R, Arulmalar S, Usha M, et al. Validation of smartphone based retinal photography for diabetic retinopathy screening. PLoS One. 2015;10(9):e0138285.
   PubMed Web of Science ®Google Scholar
• de Oliveira JAE, Nakayama LF, Zago Ribeiro L, et al. Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening. Acta Diabetol. 2023;2023:1–7.
   Google Scholar
• Bastawrous A, Giardini ME, Bolster NM, et al. Clinical validation of a smartphone-based adapter for optic disc imaging in Kenya. JAMA Ophthalmol. 2016;134(2):151–158.
   PubMed Web of Science ®Google Scholar
• Titoneli CC, Filho MS, Lencione D, Vieira FP, Stuchi JA, Paula JS. Clinical validation of a smartphone-based handheld fundus camera for the evaluation of optic nerve head. Arq Bras Oftalmol. 2021;84(6):531–537.
   PubMed Web of Science ®Google Scholar