Diabetic Retinopathy Screening Using Smartphone-Based Fundus Imaging in India


      Early detection and treatment can prevent irreversible blindness from diabetic retinopathy (DR), which is the leading cause of visual impairment among working-aged adults worldwide. Some 80% of affected persons live in low- and middle-income countries, yet lack of resources has largely prevented DR screening implementation in these world regions. Smartphone-based fundus imaging (SBFI) allows for low-cost mobile fundus examination using an adapter on a smartphone; however, key aspects such as image quality, diagnostic accuracy, and comparability of different approaches have not been systematically assessed to date.


      Evaluation of diagnostic technology.


      A total of 381 eyes of 193 patients with diabetes were recruited at outreach eye clinics in South India.


      We compared 4 technically different approaches of SBFI (3 approaches based on direct and 1 approach based on indirect ophthalmoscopy) in terms of image quality and diagnostic accuracy for DR screening.

      Main Outcome Measures

      Image quality (sharpness/focus, reflex artifacts, contrast, and illumination), field-of-view, examination time, and diagnostic accuracy for DR screening were analyzed against conventional fundus photography and clinical examination.


      Smartphone-based fundus imaging based on indirect ophthalmoscopy yielded the best image quality (P < 0.01), the largest field-of-view, and the longest examination time (111 vs. 68–86 seconds, P < 0.0001). Agreement with the reference standard (Cohen’s kappa 0.868) and sensitivity/specificity to detect DR were highest for the indirect SBFI approach (0.79/0.99 for any DR and 1.0/1.0 for severe DR, 0.79/1.0 for diabetic maculopathy).


      Smartphone-based fundus imaging can meet DR screening requirements in an outreach setting; however, not all devices are suitable in terms of image quality and diagnostic accuracy. Smartphone-based fundus imaging might aid in alleviating the burden of DR screening in low- and middle-income countries, and these results will allow for a better selection of SBFI devices in field trials for DR screening.

      Abbreviations and Acronyms:

      DR (diabetic retinopathy), SBFI (smartphone-based fundus imaging), WHO (World Health Organization)
      To read this article in full you will need to make a payment
      Subscribe to Ophthalmology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Cheung N.
        • Mitchell P.
        • Wong T.Y.
        Diabetic retinopathy.
        Lancet. 2010; 376: 124-136
        • Yau J.W.
        • Rogers S.L.
        • Kawasaki R.
        • et al.
        Global prevalence and major risk factors of diabetic retinopathy.
        Diabetes Care. 2012; 35: 556-564
        • International Diabetes Federation
        IDF Diabetes Atlas.
        8th ed. IDF, Brussels, Belgium2017
        • World Health Organization
        Global Report on Diabetes.
        WHO, Geneva, Switzerland2016
        • Flaxman S.R.
        • Bourne R.R.A.
        • Resnikoff S.
        • et al.
        Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis.
        Lancet Glob Health. 2017; 5: e1221-e1234
        • Ruta L.M.
        • Magliano D.J.
        • Lemesurier R.
        • et al.
        Prevalence of diabetic retinopathy in type 2 diabetes in developing and developed countries.
        Diabet Med. 2013; 30: 387-398
        • International Diabetes Federation
        The Diabetic Retinopathy Barometer Report: Global Findings.
        IDF, Brussels, Belgium2017
        • Sabanayagam C.
        • Banu R.
        • Chee M.L.
        • et al.
        Incidence and progression of diabetic retinopathy: a systematic review.
        Lancet Diabetes Endocrinol. 2019; 7: 140-149
        • Singer D.E.
        • Nathan D.M.
        • Fogel H.A.
        • Schachat A.P.
        Screening for diabetic retinopathy.
        Ann Intern Med. 1992; 116: 660-671
        • Ramasamy K.
        • Raman R.
        • Tandon M.
        Current state of care for diabetic retinopathy in India.
        Curr Diab Rep. 2013; 13: 460-468
        • Sasongko M.B.
        • Widyaputri F.
        • Agni A.N.
        • et al.
        Prevalence of diabetic retinopathy and blindness in Indonesian adults with type 2 diabetes.
        Am J Ophthalmol. 2017; 181: 79-87
        • Song P.
        • Yu J.
        • Chan K.Y.
        • et al.
        Prevalence, risk factors and burden of diabetic retinopathy in China: a systematic review and meta-analysis.
        J Glob Health. 2018; 8010803
        • Murthy K.R.
        • Murthy P.R.
        • Kapur A.
        • Owens D.R.
        Mobile diabetes eye care: experience in developing countries.
        Diabetes Res Clin Pract. 2012; 97: 343-349
        • Sabanayagam C.
        • Yip W.
        • Ting D.S.
        • et al.
        Ten emerging trends in the epidemiology of diabetic retinopathy.
        Ophthalmic Epidemiol. 2016; 23: 209-222
        • World Health Organization
        Global Initiative for the Elimination of Avoidable Blindness Action Plan 2006–2011.
        WHO, Geneva, Switzerland2007
        • Jones S.
        • Edwards R.T.
        Diabetic retinopathy screening: a systematic review of the economic evidence.
        Diabet Med. 2010; 27: 249-256
        • Rachapelle S.
        • Legood R.
        • Alavi Y.
        • et al.
        The cost-utility of telemedicine to screen for diabetic retinopathy in India.
        Ophthalmology. 2013; 120: 566-573
        • Shi L.
        • Wu H.
        • Dong J.
        • et al.
        Telemedicine for detecting diabetic retinopathy: a systematic review and meta-analysis.
        Br J Ophthalmol. 2015; 99: 823-831
        • Zimmer-Galler I.E.
        • Kimura A.E.
        • Gupta S.
        Diabetic retinopathy screening and the use of telemedicine.
        Curr Opin Ophthalmol. 2015; 26: 167-172
        • Lord R.K.
        • Shah V.A.
        • Filippo A.N.S.
        • Krishna R.
        Novel uses of smartphones in ophthalmology.
        Ophthalmology. 2010; 117: 1274-1274.e3
        • Bastawrous A.
        Smartphone fundoscopy.
        Ophthalmology. 2012; 119: 432-433.e2
        • Bolster N.M.
        • Giardini M.E.
        • Livingstone I.A.
        • Bastawrous A.
        How the smartphone is driving the eye-health imaging revolution.
        Exp Rev Ophthalmol. 2014; 9: 475-485
        • Jani P.D.
        • Forbes L.
        • Choudhury A.
        • et al.
        Evaluation of diabetic retinal screening and factors for ophthalmology referral in a telemedicine network.
        JAMA Ophthalmol. 2017; 135: 706-714
        • Ryan M.E.
        • Rajalakshmi R.
        • Prathiba V.
        • et al.
        Comparison among methods of retinopathy assessment (CAMRA) study smartphone, nonmydriatic, and mydriatic photography.
        Ophthalmology. 2015; 122: 2038-2043
        • Russo A.
        • Morescalch F.
        • Costagliola C.
        • et al.
        Comparison of smartphone ophthalmoscopy with slit-lamp biomicroscopy for grading diabetic retinopathy.
        Am J Ophthalmol. 2015; 159: 360-364
        • Rajalakshmi R.
        • Arulmalar S.
        • Usha M.
        • et al.
        Validation of smartphone based retinal photography for diabetic retinopathy screening.
        PLoS One. 2015; 10
        • Toy B.C.
        • Myung D.J.
        • 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: 1000-1008
        • Kim T.N.
        • 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: 21
        • Bilong Y.
        • Katte J.C.
        • Koki G.
        • et al.
        Validation of smartphone-based retinal photography for diabetic retinopathy screening.
        Ophthalmic Surg Lasers Imaging Retina. 2019; 50: S18-S22
        • Petersmann A.
        • Nauck M.
        • Muller-Wieland D.
        • et al.
        Definition, classification and diagnosis of diabetes mellitus.
        Exp Clin Endocrinol Diabetes. 2018; 126: 406-410
        • Shanmugam M.P.
        • Mishra D.K.C.
        • Madhukumar R.
        • et al.
        Fundus imaging with a mobile phone: a review of techniques.
        Indian J Ophthalmol. 2014; 62: 960-962
        • Wilkinson C.P.
        • Ferris 3rd, F.L.
        • Klein R.E.
        • et al.
        Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales.
        Ophthalmology. 2003; 110: 1677-1682
        • Vujosevic S.
        • Aldington S.J.
        • Silva P.
        • et al.
        Screening for diabetic retinopathy: new perspectives and challenges.
        Lancet Diabetes Endocrinol. 2020; 8: 337-347
        • Wang L.Z.
        • Cheung C.Y.
        • Tapp R.J.
        • et al.
        Availability and variability in guidelines on diabetic retinopathy screening in Asian countries.
        Br J Ophthalmol. 2017; 101: 1352-1360
        • Taylor R.
        • Broadbent D.M.
        • Greenwood R.
        • et al.
        Mobile retinal screening in Britain.
        Diabet Med. 1998; 15: 344-347
        • Papavasileiou E.
        • Dereklis D.
        • Oikonomidis P.
        • et al.
        An effective programme to systematic diabetic retinopathy screening in order to reduce diabetic retinopathy blindness.
        Hell J Nucl Med. 2014; 17: 30-34
        • DeBuc D.C.
        The role of retinal imaging and portable screening devices in tele-ophthalmology applications for diabetic retinopathy management.
        Curr Diabet Rep. 2016; 16: 132
        • Mohammadpour M.
        • Heidari Z.
        • Mirghorbani M.
        • Hashemi H.
        Smartphones, tele-ophthalmology, and VISION 2020.
        Int J Ophthalmol. 2017; 10: 1909-1918
        • Wyatt K.D.
        • Willaert B.N.
        • Pallagi P.J.
        • et al.
        PhotoExam: adoption of an iOS-based clinical image capture application at Mayo Clinic.
        Int J Dermatol. 2017; 56: 1359-1365
        • Tse C.
        • Patel R.M.
        • Yoon R.
        • et al.
        The endoscope using next generation smartphones: “a global opportunity”.
        J Endourol. 2018; 32: 765-770
        • Lu S.
        • Cottone C.M.
        • Yoon R.
        • et al.
        Endoscope: a disruptive endoscopic technology.
        J Endourol. 2019; 33: 960-965
        • Rao G.N.
        • Khanna R.
        • Payal A.
        The global burden of cataract.
        Curr Opin Ophthalmol. 2011; 22: 4-9
        • Ting D.
        • Cheung C.
        • 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: 2211-2223
        • van der Heijden A.A.
        • Abramoff M.D.
        • Verbraak F.
        • 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: 63-68
        • Rajalakshmi R.
        • Subashini R.
        • Anjana R.M.
        • Mohan V.
        Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.
        Eye (Lond). 2018; 32: 1138-1144
        • Natarajan S.
        • Jain A.
        • Krishnan R.
        • et al.
        Diagnostic accuracy of community-based diabetic retinopathy screening with an offline artificial intelligence system on a smartphone.
        JAMA Ophthalmol. 2019; 137: 1182-1188
        • Nussenblatt R.B.
        • Palestine A.G.
        • Chan C.C.
        • Roberge F.
        Standardization of vitreal inflammatory activity in intermediate and posterior uveitis.
        Ophthalmology. 1985; 92: 467-471
        • Chylack Jr., L.T.
        • Wolfe J.K.
        • Singer D.M.
        • et al.
        The Lens Opacities Classification System III. The Longitudinal Study of Cataract Study Group.
        Arch Ophthalmol. 1993; 111: 831-836
        • Jabs D.A.
        • Nussenblatt R.B.
        • Rosenbaum J.T.
        Standardization of Uveitis Nomenclature (SUN) Working Group. Standardization of Uveitis Nomenclature for Reporting Clinical Data. Results of the First International Workshop.
        Am J Ophthalmol. 2005; 140: 509-516
        • Munk M.R.
        • Giannakaki-Zimmermann H.
        • Berger L.
        • et al.
        OCT-angiography: a qualitative and quantitative comparison of 4 OCT-A devices.
        PLoS One. 2017; 12e0177059