Efficacy of smartphone-based retinal photography by undergraduate students in screening and early diagnosing diabetic retinopathy

Jéssica Deponti Gobbi; João Pedro Romero Braga; Moises M Lucena; Victor C F Bellanda; Miguel V S Frasson; Daniel Ferraz; Victor Koh; Rodrigo Jorge

doi:10.1186/s40942-022-00388-y

Efficacy of smartphone-based retinal photography by undergraduate students in screening and early diagnosing diabetic retinopathy

Int J Retina Vitreous. 2022 Jun 7;8(1):35. doi: 10.1186/s40942-022-00388-y.

Authors

Jéssica Deponti Gobbi¹, João Pedro Romero Braga¹, Moises M Lucena¹, Victor C F Bellanda¹, Miguel V S Frasson², Daniel Ferraz³, Victor Koh⁴, Rodrigo Jorge⁵

Affiliations

¹ Division of Ophthalmology, Ribeirão Preto Medical School, University of São Paulo, 3900, Bandeirantes Ave, Ribeirão Preto, SP, 14049-900, Brazil.
² Department of Applied Mathematics and Statistics, University of São Paulo, São Carlos, Brazil.
³ Federal University of São Paulo; D'or Institute of Teaching and Research, São Paulo, Brazil.
⁴ Department of Ophthalmology, National University Hospital, Singapore, Singapore.
⁵ Division of Ophthalmology, Ribeirão Preto Medical School, University of São Paulo, 3900, Bandeirantes Ave, Ribeirão Preto, SP, 14049-900, Brazil. rjorge@fmrp.usp.br.

Abstract

Background: To evaluate the efficacy of retinal photography obtained by undergraduate students using a smartphone-based device in screening and early diagnosing diabetic retinopathy (DR).

Methods: We carried out an open prospective study with ninety-nine diabetic patients (194 eyes), who were submitted to an ophthalmological examination in which undergraduate students registered images of the fundus using a smartphone-based device. At the same occasion, an experienced nurse captured fundus photographs from the same patients using a gold standard tabletop camera system (Canon CR-2 Digital Non-Mydriatic Retinal Camera), with a 45º field of view. Two distinct masked specialists evaluated both forms of imaging according to the presence or absence of sings of DR and its markers of severity. We later compared those reports to assess agreement between the two technologies.

Results: Concerning the presence or absence of DR, we found an agreement rate of 84.07% between reports obtained from images of the smartphone-based device and from the regular (tabletop) fundus camera; Kappa: 0.67; Sensitivity: 71.0% (Confidence Interval [CI]: 65.05-78.16%); Specificity: 94.06% (CI: 90.63-97.49%); Accuracy: 84.07%; Positive Predictive Value (PPV): 90.62%; Negative Predictive Value (NPV): 80.51%. As for the classification between proliferative diabetic retinopathy and non-proliferative diabetic retinopathy, we found an agreement of 90.00% between the reports; Kappa: 0.78; Sensitivity: 86.96%; (CI: 79.07-94.85%); Specificity: 91.49% (CI: 84.95-98.03%); Accuracy: 90.00%; PPV: 83.33%; NPV: 93.48%. Regarding the degree of classification of DR, we found an agreement rate of 69.23% between the reports; Kappa: 0.52. As relating to the presence or absence of hard macular exudates, we found an agreement of 84.07% between the reports; Kappa: 0.67; Sensitivity: 71.60% (CI: 65.05-78.16%); Specificity: 94.06% (CI: 90.63-97.49%); Accuracy: 84.07%; PPV: 90.62%; NPV: 80.51%.

Conclusion: The smartphone-based device showed promising accuracy in the detection of DR (84.07%), making it a potential tool in the screening and early diagnosis of DR.

Keywords: Diabetic retinopathy; Early diagnosis; Low cost technology; Ophthalmological diagnosis techniques; Retina; Telemedicine.