Diabetic retinopathy retinal imaging -
Despite the southern region of Brazil being one of the most developed in the country, with the municipality of Blumenau boasting one of the highest Human Development Index HDI levels nationwide, access to early detection of diabetic retinopathy remains highly limited.
Thus, implementing mass screening programs and potentially incorporating regular and continuous assessment utilizing portable cameras in primary healthcare facilities could help decrease waiting times and improve access. This approach would serve as an effective strategy to mitigate diabetes-related blindness cases.
A sentence has been included in the discussion to address this aspect. We believe the main strength of this study is to present an automatic system with a potential to yield a high sensitivity for DR screening after evaluation of a single retinal image per eye; of note, the sensitivity attained was higher than the pre-specified endpoint for FDA approval of an automatic DR screening system [ 5 ].
Further steps for a DR screening program that would deploy the present tool could include acquisition of a second fundus image per eye only for detected cases, thereby rendering the screening process simpler for most patients, who would only need one image; further studies are needed to investigate this hypothesis.
Our study has several limitations, the most notable of which is that human grading was performed by only one specialist, a potential source of bias. Additionally, automatic evaluation was performed only on images with sufficient quality, limiting partially our conclusions regarding the real world, when a considerable rate of patients has ungradable images, mainly due to cataracts.
Furthermore, diabetic maculopathy was not evaluated with gold standard methods; instead, its presence was inferred in non-stereoscopic images. Finally, the lack of comprehensive clinical and laboratory data is also a limitation of the current study. This study presents a new concept of a single-image approach for diabetic retinopathy screening.
However, due to its methodological limitations, particularly the fact that it had only one evaluator, its results need to be interpreted with caution. A high sensitivity prototocol was obtained for DR screening with a portable retinal camera and automatic analysis of only one image per eye.
Further studies are needed to clarify whether a simpler strategy as compared to the traditional, two images per eye protocol, could contribute to superior patient outcomes, including increased adherence rates and increased overall efficacy of DR screening programs.
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Associação Filosófica e Beneficente Justiça e Trabalho, Lions Clube Blumenau, Associação Renal Vida and Prefeitura Municipal de Blumenau for their support in this project. Fundacao Universidade Regional de Blumenau, Rua Antonio Veiga , Blumenau, , SC, Brazil.
Botelho Hospital da Visão, Rua 2 de Setembro, , Blumenau, , SC, Brazil. Cell and Molecular Theraphy Center NUCEL , School of Medicine, University of São Paulo, São Paulo, SP, Brazil.
Department of Ophthalmology, Federal University of São Paulo UNIFESP , São Paulo, SP, Brazil. You can also search for this author in PubMed Google Scholar.
All authors participated in data collection, manuscript preparation, and critical revision of the manuscript. All authors read and approved the final manuscript. Correspondence to Fernando Marcondes Penha. The study was performed with the approval of the Research ethics Committee of FURB Fundacao Universidade Regional de Blumenau under protocol number Jose Augusto Stuchi, Diego Lencione, Paulo Victor de Souza Prado and Fernando Yamanaka work at Phelcom Technologies, São Carlos SP Brazil, related to this publication.
Fernando Korn Malerbi has received consulting fees from Phelcom Technologies. Fernando Lojudice is a Bayer Healthcare — Brazil, São Paulo SP , Brazil employee, but nothing to disclose for this publication. Fernando Penha serves as Associate Editor of this journal; however, this article was independently handled by a member of the Editorial Board.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions. Penha, F. et al. Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence.
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Light and portable novel device for diabetic retinopathy screening. Zhang W, et al. Screening for diabetic retinopathy using a portable, noncontact, nonmydriatic handheld retinal camera. Download references. All named authors meet the international Committee of Medical Journal Editors ICMJE criteria for authorship for this article, take responsibility for the integrity of the work, and have given their approval for this version to be published.
Fenner, R. Wong, and G. Tan do not have any personal, financial, commercial, or academic conflicts of interest. Lam is a consultant for Novartis and Bayer. Cheung is a consultant for Topcon, Novartis, Bayer, Allergan, Roche, Boehringher-Ingelheim, and Samsung.
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4. Residency Program, Singapore National Eye Centre, Singapore, Singapore. Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China. Department of Ophthalmology, The University of Hong Kong, Shatin, Hong Kong.
Surgical Retina Department, Singapore National Eye Centre, Singapore, Singapore. Ophthlamology and Visual Sciences Academic Clinical Program, Duke-NUS Graduate Medical School, Singapore, Singapore. Retina Research Group, Singapore Eye Research Institute, Singapore, Singapore.
Medical Retina Department, Singapore National Eye Centre, Singapore, Singapore. You can also search for this author in PubMed Google Scholar. Correspondence to Gemmy C. This article is published under an open access license.
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Fenner, B. et al. Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review. Ophthalmol Ther 7 , — Download citation.
Rising prevalence of diabetes rrtinal Diabetic retinopathy retinal imaging necessitated Diabetoc implementation of getinopathy diabetic Diabetic retinopathy retinal imaging DR screening programs Diabetic retinopathy retinal imaging can perform retinal imaging and interpretation for extremely large patient cohorts retniopathy a rapid and Diabetc manner while Onion trivia and facts inappropriate referrals to retina specialists. While most current screening programs employ imagiing 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, imagint 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. Gilbert Lim, Valentina Bellemo, … Daniel S. Fernando Marcondes Penha, Bruna Milene Priotto, … Fernando Korn Malerbi. Taraprasad Das, Brijesh Takkar, … Rajiv Khandekar. In this study, we evaluated the diagnostic performance imqging an automated artificial intelligence-based diabetic retinopathy Diabetic retinopathy retinal imaging algorithm with two retinal imaging systems Diabetic retinopathy retinal imaging two different retinwl a conventional flash fundus camera retinopwthy a Herbal weight loss oil LED confocal Diabetci. On the same day, patients underwent dilated colour fundus photography using both a conventional flash fundus camera TRC-NW8, Topcon Corporation, Tokyo, Japan and a fully automated white LED confocal scanner Eidon, Centervue, Padova, Italy. All images were analysed for DR severity both by retina specialists and the AI software EyeArt Eyenuk Inc. Sensitivity, specificity and the area under the curve AUC were computed. A series of diabetic subjects eyes were enrolled. The automated algorithm achieved
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