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Purpose: To determine the effect of combined macular spectral-domain optical coherence tomography (SD-OCT) and ultrawide field retinal imaging (UWFI) within a telemedicine program., Methods: Comparative cohort study of consecutive patients with both UWFI and SD-OCT. Ultrawide field retinal imaging and SD-OOCT were independently evaluated for diabetic macular edema (DME) and nondiabetic macular abnormality. Sensitivity and specificity were calculated with SD-OCT as the gold standard., Results: Four hundred twenty-two eyes from 211 diabetic patients were evaluated. Diabetic macular edema severity by UWFI was as follows: no DME 93.4%, noncenter involved DME (nonciDME) 5.1%, ciDME 0.7%, ungradable DME 0.7%. SD-OCT was ungradable in 0.5%. Macular abnormality was identified in 34 (8.1%) eyes by UWFI and in 44 (10.4%) eyes by SD-OCT. Diabetic macular edema represented only 38.6% of referable macular abnormality identified by SD-OCT imaging. Sensitivity/specificity of UWFI compared with SD-OCT was 59%/96% for DME and 33%/99% for ciDME. Sensitivity/specificity of UWFI compared with SDOCT was 3%/98% for epiretinal membrane., Conclusion: Addition of SD-OCT increased the identification of macular abnormality by 29.4%. More than 58.3% of the eyes believed to have any DME on UWF imaging alone were false-positives by SD-OCT. The integration of SD-OCT with UWFI markedly increased detection and reduced false-positive assessments of DME and macular abnormality in a teleophthalmology program.

Purpose: This study aims to compare artificial intelligence (AI) systems applied in diabetic retinopathy (DR) teleophthalmology screening, currently deployed systems, fairness initiatives and the challenges for implementation., Methods: The review included articles retrieved from PubMed/Medline/EMBASE literature search strategy regarding telemedicine, DR and AI. The screening criteria included human articles in English, Portuguese or Spanish and related to telemedicine and AI for DR screening. The author's affiliations and the study's population income group were classified according to the World Bank Country and Lending Groups., Results: The literature search yielded a total of 132 articles, and nine were included after full-text assessment. The selected articles were published between 2004 and 2020 and were grouped as telemedicine systems, algorithms, economic analysis and image quality assessment. Four telemedicine systems that perform a quality assessment, image preprocessing and pathological screening were reviewed. A data and post-deployment bias assessment are not performed in any of the algorithms, and none of the studies evaluate the social impact implementations. There is a lack of representativeness in the reviewed articles, with most authors and target populations from high-income countries and no low-income country representation., Conclusions: Telemedicine and AI hold great promise for augmenting decision-making in medical care, expanding patient access and enhancing cost-effectiveness. Economic studies and social science analysis are crucial to support the implementation of AI in teleophthalmology screening programs. Promoting fairness and generalizability in automated systems combined with telemedicine screening programs is not straightforward. Improving data representativeness, reducing biases and promoting equity in deployment and post-deployment studies are all critical steps in model development.

Purpose: Estimates of diabetic eye disease in American Indian and Alaska Natives (AI/AN) vary over time, region, and methods. This article reports recent prevalence of diabetic retinopathy (DR) and diabetic macular edema (DME) in AI/AN served by the Indian Health Services' (IHS) teleophthalmology program, as identified using ultrawide field imaging (UWFI)., Methods: This was a retrospective analysis of 2016-2019 clinical data (n = 53,900). UWF images were acquired by certified imagers using a validated protocol, and graded by licensed, certified optometrists supervised by an ophthalmologist. Graders evaluated the extent/severity of retinal lesions in comparison to standard photographs. DR lesions predominantly in any peripheral field were considered "predominantly peripheral lesions" (PPL). The analyses calculated prevalence of any DR, any DME, DR and DME severity, sight-threatening disease, and PPL., Results: Patients averaged 56 years of age with a 68 mmol/mol A1c and 55% had had diabetes for 5+ years. Prevalence of any DR, any DME, and sight-threatening disease was 28.6%, 3.0%, and 3.0%. In patients with mild nonproliferative DR, PPL was seen in 25.3%. PPL suggested a more severe level of DR in 8.7% of patients. DR increased with age. DME decreased with age. Males and patients in the Nashville IHS area had more diabetic eye disease., Conclusion: AI/AN have a high burden of diabetes and its complications. The IHS is resource-constrained, making accurate disease estimates necessary for resource allocation and budget justifications to Congress. These data update the estimates of diabetic eye disease in Indian Country and suggest that UWFI identifies early DR.

Importance: Methods that increase visible retinal area (VRA; measured in millimeters squared) may improve identification of diabetic retinopathy (DR) lesions., Objective: To evaluate the association of dilation and manual eyelid lifting (MLL) with VRA on ultra-widefield imaging (UWFI) and the association of VRA with grading of DR severity and detection of predominantly peripheral lesions (PPLs)., Design, Setting, and Participants: Retrospective, comparative case-control study at the Joslin Diabetes Center, Boston, Massachusetts. Nonmydriatic UWFI with MLL was acquired from a DR teleophthalmology program (Joslin Vision Network [JVN]). A second cohort of mydriatic UWFI was acquired at an academic retina practice (Beetham Eye Institute [BEI]) from November 6, 2017, to November 6, 2018, and with MLL thereafter until November 6, 2019. Fully automated algorithms determined VRA and hemorrhage and/or microaneurysm (HMA) counts. Predominantly peripheral lesions and HMAs were defined as present when at least 1 field had greater HMA number in the peripheral retina than within the corresponding Early Treatment Diabetic Retinopathy Study field. Participants included 3014 consecutive patients (5919 eyes) undergoing retinal imaging at JVN and BEI., Exposures: Dilation and MLL performed at the time of UWFI., Main Outcomes and Measures: Visible retinal area, DR severity, and presence of PPLs., Results: Of the 3014 participants, mean (SD) age was 56.1 (14.5) years, 1302 (43.2%) were female, 2450 (81.3%) were White, and mean (SD) diabetes duration was 15.9 (11.4) years. All images from 5919 eyes with UWFI were analyzed. Mean (SD) VRA was 665.1 (167.6) mm2 for all eyes (theoretical maximal VRA, 923.9 mm2), 550.8 (240.7) mm2 for nonmydriatic JVN with MLL (1418 eyes [24.0%]), 688.1 (119.9) mm2 for mydriatic BEI images (3650 eyes [61.7%]), and 757.0 (69.7) mm2 for mydriatic and MLL BEI images (851 eyes [14.4%]). Dilation increased VRA by 25% (P < .001) and MLL increased VRA an additional 10% (P < .001). Nonmydriatic MLL increased VRA by 11.0%. With MLL, HMA counts in UWFI fields increased by 41.7% (from 4.8 to 6.8; P < .001). Visible retinal area was moderately associated with increasing PPL-HMA overall and in each cohort (all, r = 0.33; BEI, r = 0.29; JVN, r = 0.36; P < .001). In JVN images, increasing VRA was associated with more PPL-HMA (quartile 1 [Q1], 23.7%; Q2, 45.8%; Q3, 60.6%; and Q4, 69.2%; P < .001)., Conclusions and Relevance: Using fully automated VRA and HMA detection algorithms, pupillary dilation and eyelid lifting were shown to substantially increase VRA and PLL-HMA detection. Given the importance of HMA and PPL for determining risk of DR progression, these findings emphasize the importance of maximizing VRA for optimal risk assessment in clinical trials and teleophthalmology programs.

The introduction of ultrawide field imaging has allowed the visualization of approximately 82% of the total retinal area compared to only 30% using 7-standard field Early Treatment Diabetic Retinopathy (ETDRS) photography. This substantially wider field of view, while useful in many retinal vascular diseases, is particularly important in diabetic retinopathy where eyes with predominantly peripheral lesions or PPL have been shown to have significantly greater progression rates compared to eyes without PPL. In telemedicine settings, ultrawide field imaging has substantially reduced image ungradable rates and increased rate of disease identification allowing care to be delivered more effectively. Furthermore, the use of ultrawide field fluorescein angiography allows the visualization of significantly more diabetic retinal lesions and allows more accurate quantification of total retinal nonperfusion, with potential implications in the management of diabetic retinopathy and diabetic macular edema. The focus of this paper is to review the current role of ultrawide field imaging in diabetic retinopathy and its possible future role in innovations for retinal image analysis such as artificial intelligence and vessel caliber measurements.

The emergence of diabetes as a global epidemic is accompanied by the rise in diabetes‑related retinal complications. Diabetic retinopathy, if left undetected and untreated, can lead to severe visual impairment and affect an individual's productivity and quality of life. Globally, diabetic retinopathy remains one of the leading causes of visual loss in the working‑age population. Teleophthalmology for diabetic retinopathy is an innovative means of retinal evaluation that allows identification of eyes at risk for visual loss, thereby preserving vision and decreasing the overall burden to the health care system. Numerous studies worldwide have found teleophthalmology to be a reliable and cost‑efficient alternative to traditional clinical examinations. It has reduced barriers to access to specialized eye care in both rural and urban communities. In teleophthalmology applications for diabetic retinopathy, it is critical that standardized protocols in image acquisition and evaluation are used to ensure low image ungradable rates and maintain the quality of images taken. Innovative imaging technology such as ultrawide field imaging has the potential to provide significant benefit with integration into teleophthalmology programs. Teleophthalmology programs for diabetic retinopathy rely on a comprehensive and multidisciplinary approach with partnerships across specialties and health care professionals to attain wider acceptability and allow evidence‑based eye care to reach a much broader population., (Copyright 2017 Asia-Pacific Academy of Ophthalmology.)

According to current projections, the number of Americans with diabetes mellitus will increase from 27.8 million in 2007 to 60.7 million in 2030. With the increasing gap between demand for eye care and supply of ophthalmologists and optometrists, and the non-uniform distribution of eye care providers in US counties, barriers to eye examinations will likely increase. Telemedicine assessment of diabetic retinal disease through remote retinal imaging and diagnosis has the potential to meet these growing demands. To establish evidence for a telemedicine program as an effective modality for diabetic retinopathy (DR) assessment, the interpretation of teleretinal images should compare favorably with Early Treatment Diabetic Retinopathy Study film or digital photographs. We review the current evidence on the critical features and characteristics of ocular telehealth programs for DR in the following categories: image gradability, mydriasis, sensitivity and specificity, cost-effectiveness, long-term effectiveness, patient comfort and satisfaction, and improvement of patient related outcomes.

Diabetic retinopathy is a leading cause of new-onset vision loss worldwide. Treatments supported by large clinical trials are effective in preserving vision, but many persons do not receive timely diagnosis and treatment of diabetic retinopathy, which is typically asymptomatic when most treatable. Telemedicine evaluation to identify diabetic retinopathy has the potential to improve access to care and improve outcomes, but incomplete implementation of published standards creates a risk to program utility and sustainability. In a prior article, we reviewed the literature regarding the impact of imaging device, number and size of retinal images, pupil dilation, type of image grader, and diagnostic accuracy on telemedicine assessment for diabetic retinopathy. This article reviews the literature regarding the impact of automated image grading, cost effectiveness, program standards, and quality assurance (QA) on telemedicine assessment of diabetic retinopathy. Telemedicine assessment of diabetic retinopathy has the potential to preserve vision, but greater attention to development and implementation of standards is needed to better realize its potential.

Diabetic retinopathy is a leading cause of new-onset vision loss worldwide. Treatments supported by large clinical trials are effective in preserving vision, but many persons do not receive timely diagnosis and treatment of diabetic retinopathy, which is typically asymptomatic when most treatable. Telemedicine evaluation to identify diabetic retinopathy has the potential to improve access to care, but there are no universal standards regarding camera choice or protocol for ocular telemedicine. We review the literature regarding the impact of imaging device, number and size of retinal images, pupil dilation, type of image grader, and diagnostic accuracy on telemedicine assessment for diabetic retinopathy. Telemedicine assessment of diabetic retinopathy has the potential to preserve vision, but further development of telemedicine specific technology and standardization of operations are needed to better realize its potential.

Objective: To evaluate the ability of trained nonphysician retinal imagers to perform diabetic retinopathy (DR) evaluation at the time of ultrawide field retinal (UWF) imaging in a teleophthalmology program., Research Design and Methods: Clinic patients with diabetes received Joslin Vision Network protocol retinal imaging as part of their standard medical care. Retinal imagers evaluated UWF images for referable DR at the time of image capture. Training of the imagers included 4 h of standardized didactic lectures and 12 h of guided image review. Real-time evaluations were compared with standard masked gradings performed at a centralized reading center., Results: A total of 3,978 eyes of 1,989 consecutive patients were imaged and evaluated. By reading center evaluation, 3,769 eyes (94.7%) were gradable for DR, 1,376 (36.5%) had DR, and 580 (15.3%) had referable DR. Compared with the reading center, real-time image evaluation had a sensitivity and specificity for identifying more than minimal DR of 0.95 (95% CI 0.94-0.97) and 0.84 (0.82-0.85), respectively, and 0.99 (0.97-1.00) and 0.76 (0.75-0.78), respectively, for detecting referable DR. Only three patients with referable DR were not identified by imager evaluation., Conclusions: Point-of-care evaluation of UWF images by nonphysician imagers following standardized acquisition and evaluation protocols within an established teleophthalmology program had good sensitivity and specificity for detection of DR and for identification of referable retinal disease. With immediate image evaluation, <0.1% of patients with referable DR would be missed, reading center image grading burden would be reduced by 60%, and patient feedback would be expedited., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

There will be an estimated 552 million persons with diabetes globally by the year 2030. Over half of these individuals will develop diabetic retinopathy, representing a nearly insurmountable burden for providing diabetes eye care. Telemedicine programmes have the capability to distribute quality eye care to virtually any location and address the lack of access to ophthalmic services. In most programmes, there is currently a heavy reliance on specially trained retinal image graders, a resource in short supply worldwide. These factors necessitate an image grading automation process to increase the speed of retinal image evaluation while maintaining accuracy and cost effectiveness. Several automatic retinal image analysis systems designed for use in telemedicine have recently become commercially available. Such systems have the potential to substantially improve the manner by which diabetes eye care is delivered by providing automated real-time evaluation to expedite diagnosis and referral if required. Furthermore, integration with electronic medical records may allow a more accurate prognostication for individual patients and may provide predictive modelling of medical risk factors based on broad population data.

OBJECTIVE To compare efficiency of nonmydriatic ultrawide field retinal imaging (UWFI) and nonmydriatic fundus photography (NMFP) in a diabetic retinopathy (DR) ocular telehealth program. RESEARCH DESIGN AND METHODS Patients in this retrospective, comparative cohort study underwent NMFP and UWFI between 1 November 2011 and 1 November 2012. Images were evaluated for DR and diabetic macular edema (DME) by certified graders using a standard protocol at a centralized reading center. Identification of DR, image evaluation time, and rate of ungradable eyes were compared. RESULTS NMFP and UWFI were performed in 1,633 and 2,170 consecutive patients, respectively. No statistically significant differences were found between groups regarding age, diabetes duration, sex, ethnicity, or insulin use. The ungradable rate per patient for DR (2.9 vs. 9.9%, P < 0.0001) and DME (3.8 vs. 8.8%, P < 0.0001) was lower with UWFI than with NMFP. With UWFI, the median image evaluation time per patient was reduced from 12.8 to 9.2 min (P < 0.0001). The identification of patients with DR (38.4 vs. 33.8%) and vision-threatening DR (14.5 vs. 11.9%) was increased with UWFI versus NMFP. In a consecutive subgroup of 502 eyes of 301 patients with DR, the distribution of peripheral retinal lesions outside Early Treatment Diabetic Retinopathy Study fields suggested a more severe DR level in 9.0% (45 eyes). CONCLUSIONS In a standardized DR ocular telehealth program, nonmydriatic UWFI reduced the ungradable rate by 71% (to <3%) and reduced image evaluation time by 28%. DR was identified 17% more frequently after UWFI, and DR peripheral lesions suggested a more severe DR level in 9%. These data suggest that UWFI may improve efficiency of ocular telehealth programs evaluating DR and DME.

Current projections estimate that diabetes mellitus will afflict over 439 million individuals worldwide by 2030. The task of detecting and evaluating for the presence and severity of retinopathy in the populations with diabetes mellitus is enormous. Although current methods of treatment are effective in reducing the risk for vision loss, a substantial proportion of patients still do not receive appropriate eye care. The use of an ocular telemedicine-based approach has the potential to expand the reach of these highly effective treatments to virtually any location. Novel methods of image acquisition and analysis, as well as the identification of predictive biomarkers, will need to be developed to further enhance this approach of eye care delivery. In addition, such programs will allow the rapid transfer of clinically relevant discoveries and will allow a considerably larger benefit to a broader patient population.

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes. The Joslin Vision Network Diabetes Eye Care Program (JVN) is a validated ocular telemedicine program developed at the Joslin Diabetes Center that has provided diabetes eye care to over 70,000 persons. The JVN allows accurate assessment of level of DR severity, detects the presence of nondiabetic eye disease, and allows determination of appropriate treatment recommendations. The JVN integrates eye care in a comprehensive diabetes program, extends access to evidence-based diabetes eye care, and offers alternative means of diabetes eye care in appropriate settings, ultimately preserving vision and preventing visual loss.

Diabetic retinopathy (DR) is a common complication of diabetes mellitus and a leading cause of new-onset vision loss in adults worldwide. Current medical and surgical evidence-based care, including laser photocoagulation, is effective in preserving vision. This care is most effective prior to the onset of ocular or visual symptoms, but many diabetic persons do not receive the recommended annual eye examination for the evaluation of the retina for level of DR. With diabetes incidence and prevalence increasing at epidemic rates and the prediction that 370 million people worldwide will have diabetes by the year 2030, human and fiscal resources will be unable to meet the visual needs with current acute care methods. Appropriate and validated telemedicine programs for DR hold the promise of both enrolling patients into appropriate eye care programs and, more importantly, providing more effective, high-quality diabetes eye care based on current and developing technology.