Screening for Diabetic Retinopathy Using a Portable, Noncontact, Nonmydriatic Handheld Retinal Camera

Effectiveness of Conventional Digital Fundus Photography-Based Teleretinal Screening for Diabetic Retinopathy and Diabetic Macular Edema: A Report by the American Academy of Ophthalmology

PURPOSE

This American Academy of Ophthalmology Ophthalmic Technology Assessment aims to assess the effectiveness of conventional teleretinal screening (TS) in detecting diabetic retinopathy (DR) and diabetic macular edema (DME).

METHODS

A literature search of the PubMed database was conducted most recently in July 2023 to identify data published between 2006 and 2023 on any of the following elements related to TS effectiveness: (1) the accuracy of TS in detecting DR or DME compared with traditional ophthalmic screening with dilated fundus examination or 7-standard field Early Treatment Diabetic Retinopathy Study photography, (2) the impact of TS on DR screening compliance rates or other patient behaviors, and (3) cost-effectiveness and patient satisfaction of TS compared with traditional DR screening. Identified studies then were rated based on the Oxford Centre for Evidence-Based Medicine grading system.

RESULTS

Eight level I studies, 14 level II studies, and 2 level III studies were identified in total. Although cross-study comparison is challenging because of differences in reference standards and grading methods, TS demonstrated acceptable sensitivity and good specificity in detecting DR; moderate to good agreement between TS and reference-standard DR grading was observed. Performance of TS was not as robust in detecting DME, although the number of studies evaluating DME specifically was limited. Two level I studies, 5 level II studies, and 1 level III study supported that TS had a positive impact on overall DR screening compliance, even increasing it by more than 2-fold in one study. Studies assessing cost-effectiveness and patient satisfaction were not graded formally, but they generally showed that TS was cost-effective and preferred by patients over traditional surveillance.

CONCLUSIONS

Conventional TS is an effective approach to DR screening not only for its accuracy in detecting referable-level disease, but also for improving screening compliance in a cost-effective manner that may be preferred by patients. Further research is needed to elucidate the ideal approach of TS that may involve integration of artificial intelligence or other imaging technologies in the future.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Clinical utility of handheld fundus and smartphone-based camera for monitoring diabetic retinal diseases: a review study

Diabetic retinopathy (DR) is the leading global cause of vision loss, accounting for 4.8% of global blindness cases as estimated by the World Health Organization (WHO). Fundus photography is crucial in ophthalmology as a diagnostic tool for capturing retinal images. However, resource and infrastructure constraints limit access to traditional tabletop fundus cameras in developing countries. Additionally, these conventional cameras are expensive, bulky, and not easily transportable. In contrast, the newer generation of handheld and smartphone-based fundus cameras offers portability, user-friendliness, and affordability. Despite their potential, there is a lack of comprehensive review studies examining the clinical utilities of these handheld (e.g. Zeiss Visuscout 100, Volk Pictor Plus, Volk Pictor Prestige, Remidio NMFOP, FC161) and smartphone-based (e.g. D-EYE, iExaminer, Peek Retina, Volk iNview, Volk Vistaview, oDocs visoScope, oDocs Nun, oDocs Nun IR) fundus cameras. This review study aims to evaluate the feasibility and practicality of these available handheld and smartphone-based cameras in medical settings, emphasizing their advantages over traditional tabletop fundus cameras. By highlighting various clinical settings and use scenarios, this review aims to fill this gap by evaluating the efficiency, feasibility, cost-effectiveness, and remote capabilities of handheld and smartphone fundus cameras, ultimately enhancing the accessibility of ophthalmic services.

Diagnostic Accuracy of Hand-Held Fundus Camera and Artificial Intelligence in Diabetic Retinopathy Screening

Our study aimed to assess the role of a hand-held fundus camera and artificial intelligence (AI)-based grading system in diabetic retinopathy (DR) screening and determine its diagnostic accuracy in detecting DR compared with clinical examination and a standard fundus camera. This cross-sectional instrument validation study, as a part of the International Diabetes Federation (IDF) Diabetic Retinopathy Screening Project, included 160 patients (320 eyes) with type 2 diabetes (T2DM). After the standard indirect slit-lamp fundoscopy, each patient first underwent fundus photography with a standard 45° camera VISUCAM Zeiss and then with a hand-held camera TANG (Shanghai Zhi Tang Health Technology Co., Ltd.). Two retina specialists independently graded the images taken with the standard camera, while the images taken with the hand-held camera were graded using the DeepDR system and an independent IDF ophthalmologist. The three screening methods did not differ in detecting moderate/severe nonproliferative and proliferative DR. The area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa (ĸ) agreement, diagnostic odds ratio, and diagnostic effectiveness for a hand-held camera compared to clinical examination were 0.921, 89.1%, 100%, 100%, 91.4%, infinity, 0.11, 0.86, 936.48, and 94.9%, while compared to the standard fundus camera were 0.883, 83.2%, 100%, 100%, 87.3%, infinity, 0.17, 0.78, 574.6, and 92.2%. The results of our study suggest that fundus photography with a hand-held camera and AI-based grading system is a short, simple, and accurate method for the screening and early detection of DR, comparable to clinical examination and fundus photography with a standard camera.

A Systematic Review of Digital Ophthalmoscopes in Medicine

Purpose

Recent advances in telemedicine have led to increased use of digital ophthalmoscopes (DO) in clinical settings. This review aims to assess commercially available DOs, including smartphone (SP), desktop, and handheld ophthalmoscopes, and evaluate their applications.

Methods

A literature review was performed by searching PubMed (pubmed.ncbi.nlm.nih.gov), Web of Science (webofknowledge.com), and Science Direct (sciencedirect.com). All English-language papers that resulted from the search terms "digital ophthalmoscope", "screening tool", "glaucoma screening", "diabetic retinopathy screening", "cataract screening", and "papilledema screening" were reviewed. Studies that contained randomized clinical trials with human participants between January 2010 and December 2020 were included. The Risk of Bias in Systematic Reviews (ROBIS) tool was used to assess the methodological quality of each included paper.

Results

Of the 1307 studies identified, 35 met inclusion and exclusion criteria. The ROBIS tool determined that 29/35 studies (82.8%) had a low risk of bias, 3/35 (8.5%) had a moderate risk of bias, and 3/35 (8.5%) had a high risk of bias.

Conclusion

The continued adoption of DOs remains uncertain because of concerns about the image quality for non-mydriatic eyes and the confidence in data captured from the device. Likewise, there is a lack of guidelines for the use of DOs, which makes it difficult for providers to determine the best device for their practice and to ensure appropriate use. Even so, DOs continue to gain acceptance as technology and practice integration improve, especially in underserved areas with limited access to ophthalmologists.

Diabetic Retinopathy Screening Using a Portable Retinal Camera in Vanuatu

Background and Objective

Proof-of-concept study to test the feasibility of using an all-in-one portable retinal camera for the screening of diabetic retinopathy in the Pacific Island of Vanuatu, which has a high rate of diabetes and its associated complications and a dearth of ophthalmologists.

Study Design/Materials and methods

From February 10, 2020, through February 28, 2020, 49 patients with diabetes mellitus from three islands in Vanuatu were recruited to participate in the study. Demographics, basic health data and retinal photography were obtained. A non-mydriatic, handheld camera was used (Volk Pictor Plus).

Results

Eleven participants (24%) had referral-warranted diabetic retinopathy. There was moderately high inter-rater reliability for our dependent variables: referral status (κ = 0.62, 95% CI 0.42-0.83), retinopathy severity (κ = 0.76, 95% CI 0.55-0.96), and clinically significant macular edema (κ = 0.50, 95% CI 0.25-0.74).

Conclusion

Our study confirms that portable handheld cameras can be used to obtain retinal images of sufficient quality for diabetic retinopathy screening even in resource limited environments like Vanuatu. Among this cohort, a relatively high (24%) prevalence of referral-warranted diabetic retinopathy was found in Vanuatu.

Hybrid spiral scanning in a double-clad fiber-based handheld confocal scanning light ophthalmoscope

High-speed, accessible, and robust in vivo imaging of the human retina is critical for screening of retinal pathologies, such as diabetic retinopathy, age-related macular degeneration, and others. Scanning light ophthalmoscopy (SLO) is a retinal imaging modality that produces digital, en face images of the human retina with superior image gradability rates when compared to the current standard of care in screening for these diseases, namely the flood-illumination handheld fundus camera (HFC). However, current-generation commercial SLO systems are mostly tabletop devices, limiting their accessibility and utility in screening applications. Moreover, most existing SLO systems use raster scan patterns, which are both inefficient and lead to undesired subject gaze drift when used with visible or pseudo-visible illumination. Non-raster scan patterns, especially spiral scanning as described herein, promise advantages in both scan efficiency and reduced subject eye motion. In this work, we introduce a novel "hybrid spiral" scan pattern and the associated hardware design and real-time image reconstruction techniques necessary for its implementation in an SLO system. Building upon this core hybrid spiral scanning SLO (HSS-SLO) technology, we go on to present a complete handheld HSS-SLO system, featuring a fiber-coupled portable patient interface which leverages a dual-clad fiber (DCF) to form a single-path optical topology, thus ensuring mechanically robust co-alignment of illumination and collection apertures, a necessity for a handheld system. The feasibility of HSS-SLO for handheld, in vivo imaging is demonstrated by imaging eight human volunteers.

Health system adaptions to improve care for people living with non-communicable diseases during COVID-19 in low-middle income countries: A scoping review

Background

During the COVID-19 pandemic, access to health care for people living with non-communicable diseases (NCDs) has been significantly disrupted. Calls have been made to adapt health systems and innovate service delivery models to improve access to care. We identified and summarized the health systems adaptions and interventions implemented to improve NCD care and their potential impact on low- and middle-income countries (LMICs).

Methods

We comprehensively searched Medline/PubMed, Embase, CINAHL, Global Health, PsycINFO, Global Literature on coronavirus disease, and Web of Science for relevant literature published between January 2020 and December 2021. While we targeted articles written in English, we also included papers published in French with abstracts written in English.

Results

After screening 1313 records, we included 14 papers from six countries. We identified four unique health systems adaptations/interventions for restoring, maintaining, and ensuring continuity of care for people living with NCDs: telemedicine or teleconsultation strategies, NCD medicine drop-off points, decentralization of hypertension follow-up services and provision of free medication to peripheral health centers, and diabetic retinopathy screening with a handheld smartphone-based retinal camera. We found that the adaptations/interventions enhanced continuity of NCD care during the pandemic and helped bring health care closer to patients using technology and easing access to medicines and routine visits. Telephonic aftercare services appear to have saved a significant amount of patients' time and funds. Hypertensive patients recorded better blood pressure controls over the follow-up period.

Conclusions

Although the identified measures and interventions for adapting health systems resulted in potential improvements in access to NCD care and better clinical outcomes, further exploration is needed to establish the feasibility of these adaptations/interventions in different settings given the importance of context in their successful implementation. Insights from such implementation studies are critical for ongoing health systems strengthening efforts to mitigate the impact of COVID-19 and future global health security threats for people living with NCDs.

Evaluation of a New Neural Network Classifier for Diabetic Retinopathy

BACKGROUND

Medical image segmentation is a well-studied subject within the field of image processing. The goal of this research is to create an AI retinal screening grading system that is both accurate and fast. We introduce a new segmentation network which achieves state-of-the-art results on semantic segmentation of color fundus photographs. By applying the net-work to identify anatomical markers of diabetic retinopathy (DR) and diabetic macular edema (DME), we collect sufficient information to classify patients by grades R0 and R1 or above, M0 and M1.

METHODS

The AI grading system was trained on screening data to evaluate the presence of DR and DME. The core algorithm of the system is a deep learning network that segments relevant anatomical features in a retinal image. Patients were graded according to the standard NHS Diabetic Eye Screening Program feature-based grading protocol.

RESULTS

The algorithm performance was evaluated with a series of 6,981 patient retinal images from routine diabetic eye screenings. It correctly predicted 98.9% of retinopathy events and 95.5% of maculopathy events. Non-disease events prediction rate was 68.6% for retinopathy and 81.2% for maculopathy.

CONCLUSION

This novel deep learning model was trained and tested on patient data from annual diabetic retinopathy screenings can classify with high accuracy the DR and DME status of a person with diabetes. The system can be easily reconfigured according to any grading protocol, without running a long AI training procedure. The incorporation of the AI grading system can increase the graders' productivity and improve the final outcome accuracy of the screening process.

Diabetic retinopathy screening in the emerging era of artificial intelligence

Diabetic retinopathy is a frequent complication in diabetes and a leading cause of visual impairment. Regular eye screening is imperative to detect sight-threatening stages of diabetic retinopathy such as proliferative diabetic retinopathy and diabetic macular oedema in order to treat these before irreversible visual loss occurs. Screening is cost-effective and has been implemented in various countries in Europe and elsewhere. Along with optimised diabetes care, this has substantially reduced the risk of visual loss. Nevertheless, the growing number of patients with diabetes poses an increasing burden on healthcare systems and automated solutions are needed to alleviate the task of screening and improve diagnostic accuracy. Deep learning by convolutional neural networks is an optimised branch of artificial intelligence that is particularly well suited to automated image analysis. Pivotal studies have demonstrated high sensitivity and specificity for classifying advanced stages of diabetic retinopathy and identifying diabetic macular oedema in optical coherence tomography scans. Based on this, different algorithms have obtained regulatory approval for clinical use and have recently been implemented to some extent in a few countries. Handheld mobile devices are another promising option for self-monitoring, but so far they have not demonstrated comparable image quality to that of fundus photography using non-portable retinal cameras, which is the gold standard for diabetic retinopathy screening. Such technology has the potential to be integrated in telemedicine-based screening programmes, enabling self-captured retinal images to be transferred virtually to reading centres for analysis and planning of further steps. While emerging technologies have shown a lot of promise, clinical implementation has been sparse. Legal obstacles and difficulties in software integration may partly explain this, but it may also indicate that existing algorithms may not necessarily integrate well with national screening initiatives, which often differ substantially between countries.

Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema

PURPOSE

To compare nonmydriatic (NM) and mydriatic (MD) handheld retinal imaging with standard ETDRS 7-field color fundus photography (ETDRS photographs) for the assessment of diabetic retinopathy (DR) and diabetic macular edema (DME).

DESIGN

Prospective, comparative, instrument validation study.

SUBJECTS

A total of 225 eyes from 116 patients with diabetes mellitus.

METHODS

Following a standardized protocol, NM and MD images were acquired using handheld retinal cameras (NM images: Aurora, Smartscope, and RetinaVue-700; MD images: Aurora, Smartscope, RetinaVue-700, and iNview) and dilated ETDRS photographs. Grading was performed at a centralized reading center using the International Clinical Classification for DR and DME. Kappa statistics (simple [K], weighted [Kw]) assessed the level of agreement for DR and DME. Sensitivity and specificity were calculated for any DR, referable DR (refDR), and vision-threatening DR (vtDR).

MAIN OUTCOME MEASURES

Agreement for DR and DME; sensitivity and specificity for any DR, refDR, and vtDR; ungradable rates.

RESULTS

Severity by ETDRS photographs: no DR, 33.3%; mild nonproliferative DR, 20.4%; moderate DR, 14.2%; severe DR, 11.6%; proliferative DR, 20.4%; no DME, 68.0%; DME, 9.3%; non-center involving clinically significant DME, 4.9%; center-involving clinically significant DME, 12.4%; and ungradable, 5.3%. For NM handheld retinal imaging, Kw was 0.70 to 0.73 for DR and 0.76 to 0.83 for DME. For MD handheld retinal imaging, Kw was 0.68 to 0.75 for DR and 0.77 to 0.91 for DME. Thresholds for sensitivity (0.80) and specificity (0.95) were met by NM images acquired using Smartscope and MD images acquired using Aurora and RetinaVue-700 cameras for any DR and by MD images acquired using Aurora and RetinaVue-700 cameras for refDR. Thresholds for sensitivity and specificity were met by MD images acquired using Aurora and RetinaVue-700 for DME. Nonmydriatic and MD ungradable rates for DR were 15.1% to 38.3% and 0% to 33.8%, respectively.

CONCLUSIONS

Following standardized protocols, NM and MD handheld retinal imaging devices have substantial agreement levels for DR and DME. With mydriasis, not all handheld retinal imaging devices meet standards for sensitivity and specificity in identifying any DR and refDR. None of the handheld devices met the established 95% specificity for vtDR, suggesting that lower referral thresholds should be used if handheld devices must be utilized. When using handheld devices, the ungradable rate is significantly reduced with mydriasis and DME sensitivity thresholds are only achieved following dilation.

Optics and Utility of Low-Cost Smartphone-Based Portable Digital Fundus Camera System for Screening of Retinal Diseases

Purpose: To describe optical principles and utility of inexpensive, portable, non-contact digital smartphone-based camera for the acquisition of fundus photographs for the evaluation of retinal disorders. Methods: The digital camera has a high-quality glass 25 D condensing lens attached to a 21.4-megapixel smartphone camera. The white-emitting LED light of the smartphone at low illumination levels is used to visualize the fundus and limit source reflection. The camera captures a high-definition fundus (5344 × 4016) image on a complementary metal oxide semiconductor (CMO) with an area of 6.3 mm × 4.5 mm. The auto-acquisition mode of the device facilitates the quick capture of the image from continuous video streaming in a fraction of a second. Results: This new smartphone-based camera provides high-resolution digital images of the retina (50° telescopic view) in patients at a fraction of the cost (USD 1000) of established, non-transportable, office-based fundus photography systems. Conclusions: The portable user-friendly smartphone-based digital camera is a useful alternative for the acquisition of fundus photographs and provides a tool for screening retinal diseases in various clinical settings such as primary care clinics or emergency rooms. The ease of acquisition of photographs from a continuously streaming video of fundus obviates the need for a skilled photographer.

Handheld Fundus Camera for Diabetic Retinopathy Screening: A Comparison Study with Table-Top Fundus Camera in Real-Life Setting

The aim of the study was to validate the performance of the Optomed Aurora^® handheld fundus camera in diabetic retinopathy (DR) screening. Patients who were affected by diabetes mellitus and referred to the local DR screening service underwent fundus photography using a standard table-top fundus camera and the Optomed Aurora^® handheld fundus camera. All photos were taken by a single, previously unexperienced operator. Among 423 enrolled eyes, we found a prevalence of 3.55% and 3.31% referable cases with the Aurora^® and with the standard table-top fundus camera, respectively. The Aurora^® obtained a sensitivity of 96.9% and a specificity of 94.8% in recognizing the presence of any degree of DR, a sensitivity of 100% and a specificity of 99.8% for any degree of diabetic maculopathy (DM) and a sensitivity of 100% and specificity of 99.8% for referable cases. The overall concordance coefficient k (95% CI) was 0.889 (0.828–0.949) and 0.831 (0.658–1.004) with linear weighting for DR and DM, respectively. The presence of hypertensive retinopathy (HR) was recognized by the Aurora^® with a sensitivity and specificity of 100%. The Optomed Aurora^® handheld fundus camera proved to be effective in recognizing referable cases in a real-life DR screening setting. It showed comparable results to a standard table-top fundus camera in DR, DM and HR detection and grading. The Aurora^® can be integrated into telemedicine solutions and artificial intelligence services which, in addition to its portability and ease of use, make it particularly suitable for DR screening.

Sensitivity and Specificity of Handheld Fundus Cameras for Eye Disease: A Systematic Review and Pooled Analysis

In order to evaluate the accuracy of commercially available handheld fundus cameras for a variety of ophthalmic diagnoses, we conducted a systematic review, searching PubMed and PubMed Central and performing a bivariate analysis to determine the pooled sensitivity and specificity of handheld fundus cameras. Eleven studies validating handheld fundus cameras against a gold-standard method for disease diagnosis were included. For non-mydriatic images, pooled sensitivity was 83% (95% CI: 77-88%) and specificity was 92% (95% CI: 79-97%). For mydriatic images, pooled sensitivity was 87% (95% CI: 79-92%) and specificity was 90% (95% CI: 78-96%). Overall pooled sensitivity was 85% (95% CI: 80-89%) and specificity was 91% (95% CI: 83-95%). Of the 11 studies included, 5 assessed the diagnosis of diabetic retinopathy, for which sensitivity was 87% (95% CI: 80-92%) and specificity was 95% (95% CI: 85-98%). For all other diagnoses combined, sensitivity was 81% (95% CI: 74-87%) and specificity was 83% (95% CI: 76-89%). These findings suggest that handheld fundus cameras are capable of achieving acceptable sensitivity and specificity values for eye disease, with mydriatic images being more sensitive for disease. Diabetic retinopathy was the single diagnosis with the strongest data to support the use of handheld fundus cameras for disease screening.

Development of 3D Printed Smartphone-Based Multi-Purpose Fundus Camera (MultiScope) for Retinopathy of Prematurity

Retinopathy of Prematurity (ROP) is a prominent source of low vision and blindness in preterm babies. Wide-Field Digital Retinal Imaging (WFDRI) systems acquire accurate digital images which are very useful for identification, documentation and transmitting the various retinal diseases. This telemedicine technique has potential for an alternative tool for Binocular Indirect Ophthalmoscopy (BIO) in ROP screening, but it is very expensive and accessibility for poor communities is limited. Capabilities of good illumination, high resolution camera and processing speed of the modern smartphones are being identified as a substitute. Potential applications of 3D printing is that it provides a severe impact in medical field, especially in ophthalmology sector. Competences of 3D printing are very useful for the development of retinal camera from any smartphone with the help of 3D printable devices. The primary aim of this study is to develop a handheld 3D printed smartphone-based multi-purpose fundus camera for ROP screening. The secondary aim is to check the feasibility and compare the digital fundus images obtained from the developed fundus camera against the commercial RetCam imaging. The proposed cost effective and remote reading device is an alternative to WFDRI for ROP screening and can improve the potential of ROP care for low resource communities.

The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy

In the presence of the ever-increasing incidence of diabetes mellitus (DM), the prevalence of diabetic eye disease (DED) is also growing. Despite many improvements in diabetic care, DM remains a leading cause of visual impairment in working-age patients. So far, prevention has been the best way to protect vision. The sooner we diagnose DED, the more effective the treatment is. Thus, diabetic retinopathy (DR) screening, especially with imaging techniques, is a method of choice for vision protection. To alleviate the burden of diabetic patients who need ophthalmic care, telemedicine and in-home testing are used, supported by artificial intelligence (AI) algorithms. This is why we decided to evaluate current image teleophthalmology methods used for DR screening. We searched the PubMed platform for papers published over the last 5 years (2015–2020) using the following key words: telemedicine in diabetic retinopathy screening, diabetic retinopathy screening, automated diabetic retinopathy screening, artificial intelligence in diabetic retinopathy screening, smartphone diabetic retinopathy testing. We have included 118 original articles meeting the above criteria, discussing imaging diabetic retinopathy screening methods. We have found that fundus cameras, stable or mobile, are most commonly used for retinal photography, with portable fundus cameras also relatively common. Other possibilities involve the use of ultra-wide-field (UWF) imaging and even optical coherence tomography (OCT) devices for DR screening. Also, the role of smartphones is increasingly recognized in the field. Retinal fundus images are assessed by humans instantly or remotely, while AI algorithms seem to be useful tools facilitating retinal image assessment. The common use of smartphones and availability of relatively cheap, easy-to-use adapters for retinal photographs augmented by AI algorithms make it possible for eye fundus photographs to be taken by non-specialists and in non-medical setting. This opens the way for in-home testing conducted on a much larger scale in the future. In conclusion, based on current DR screening techniques, we can suggest that the future practice of eye care specialists will be widely supported by AI algorithms, and this way will be more effective.

Perceived usefulness and ease of use of fundoscopy by medical students: a randomised crossover trial of six technologies (eFOCUS 1)

BACKGROUND

Fundoscopy outside ophthalmology is in decline, and the technical demands of the traditional direct ophthalmoscope examination are likely contributing. Alternative fundoscopy technologies are increasingly available, yet valid comparisons between fundoscopy technologies are lacking. We aimed to assess medical students' perceptions of usefulness and ease of use of traditional and contemporary fundus-viewing technologies including smartphone fundoscopy.

METHODS

One hundred forty-six second-year medical students participated in a cross-sectional, randomised, cross-over study of fundoscopy methods. Medical students completed small group training sessions using six current fundoscopy technologies including: a non-mydriatic fundus camera; two types of direct fundoscopy; and three types of smartphone fundoscopy. A novel survey of perceived usefulness and ease of use was then completed by students.

RESULTS

Repeated-measures ANOVA found students rated both the perceived usefulness (p< 0.001) and ease of use (p< 0.001) of smartphone fundoscopy significantly higher than both the non-mydriatic camera and direct fundoscopy.

CONCLUSIONS

Smartphone fundoscopy was found to be significantly more useful and easier to use than other modalities. Educators should optimise student access to novel fundoscopy technologies such as smartphone fundoscopy which may mitigate the technical challenges of fundoscopy and reinvigorate use of this valuable clinical examination.

Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy

Purpose:

To evaluate the sensitivity and specificity of smartphone-based nonmydriatic (NM) retinal camera in the detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) in a tertiary eye care facility.

Methods:

Patients with diabetes underwent retinal photography with a smartphone-based NM fundus camera before mydriasis and standard 7-field fundus photography with a desktop mydriatic fundus camera after mydriasis. DR was graded using the international clinical classification of diabetic retinopathy system by two retinal expert ophthalmologists masked to each other and to the patient's identity. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to detect DR and STDR by NM retinal imaging were assessed.

Results:

245 people had gradable images in one or both eyes. DR and STDR were detected in 45.3% and 24.5%, respectively using NM camera, and in 57.6% and 28.6%, respectively using mydriatic camera. The sensitivity and specificity to detect any DR by NM camera was 75.2% (95% confidence interval (CI) 68.1–82.3) and 95.2% (95%CI 91.1–99.3). For STDR the values were 82.9% (95% CI 74.0–91.7) and 98.9% (95% CI 97.3–100), respectively. The PPV to detect any DR was 95.5% (95% CI 89.8–98.5) and NPV was 73.9% (95% CI 66.4–81.3); PPV for STDR detection was 96.7% (95% CI 92.1–100)) and NPV was 93.5% (95% CI 90.0–97.1).

Conclusion:

Smartphone-based NM retinal camera had fairly high sensitivity and specificity for detection of DR and STDR in this clinic-based study. Further studies are warranted in other settings.

The Utility of Routine Fundus Photography Screening for Posterior Segment Disease: A Stepped-wedge, Cluster-randomized Trial in South India

PURPOSE

To assess whether routine fundus photography (RFP) to screen for posterior segment disease at community eye clinics (vision centers [VCs]) in India increases referral to centralized ophthalmolic care.

DESIGN

Stepped-wedge, cluster-randomized trial.

PARTICIPANTS

Patients aged 40 to 75 years and those aged 20 to 40 years with a known history of hypertension or diabetes mellitus presenting to 4 technician-run VCs associated with the Aravind Eye Care System in India.

METHODS

VCs (clusters) were randomized to standard care or RFP across five 2-week study periods (steps). Patients in each cluster received standard care initially. At the start of each subsequent step, a randomly chosen cluster crossed over to providing RFP to eligible patients. All clusters took part in RFP during the last step. Standard care involved technician eye exams, optional fundus photography, and teleconsultation with an ophthalmologist. RFP involved eye exams, dilation and 40-degree fundus photography, and teleconsultation with an ophthalmologist.

MAIN OUTCOME MEASURES

Standard care and RFP clusters were compared by the proportion of patients referred for in-person evaluation by an ophthalmologist because of fundus photography findings and urgency of referral (urgently in ≤ 2 weeks vs. nonurgently in > 2 weeks). Generalized linear mixed models adjusting for cluster and step were used to estimate the odds of referral due to fundus photography findings compared with standard care.

RESULTS

A total of 1447 patients were enrolled across the VCs, including 737 in the standard care group and 710 in the RFP group. Compared with standard care, the RFP group had a higher proportion of referrals due to fundus photography findings (11.3% vs. 4.4%), nonurgent referrals due to fundus photography (9.3% vs. 3.3%), and urgent referrals due to fundus photography (1.8% vs. 1.1%). The RFP intervention was associated with a 2-fold increased odds of being referred because of photography findings compared with standard care (odds ratio, 2.07; 95% confidence interval, 0.98-4.40; P = 0.058).

CONCLUSIONS

Adding RFP to community eye clinics was associated with an increased odds of referral compared with standard care. This increase in referral was mostly due to nonurgent posterior segment disease.

Review of retinal cameras for global coverage of diabetic retinopathy screening

The global burden of diabetes has resulted in an increase in the prevalence of diabetic retinopathy (DR), a microvascular complication of diabetes. Lifelong repetitive screening for DR is essential for early detection and timely management to prevent visual impairment due to the silent sight-threatening disorder. Colour fundus photography (CFP) is helpful for documentation of the retinopathy as well as for counselling the patient. CFP has established roles in DR screening, detection, progression and monitoring of treatment response. DR screening programmes use validated mydriatic or non-mydriatic fundus cameras for retinal imaging and trained image graders identify referable DR. Smartphone-based fundus cameras and handheld fundus cameras that are cost-effective, portable and easy to handle in remote places are gaining popularity in recent years. The images captured with these low-cost devices can be immediately sent to trained ophthalmologists for grading of DR. Recent increase in numbers of telemedicine programmes based on imaging with digital fundus cameras and remote interpretation has facilitated larger population coverage of DR screening and timely referral of those with sight-threatening DR to ophthalmologists. Good-quality retinal imaging and accurate diagnosis are essential to reduce inappropriate referrals. Advances in digital imaging such as ultra-wide field imaging and multi-modal imaging have opened new avenues for assessing DR. Fundus cameras with integrated artificial intelligence (AI)-based automated algorithms can also provide instant DR diagnosis and reduce the burden of healthcare systems. We review the different types of fundus cameras currently used in DR screening and management around the world.

Validation of mobile-based funduscope for diabetic retinopathy screening in Estonia

AIM

To validate mobile-based funduscope for diabetic retinopathy screening in Estonia.

METHODS

Quality validation comparison of HEINE^® iC2 funduscope and Zeiss Visucam camera with image scoring and diagnostic test accuracy measurement by sensitivity and specificity. Study took place from January 2020 until March 2020 in East-Tallinn Central Hospital's eye clinic.

RESULTS

Based on 90 patients, the Zeiss Visucam showed 35.6% DR prevalence while iC2 had 18.9% for images and 17.8% for videos. The average Likert score was 4.7 for Zeiss Visucam and 2.4 for both iC2 images and iC2 videos. The sensitivity of iC2 images was 72.7% (95%CI 49.6-88.4) for grader 1 and 61.9% (95%CI 38.7-81.0) for grader 2, iC2 video sensitivity was 57.1% (95%CI 37.4-75.0) and 65.4% (95%CI 44.4-82.1), respectively. The grader-based specificity for iC2 images was 96.7% (95%CI 80.9-99.8) and 93.5% (95%CI 77.2-98.9). iC2 videos had a 100% (95%CI 91.7-1.0; 92.0-1.0) specificity by both graders. Cohen's kappa agreement was 0.82 and 0.96 for images and videos.

CONCLUSION

Mobile-based funduscope iC2 is not valid for DR screening with non-dilated pupils and thus not suitable for clinics that do not have experienced specialist present. Moreover, the screening specialist needs to be experienced fundus photographer with extra multiple day training for funduscope use. As main resolution, mobile-based funduscope was not validated for DR screening in Estonia based on pre-set study criteria. Additional research and development of funduscope algorithm for image stripping from videos is needed for validation as iC2 benefits do not offset the gold standard at the moment.

A Review of Advancements and Evidence Gaps in Diabetic Retinopathy Screening Models

Diabetic retinopathy (DR) is a microvascular complication of diabetes with a prevalence of ~35%, and is one of the leading causes of visual impairment in people of working age in most developed countries. The earliest stage of DR, non-proliferative DR (NPDR), may progress to sight-threatening DR (STDR). Thus, early detection of DR and active regular screening of patients with diabetes are necessary for earlier intervention to prevent sight loss. While some countries offer systematic DR screening, most nations are reliant on opportunistic screening or do not offer any screening owing to limited healthcare resources and infrastructure. Currently, retinal imaging approaches for DR screening include those with and without mydriasis, imaging in single or multiple fields, and the use of conventional or ultra-wide-field imaging. Advances in telescreening and automated detection facilitate screening in previously hard-to-reach communities. Despite the heterogeneity in approaches to fit local needs, an evidence base must be created for each model to inform practice. In this review, we appraise different aspects of DR screening, including technological advances, identify evidence gaps, and propose several studies to improve DR screening globally, with a view to identifying patients with moderate-to-severe NPDR who would benefit if a convenient treatment option to delay progression to STDR became available.

Detecting Common Eye Diseases Using the First Teleophthalmology GlobeChek Kiosk in the United States: A Pilot Study

PURPOSE

The aim of this study was to assess the benefit and feasibility of the teleophthalmology GlobeChek kiosk in a community-based program.

DESIGN

Single-site, nonrandomized, cross-sectional, teleophthalmologic study.

METHODS

Participants underwent comprehensive evaluation that consists of a questionnaire form, brief systemic evaluation, screening visual field (VF), and GlobeChek kiosk screening, which included but not limited to intraocular pressure, pachymetry, anterior segment optical coherence tomography, posterior segment optical coherence tomography, and nonmydriatic fundus photography. The results were evaluated by a store-and-forward mechanism and follow-up questionnaires were obtained through phone calls.

RESULTS

A total of 326 participatents were screened over 4 months. One hundred thirty-three (40.79%) participants had 1 condition in either eye, and 47 (14.41%) had >1 disease. Seventy (21.47%) had glaucoma, 37 (11.34%) narrow-angles, 6 (1.84%) diabetic retinopathy, 4 (1.22%) macular degeneration, and 43 (13.10%) had other eye disease findings. Age >65, history of high blood pressure, diabetes mellitus, not having a dental examination >5 years, hemoglobn A1c measurement of ≥5.6, predibates risk score of ≥9, stage 2 hypertension, and low blood pressure were found to be significant risk factors. As for the ocular parameters, all but central corneal thickness, including an intraocular pressure >21 mm Hg, vertical cup to disc ratio >0.7, visual field abnormalities, and retinal nerve fiber layer thinning were found to be significant.

CONCLUSIONS

GlobeChek kiosk is both workable and effective in increasing access to care and identifying the most common causes of blindness and their risk factors.

Telemedicine for Diabetic Retinopathy Screening in an Urban, Insured Population Using Fundus Cameras in a Primary Care Office Setting

BACKGROUND AND OBJECTIVE

This study examines the rate of adherence to recommended ophthalmology follow-up after primary care-based telemedicine diabetic retinopathy (DR) screening.

PATIENTS AND METHODS

Retrospective observational study of 5,764 insured diabetic patients undergoing telemedicine DR screening between May 2015 and April 2017 in an urban primary care setting. Patients underwent non-mydriatic fundus photography for telemedicine DR screening. The main outcome measure was the "capture rate."

RESULTS

Of the patients studied, 31.7% were found to have any retinal pathology, and 20% were found to have DR. In the 11.8% percent of patients with sight-threatening retinopathy who were recommended to have a retinal examination, the capture rate was 81.9%.

CONCLUSION

The authors' study demonstrated higher capture rate than has been previously reported, indicating that telemedicine DR screening in an urban, insured population may be a useful method for triaging high-risk patients without losing patients to follow-up. [Ophthalmic Surg Lasers Imaging Retina. 2019;50: e274-e277.].

Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic

Background

The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting.

Methods

This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM) > 18 years of age, not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation, using a hand-held non-mydriatic (Visuscout 100®-Germany) digital retinal camera. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician’s grading with a retinologist’s clinical examination by mydriatic bio-microscopy, according to a locally adopted guideline.

Results

Seven hundred eligible PwDM were screened by physician graders. The mean age of participants was 60.8 years (SD ±10.08) and mean duration of DM was 9.9 years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7–93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4–96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6–96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3–97.3%) for grader 2 (NPV 99.4%).

Conclusions

The Physicians grading of images from a digital hand-held non-mydriatic camera at a medical clinic, with dilatation of pupil of those who have ungradable images, provides a valid modality to identify referable level of DR. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

Trial registration

Current Controlled Trials ISRCTN47559703. Date of Registration 18th March 2019, Retrospectively registered.

Electronic supplementary material

The online version of this article (10.1186/s12886-019-1092-3) contains supplementary material, which is available to authorized users.

Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review

Rising prevalence of diabetes worldwide has necessitated the implementation of population-based diabetic retinopathy (DR) screening programs that can perform retinal imaging and interpretation for extremely large patient cohorts in a rapid and sensitive manner while minimizing inappropriate referrals to retina specialists. While most current screening programs employ mydriatic 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, macular 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.

Accuracy and Reliability of a Handheld, Nonmydriatic Fundus Camera for the Remote Detection of Optic Disc Edema

BACKGROUND

Optic disc edema can be an important indicator of serious neurological disease, but is poorly detected using the direct ophthalmoscope. Portable fundus photography may overcome this difficulty.

INTRODUCTION

The purpose of this study was to determine the sensitivity and specificity of a handheld, nonmydriatic fundus camera for the detection of optic disc edema.

MATERIALS AND METHODS

Retrospective review of nonmydriatic optic disc photographs taken with a portable fundus camera (Pictor Plus; Volk Optical, Mentor, OH) from the University of Michigan Neuro-Ophthalmology Clinics. We included 103 consecutive eyes with optic disc edema and 103 consecutive eyes without optic disc edema of 109 patients. Four masked neuro-ophthalmologists graded a single photograph of each optic disc presented in randomized order and documented the presence of optic disc edema. Sensitivity and specificity of graders' photographic interpretation was compared with clinical examinations. Reliability of assessments within and between graders was determined using kappa statistics.

RESULTS

The sensitivity and specificity for detection of optic disc edema were 71.8-92.2% and 81.6-95.2%, respectively. Photos were found to be ungradable in 0-8.3% of cases. The intergrader reliabilities ranged from 0.60 [95% confidence interval (CI): 0.52-0.67] to 0.72 (95% CI: 0.66-0.77). Intragrader reliability ranged from 0.76 (95% CI: 0.63-0.92) to 0.82 (95% CI: 0.69-0.95).

DISCUSSION

Photographs taken with portable, nonmydriatic technology met threshold sensitivity and specificity for remote screening for optic disc edema when performed by most, but not all graders. Reliability between graders was moderate-strong and strong within individual providers.

CONCLUSIONS

Portable photography holds promise for use in remote screening of optic disc edema.

Diabetic Eye Screening: Knowledge and Perspectives from Providers and Patients

PURPOSE OF REVIEW

Diabetic retinopathy remains the leading cause of blindness among working-age US adults even though timely screening and treatment prevent 90% of blindness. We summarize current knowledge and perspectives to better understand why diabetic eye screening rates remain low and future directions towards preventing blindness from diabetes.

RECENT FINDINGS

Significant advancements in the past 10 years include primary care and patient-oriented interventions as well as the use of teleophthalmology. In England, diabetic eye disease is no longer the leading cause of certifiable blindness following the implementation of a national teleophthalmology program for diabetic retinopathy. Multiple workflow and systems-level barriers affect providers. Patient barriers include a limited understanding of screening and lack of access to care. Interventions have been developed, but new barriers exist towards sustaining their impact. More research is needed to identify and implement the best practices to increase diabetic eye screening rates long-term.

CTRP3 is a novel biomarker for diabetic retinopathy and inhibits HGHL-induced VCAM-1 expression in an AMPK-dependent manner

Objectives

Diabetic retinopathy (DR) is a severe complication of chronic diabetes. The C1q/TNF-related protein family (CTRPs) has been demonstrated to exert protective effects against obesity and atherosclerosis in animal studies. Heretofore, the association between circulating CTRPs and DR patients has been unexplored. In the current study, we attempt to define this association, as well as the effect of CTRPs upon DR pathophysiology.

Design

The present investigation is a case control study that enrolled control subjects and type 2 diabetes mellitus (T2DM) patients diagnosed with DR. Serum CTRPs and sVACM-1 were determined by ELISA.

Results

Serum CTRP3 and CTRP5 levels were markedly decreased in patients with T2DM compared to controls (p<0.05) and inversely associated with T2DM. Furthermore, mutivariate regression and ROC analysis revealed CTRP3 deficiency, not CTRP5, was associated with proliferative diabetic retinopathy (PDR). Spearman’s rank correlation assay demonstrated an inverse association between CTRP3 and sVCAM-1. Finally, exogenous CTRP3 administration attenuated high glucose high lipid (HGHL)-induced VCAM-1 production in an AMPK-dependent manner in cultured human retinal microvascular endothelial cells (HRMECs).

Conclusion

CTRP3 may serve as a novel biomarker for DR severity. CTRP3 may represent a future novel therapeutic against DR, a common ocular complication of diabetes.

Can Commercially Available Handheld Retinal Cameras Effectively Screen Diabetic Retinopathy?

Organizations that care for people with diabetes have increasingly adopted telemedicine-based diabetic retinopathy screening (TMDRS) as a way to increase adherence to recommended retinal exams. Recently, handheld retinal cameras have emerged as a low-cost, lightweight alternative to traditional bulky tabletop retinal cameras. Few published clinical trials have been performed on handheld retinal cameras. Peer-reviewed articles about commercially available handheld retinal cameras have concluded that they are a usable alternative for TMDRS, however, the clinical results presented in these articles do not meet criteria published by the United Kingdom Diabetic Eye Screening Programme and the American Academy of Ophthalmology. The future will likely remedy the shortcomings of currently available handheld retinal cameras, and will create more opportunities for preventing diabetic blindness.

Payment Reform Needed to Address Health Disparities of Undiagnosed Diabetic Retinopathy in the City of Chicago

Introduction

The Affordable Care Act (ACA) has expanded health coverage for thousands of Illinois residents. Expanded coverage, however, does not guarantee appropriate health care. Diabetes and its ocular complications serve as an example of how providers in underserved urban areas may not be able to keep up with new demand for labor- and technology-intensive health care unless changes in reimbursement policies are instituted.

Methods

A retrospective cohort study was conducted using medical encounter information from the Chicago HealthLNK Data Repository (HDR), an assembly of non-duplicated and de-identified patient medical records. We used a method of estimating the geographic distribution of undiagnosed diabetic retinopathy in the city of Chicago to illustrate the magnitude of potentially preventable eye disease. All rates were calculated for all ZIP Codes within Chicago (Cook County), and statistical differences between observed and geographically adjusted expected rates (p < 0.10, p < 0.05, p < 0.01) were highlighted as underserved areas.

Results

This analysis included 150,661 patients with diabetes identified from a total of nearly two million patients in Chicago. High rates of undetected diabetic retinopathy were found in low-income and minority areas. Within these areas, 37% of the identified diabetics were uninsured, with rates ranging widely from 20% to 68.6%. Among those with insurance, 32.8% were covered by Medicare and only 10% by Medicaid. Most patients with untreated diabetic retinopathy were found to reside in areas where primary health care is provided through Federally Qualified Health Centers.

Conclusions

With 150,661 diabetics identified in the city of Chicago, and this number continuing to rise each year, a manpower approach with ophthalmologist screening for diabetic retinopathy is not realistic. The ability to identify the growing number of diabetic patients with retinopathy in low-income areas will likely require the adoption of cost-effective screening technologies that are currently not funded by Medicare and Medicaid.