Handheld Fundus Camera Research Articles

Evaluation of a remote telemedicine platform using a novel handheld fundus camera: Physician and patient perceptions from real-world experience.

Although teleophthalmology has gained traction in recent years, it is at the center of the coronavirus disease pandemic. However, most hospitals are not ready owing to a severe lack of real-world experience. Furthermore, a limited number of studies have evaluated telemedicine applications on remote islands. This study aimed to evaluate real-world clinical and referral accuracy, image quality, physician-perceived diagnostic certainty, and patient satisfaction with telemedicine eye screening using a novel handheld fundus camera in a rural and medically underserved population. This prospective study included 176 eyes from a remote island. All participants underwent a comprehensive ophthalmic examination. Nonmydriatic retinal images obtained using a handheld fundus camera were reviewed by two retinal specialists to determine image quality, diagnosis, and need for referrals. The agreement of diagnosis between image-based assessments was compared with that of binocular indirect ophthalmoscopic assessments. Image quality of fundus photographs was considered acceptable or ideal in 97.7% and 95.5% of eyes assessed by two reviewers, respectively. There was considerable agreement in diagnosis between the indirect ophthalmoscopic assessment and image-based assessment by two reviewers (Cohen's kappa = 0.80 and 0.78, respectively). Likewise, substantial agreement was achieved in the referrals. The sensitivity for referable retinopathy from the two reviewers was 78% (95% confidence interval [CI], 57%-91%) and 78% (95% CI, 57%-91%), whereas specificity was 99% (95% CI, 95%-99%] and 98% (95% CI, 93%-99%), respectively. For physicians' perceived certainty of diagnosis, 93.8% and 90.3% were considered either certain or reliable. Overall, 97.4% of participants were satisfied with their experiences and greatly valued the telemedicine services. Novel fundus camera-based telemedicine screening demonstrated high accuracy in detecting clinically significant retinopathy in real-world settings. It achieved high patient satisfaction and physician-perceived certainty in diagnosis with reliable image quality, which may be scaled internationally to overcome geographical barriers under the global pandemic.

Posterior Segment Pathologies in Leprosy Patients with Visual Impairment: A Case Series

Leprosy is an important infectious disease, which is still prevalent in developing countries including Indonesia. This disease may affect the skin, extremities, peripheral nerves, and the eyes, causing disabilities of the patient. Leprosy is known to cause various ocular disorders, however, posterior segment abnormalities which involve the retina, choroid dan vitreous, have rarely been reported. Therefore, we present a case series of patients with posterior segment pathologies in visually impaired leprosy patients. These patients were identified during a community-based screening program on 99 leprosy patients, held in July 2019 in Alverno Hospital, Singkawang West Kalimantan. Patient comprised of inpatients and former patients who lived within the city and nearby cities who were invited for the program. All patients underwent comprehensive ophthalmology examination, performed by general ophthalmologists. Visual impairment was found in 15 patients, and their pupils were dilated, followed with posterior segment examination with indirect ophthalmoscopy and fundus photograph, using a handheld fundus camera, done by a vitreoretina specialist. Out of all patients screened, we did not find any leprosy-related posterior segment abnormalities. However, posterior segment pathologies were found in six patients, including peripapillary atrophy, myopic crescent, drusen and chorioretinal atrophy. One patient showed extensive chorioretinal atrophy with pigment clumping, which may be caused by leprosy- related chronic inflammatory process.

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.

A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

To explore the performance in diabetic retinopathy (DR) screening of artificial intelligence (AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. Overall, 630 eyes were included from three centers and screened by a handheld camera (Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR. Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range (1.47, 1.48, and 1.40) than conventional tabletop cameras (1.30, 1.28, and 1.18; P<0.001). Detection of retinal hemorrhage, hard exudation, and macular edema were comparable between the two modalities, in principle, with the area under the curve of the handheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1% (95%CI: 72.1%-92.2%) and 97.4% (95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory; however, Phoebus showed a high sensitivity (88.2%, 95%CI: 79.4%-97.1%) and low specificity (40.7%, 95%CI: 34.1%-47.2%) when detecting referable DR. The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.

A new approach to non-mydriatic portable fundus imaging

ABSTRACT Introduction The present study proposes a new hand-held non-mydriatic fundus camera for retinal imaging. The goal is to design a fundus camera which is equally effective in both clinical and telemedicine scenarios. Areas covered A new retinal illumination approach is proposed to address the main dilemma of the optical design, i.e. balancing efficacy with structural simplicity. This is achieved by symmetrical and co-axial placement of multiple illumination sources along the optical pathway. Each illumination source includes a white and a Near Infra-Red (NIR) LED, which are placed adjacent to each other. Hence, the camera can produce a view-finder with NIR illumination without the need for additional beam-splitters and filters. Expert Opinion The proposed design blends the structural simplicity of the ‘off-axis illumination with the wide field of view and uniform illumination of the ‘ring’ illumination. Moreover, the camera is designed to work with Android-based smartphones, which can easily be mounted and interfaced. The efficacy of the proposed camera is determined by ocular safety analysis and comparative evaluation with a table-top fundus camera. The results convincingly demonstrate the ability of the proposed camera as a primary driver of a wide-scale screening program in both clinical and remote resource constraint environments.

Feasibility and clinical utility of handheld fundus cameras for retinal imaging

Background/objectivesHandheld fundus cameras are portable and cheaper alternatives to table-top counterparts. To date there have been no studies comparing feasibility and clinical utility of handheld fundus cameras to table-top devices. We compare the feasibility and clinical utility of four handheld fundus cameras/retinal imaging devices (Remidio NMFOP, Volk Pictor Plus, Volk iNview, oDocs visoScope) to a table-top camera (Zeiss VisucamNM/FA).Subjects/methodsHealthy participants (n = 10, mean age ± SD = 21.0 ± 0.9 years) underwent fundus photography with five devices to assess success/failure rates of image acquisition. Participants with optic disc abnormalities (n = 8, mean age ± SD = 26.8 ± 15.9) and macular abnormalities (n = 10, mean age ± SD = 71.6 ± 15.4) underwent imaging with the top three scoring fundus cameras. Images were randomised and subsequently validated by ophthalmologists masked to the diagnoses and devices used.ResultsImage acquisition success rates (100%) were achieved in non-mydriatic and mydriatic settings for Zeiss, Remidio and Pictor, compared with lower success rates for iNview and oDocs. Image quality and gradeability were significantly higher for Zeiss, Remidio and Pictor (p < 0.0001) compared to iNview and oDocs. For cup:disc ratio estimates, similar levels of bias were seen for Zeiss (−0.09 ± SD:0.15), Remidio (−0.07 ± SD:0.14) and Pictor (−0.05 ± SD:0.16). Diagnostic sensitivities were highest for Zeiss (84.9%; 95% CI, 78.2–91.5%) followed by Pictor (78.1%; 95% CI, 66.6–89.5%) and Remidio (77.5%; 95% CI, 65.9–89.0%).ConclusionsRemidio and Pictor achieve comparable results to the Zeiss table-top camera. Both devices achieved similar scores in feasibility, image quality, image gradeability and diagnostic sensitivity. This suggests that these devices potentially offer a more cost-effective alternative in certain clinical scenarios.

Implementation and Evaluation of a Mobile Retinal Image Acquisition System for Screening Diabetic Retinopathy: Study Protocol

Screening diabetic retinopathy, a major cause of blindness, is time-consuming for ophthalmologists and has some constrains in achieving full coverage and attendance. The handheld fundus camera EyeFundusScope was recently developed to expand the scale of screening, drawing on images acquired in primary care and telescreening made by ophthalmologists or a computer-aided diagnosis (CADx) system. This study aims to assess the diagnostic accuracy of the interpretation of images captured using EyeFundusScope and perform its technical evaluation, including image quality, functionality, usability, and acceptance in a real-world clinical setting. Physicians and nurses without training in ophthalmology will use EyeFundusScope to take pictures of the retinas of patients with diabetes and the images will be classified for the presence or absence of diabetic retinopathy and image quality by a panel of ophthalmologists. A subgroup of patients will also be examined with the reference standard tabletop fundus camera. Screening results provided by the CADx system on images taken with EyeFundusScope will be compared against the ophthalmologists’ analysis of images taken with the tabletop fundus camera. Diagnostic accuracy measures with 95% confidence intervals (CIs) will be calculated for positive and negative test results. Proportion of each category of image quality will be presented. Usability and acceptance results will be presented qualitatively.

Detail-richest-channel based enhancement for retinal image and beyond

The quality of retinal photography is not always satisfactory due to the limited imaging conditions. Low contrast and insufficient brightness are common problems. By comprehensively analyzing the image formation model from an intuitive perspective, we present general principles of parameter settings for different enhancement scenarios, and this analysis provides theoretical support for designing the proposed method. In a retinal image, the green channel preserves the richest details due to the red free photography. We term the green channel as the “detail-richest-channel” in a retinal image, and it is used as the initial transmission map. Subsequently, the transmission map is corrected by the modified cubic function to reduce over enhancement. The proposed method is designed for enhancing retinal images photographed by handheld fundus camera initially, and it can be extended to other applications. A total of 1045 retinal images photographed by handheld fundus camera, 460 retinal images acquired from cataract patients using high-end fundus camera, and 890 underwater images are tested to validate the effectiveness of the proposed method. Results show that the proposed method can improve the quality of degraded images as well as preserve the natural visual perception.

Vision Platform Lesion Quality Measurement of Accessible Endoscopic Images Using Machine Learning Techniques

Through use of non-mydriatic retinal computed radiography which led to invaluable applications of handheld fundus cameras is illustrated by telemedicine and the medical “big data” age of dermatology. Even then, non-mydriatic visual acuity is more resistant to distortion in the case of portable fundus photography, such as irregular lighting, reduction of light, boring and poor contrast. These distortions are known as distortions of standardised content. This paper presents a methodology capable of identifying fair-generic images that would’ve been useful particularly for the collection of clear meaningful and interpretable data by inexperienced people. The algorithm relies on three features: the multi-channel feeling, only visible blur and the visual field function, which senses lighting and distortion of colour, blurred and low distortion of contrast respectively. A total of 536 photographs were classified by one senior and two junior ophthalmicists separately, 280 from private data bases and 256 from public collections, thereby splitting three calculation sizes of consistency and general quality into two groups. In order to evaluate the performance of the proposed algorithm, binary classifications were performed via the support vector machine and the decision tree and receptor operating function (ROC) curves were obtained and scheduled. The experimental findings indicate that the overall grade sensitivity of 87,45 percent at 91,66 percent with a Correlation coefficient region of 0,9450 indicates the importance of the implementation of the human-vision method algorithm, particularly with low-cost ophthalmic telemedicine’s, in order to assess the photographic performance, the non-mydriatic images.

Screening for Diabetic Retinopathy in Endocrinology Clinics by Using Handheld Cameras and Applying Artificial Intelligence Algorithms

According to estimations of the World Health Organization (WHO), there are almost 500M people in the world that suffer from diabetes. Projections suggest this number will surpass 700M by 2045 with global prevalence surpassing 7%. This huge population, alongside people with pre-diabetics, is prone to develop diabetic retinopathy, the leading cause of vision loss in the working age. While early screening can help prevent most cases of vision loss caused by diabetic retinopathy, the vast majority of patients are not being screened periodically as the guidelines instruct. The challenge is to find a reliable and convenient method to screen patients so that efficacy in detection of referral diabetic retinopathy is sufficient while integration with the flow of care is smooth, easy, simple, and cost-efficient. In this research, we described a screening process for more-than-mild retinopathy through the application of artificial intelligence (AI) algorithms on images obtained by a portable, handheld fundus camera.156 patients were screened for mtmDR indication. Four images were taken per patient, two macula centered and two optic disc centered. The 624 images were taken using the Optomed Aurora fundus camera and were uploaded using Optomed Direct-Upload. Fully blinded and independently, a certified, experienced ophthalmologist (contracted by Optomed and based in Finland) reviewed each patient to determine ground truth. Indications that are different than mtmDR were also documented by the ophthalmologist to meet exclusion criteria. Data was obtained from anonymized images uploaded to the cloud-based AEYE-DS system and analysis results from the AI algorithm were promptly returned to the users.Of the 156 patients, a certified ophthalmologist determined 100% reached sufficient quality of images for grading, and 36 had existing retinal diseases that fall under exclusion criteria, thus, 77% of the participants met the participation criteria. Of the remaining 120 patients, the AEYE-DS system determined that 2 patients had at least one insufficient quality image. AEYE-DS provided readings for each of the 118 remaining patients (98.3% of all patients). These were statistically compared to the output of the ground truth arm. The patient ground truth was defined as the most severe diagnosis from the four patient images; the ophthalmologist diagnosed 54 patients as mtmDR+ (45% prevalence). Of the 54 patients with referable DR, 50 were diagnosed and of the 64 mtmDR- patients, 61 were correctly diagnosed by the AI. In summary, the results of the study in terms of sensitivity and specificity were 92.6% and 95.3%, respectively.The results indicated accurate classification of diabetic patients that required referral to the ophthalmologist and those who did not. The results also demonstrated the potential of efficient screening and easy workflow integration into points of care such as endocrinology clinics.

Fundus evaluation in COVID-19 positives with non-severe disease.

Purpose:The aim of this work was to study and document retinal changes in coronavirus disease-2019 (COVID-19) positive patients with nonsevere disease using a nonmydriatic handheld fundus camera.Methods:A cross-sectional observational study was conducted on patients affected by COVID-19 who were admitted at our center. Our study included patients with no, mild, and moderate symptoms (nonsevere cases). Intensive care unit (ICU)-admitted patients were excluded considering the difficulty in procuring the fundus image by the handheld camera due to patients positioning. Patients with systemic conditions (diabetes, hypertension, and severe anemia) known to cause retinopathy were also excluded. Bedside anterior segment examination, fundus examination using indirect ophthalmoscopy and fundus imaging of each patient using a nonmydriatic handheld fundus camera was done by a trained ophthalmologist posted for COVID duty.Results:In a cohort of 138 patients, 94 (68.1%) were men and 44 (31.9%) were women. A total of 276 eyes were evaluated. The mean age of the patients was 38.51 ± 14.4 years. Anterior segment evaluation showed no abnormality in any of the eyes. On fundus screening using nonmydriatic handheld camera, a single streak of superficial retinal hemorrhage was noted at the posterior pole of the fundus in the left eye of one patient (0.72%), which was away from fovea. Laboratory tests revealed low hemoglobin (between 10 and 10.9 g/dL falling under mild Anemia) in 12 patients, elevated total leucocyte count in 6 patients, raised LDH in majority of patients (323 ± 101 Units/L) and elevated CRP (14.6 ± 30.99 mg/L). Rest of the lab parameters were within the normal range.Conclusion:In our study, COVID patients with mild-to-moderate symptoms did not show any inflammatory/infective or vaso-occlusive lesions in the retina attributable to COVID-19 infection, except one patient who had a single streak hemorrhage in the macula away from fovea, probably incidental.

RetIS: Unique Identification System of Goats through Retinal Analysis

Developing an accurate, reliable and tamper-proof unique identification system for identifying individual animals is one of the most important but challenging tasks in intelligent livestock management. Currently, unique identification for animals is done using methods like stenciling, ear tagging, ear notching, branding, etc. which create opportunities for the poachers, middle men and animal thieves to manipulate the tags and transfer animals across international borders, claim false insurance, poach for their meat, bones, etc. illegally. This becomes a huge headache for the livestock owners. In this paper, a novel biometric unique identification system called “RetIS” has been developed based on goat retinal image which is unique, tamper-proof, reliable and accurate. The identification system has been developed based on the origination and distribution pattern of the blood vessels through a circular ring around the optic disc, which remains constant for the entire lifetime of the goat. Goat retinal images have been captured using a handheld fundus camera. The captured images are then segmented, normalized and encoded for the creation of templates, which are eventually stored in a database for matching with query templates based on hamming distance criteria. In matching, it has been observed that if the hamming distance between stored and query template is less than equal to 0.37 (matching >= 63%), it can be confirmed that the stored and query template belongs to the same individual goat providing its unique identification, otherwise the templates belong to two separate individual goats. This model has been tested with more than 200 retinal images obtained from twelve different goats producing 99% accuracy. The performance of this proposed model has been compared with other animal identification technologies and is found to be the most accurate and precise.

Handheld fundus camera performance, image quality and outcomes of diabetic retinopathy grading in a pilot screening study

To compare the performance and image quality of the handheld fundus camera to standard table-top fundus cameras in diabetic retinopathy (DR) screening. The reliability and diagnostic accuracy of DR grading performed by an ophthalmologist and a photographer reader were evaluated. 157 patients with diabetes, attending screening or follow-up of DR, were evaluated by fundus photographs taken in mydriasis by Optomed Aurora and Canon or Zeiss Visucam fundus cameras. The image quality and the severity of DR were evaluated independently by an ophthalmologist and experienced photographer. The sensitivity, specificity and reliability of the assessments were determined. 1884 fundus images from 314 eyes were analysed. In 53% of all eyes, DR was not present. 10% had mild non-proliferative diabetic retinopathy (NPDR), 16% moderate NPDR, 6% severe NPDR and 16% proliferative diabetic retinopathy (PDR). The DR grading outcomes by Aurora highly equalled to those of Canon or Zeiss (κ = 0.93, 95% CI 0.91 to 0.94), and there was almost perfect agreement in grading between the ophthalmologist and photographer (κ = 0.96, 95% CI 0.95 to 0.97). The image quality of Aurora was sufficient for reliable assessment according to both graders in 84-88% of the cases. The Optomed Aurora fundus camera seems appropriate for DR screening. The sufficient image quality and high diagnostic accuracy for DR grading are supportive for a less expensive and easily transportable screening system for DR. Immediate image grading carried out by a photographer would further improve and speed up the screening process in all settings.

Wide field of view handheld smart fundus camera for telemedicine applications.

Purpose: We report that a large field-of-view (FOV) retinal image can be acquired by a smart fundus camera. Approach: This handheld system consists of a Raspberry Pi board, a touch screen display, a customized optical lens group, a ring light-emitting diode, and a Li-battery. Results: Wide FOV of is observed with proper lens configuration and can be expanded using image stitching algorithms. Conclusions: This customized handheld fundus camera provides better image quality than cellphone-based fundus imaging solutions and offers more operational features than traditional portable fundus cameras. It may benefit field-portable ophthalmic diagnostic applications.

Diabetic Retinopathy Screening in Patients with Diabetes Using a Handheld Fundus Camera: The Experience from the South-Eastern Region in Hungary.

Purpose Diabetic retinopathy (DR) is the leading cause of vision loss among active adults in industrialized countries. We aimed to investigate the prevalence of diabetes mellitus (DM), DR and its different grades, in patients with DM in the Csongrád County, South-Eastern region, Hungary. Furthermore, we aimed to detect the risk factors for developing DR and the diabetology/ophthalmology screening patterns and frequencies, as well as the effect of socioeconomic status- (SES-) related factors on the health and behavior of DM patients. Methods A cross-sectional study was conducted on adults (>18 years) involving handheld fundus camera screening (Smartscope Pro Optomed, Finland) and image assessment using the Spectra DR software (Health Intelligence, England). Self-completed questionnaires on self-perceived health status (SPHS) and health behavior, as well as visual acuity, HbA1c level, type of DM, and attendance at healthcare services were also recorded. Results 787 participants with fundus camera images and full self-administered questionnaires were included in the study; 46.2% of the images were unassessable. T1D and T2D were present in 13.5% and 86.5% of the participants, respectively. Among the T1D and T2D patients, 25.0% and 33.5% had DR, respectively. The SES showed significant proportion differences in the T1D group. Lower education was associated with a lower DR rate compared to non-DR (7.7% vs. 40.5%), while bad/very bad perceived financial status was associated with significantly higher DR proportion compared to non-DR (63.6% vs. 22.2%). Neither the SPHS nor the health behavior showed a significant relationship with the disease for both DM groups. Mild nonproliferative retinopathy without maculopathy (R1M0) was detected in 6% and 23% of the T1D and T2D patients having DR, respectively; R1 with maculopathy (R1M1) was present in 82% and 66% of the T1D and T2D groups, respectively. Both moderate nonproliferative retinopathy with maculopathy (R2M1) and active proliferative retinopathy with maculopathy (R3M1) were detected in 6% and 7% of the T1D and T2D patients having DR, respectively. The level of HbA1c affected the attendance at the diabetology screening (HbA1c > 7% associated with >50% of all quarter-yearly attendance in DM patients, and with 10% of the diabetology screening nonattendance). Conclusion The prevalence of DM and DR in the studied population in Hungary followed the country trend, with a slightly higher sight-threatening DR than the previously reported national average. SES appears to affect the DR rate, in particular, for T1D. Although DR screening using handheld cameras seems to be simple and dynamic, much training and experience, as well as overcoming the issue of decreased optic clarity is needed to achieve a proper level of image assessability, and in particular, for use in future telemedicine or artificial intelligence screening programs.

Clinical validation of a smartphone-based handheld fundus camera for the evaluation of optic nerve head.

To compare the quality of retinal images captured with a smartphone-based, handheld fundus camera with that of retinal images captured with a commercial fundus camera and to analyze their agreement in determining the cup-to-disc ratio for a cohort of ophthalmological patients. A total of 50 patients from a secondary ophthalmic outpatient service center underwent a bilateral fundus examination under mydriasis with a smartphone-based, handheld fundus camera and with a commercial fundus camera (4 images/patient by each). Two experienced ophthalmologists evaluated all the fundus images and graded them on the Likert 1-5 scale for quality. Multivariate regression analyses was then performed to evaluate the factors associated with the image quality. Two masked ophthalmologists determined the vertical cup-to-disc ratio of each fundus image, and both the intraobserver (between devices) and interobserver agreement between them was calculated. Ninety-eight images from 49 patients were processed in this study for their quality analysis. Ten images from five patients (four from commercial fundus camera and one from smartphone-based, handheld fundus camera) were not included in the analyses due to their extremely poor quality. The medians [interquartile interval] of the image quality were not significantly different between those from the smartphone-based, handheld fundus camera and from the commercial fundus camera (4 [4-5] versus 4 [3-4] respectively, p=0.06); however, both the images captured with the commercial fundus camera and the presence of media opacity presented a significant negative correlation with the image quality. Both the intraobserver [intraclass correlation coefficient (ICC)=0.82, p<0.001 and 0.83, p<0.001, for examiners 1 and 2, respectively] and interobserver (ICC=0.70, p=0.001 and 0.81; p<0.001, for smartphone-based handheld fundus camera and commercial fundus camera, respectively) agreements were excellent and statistically significant. Our results thus indicate that the smartphone-based, handheld fundus camera yields an image quality similar to that from a commercial fundus camera, with significant agreement in the cup-to-disc ratios between them. In addition to the good outcomes recorded, the smartphone-based, handheld fundus camera offers the advantages of portability and low-cost to serve as an alternative for fundus documentation for future telemedicine approaches in medical interventions.

Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low- and medium-income countries.

Diabetic retinopathy (DR) is a leading cause of blindness among adults and the numbers are projected to rise. There have been dramatic advances in the field of retinal imaging since the first fundus image was captured by Jackman and Webster in 1886. The currently available imaging modalities in the management of DR include fundus photography, fluorescein angiography, autofluorescence imaging, optical coherence tomography, optical coherence tomography angiography, and near-infrared reflectance imaging. These images are obtained using traditional fundus cameras, widefield fundus cameras, handheld fundus cameras, or smartphone-based fundus cameras. Fluorescence lifetime ophthalmoscopy, adaptive optics, multispectral and hyperspectral imaging, and multicolor imaging are the evolving technologies which are being researched for their potential applications in DR. Telemedicine has gained popularity in recent years as remote screening of DR has been made possible. Retinal imaging technologies integrated with artificial intelligence/deep-learning algorithms will likely be the way forward in the screening and grading of DR. We provide an overview of the current and upcoming imaging modalities which are relevant to the management of DR.

Fundus Lesions in Patients Hospitalized With COVID-19 Infection in Mumbai, India: A Retrospective Review

Background and objectiveCoronavirus disease 2019 (COVID-19) is a viral infection that has grown to be a global pandemic, and it is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The ocular involvement in COVID-19, both in the anterior and posterior segments, is increasingly being recognized by ophthalmologists. We report the fundus photographic and systemic findings in 25 patients without recent-onset visual symptoms who were hospitalized with COVID-19.MethodsPatients with COVID-19 infection who were admitted to an isolation ward/ICU in Mumbai, India during June-August 2020 underwent a comprehensive clinical and systemic evaluation. We performed a fundus evaluation using a handheld fundus camera during their admission period. We conducted a retrospective case record review and extracted demographic characteristics, laboratory findings, and fundus photographs from each case record.ResultsWe screened 25 non-consecutive patients, and they included 20 (80%) men and five (20%) women, with ages ranging from 31 to 79 years (mean: 56.3 years). Systemically, the spectrum of severity on admission varied from mild to moderate to severely ill. The majority of the patients had no complaints of recent visual loss. An analysis of fundus photographs of 50 eyes of 25 patients revealed no evidence of fundus lesions in as many as 48 photographs. Two photographs of two eyes of patients showed incidental lesions.ConclusionsWe found no evidence of vascular, inflammatory, or thromboembolic disease that could be linked to COVID-19 infection in any of the images we studied; however, fundus examination may be utilized in patients with co-infection.

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 handheld fundus camera with mydriasis for retinal imaging of diabetic retinopathy screening in China: a prospective comparison study

ObjectivesTo investigate the clinical validity of using a handheld fundus camera to detect diabetic retinopathy (DR) in China.Design and settingsProspective comparison study of the handheld fundus camera with a standard...