Importance Visualization and interpretation of the optic nerve and retina is an essential part of most physical examinations. Objectives To design and validate a smartphone-based retinal adapter enabling image capture and remote grading of the retina Design, setting and participants Validation study comparing the grading of optic nerves from smartphones images with those of a Digital Fundus Camera. Both image sets were independently graded at Moorfields Eye Hospital Reading Centre. Nested within the six-year follow-up of the Nakuru Eye Disease Cohort in Kenya: 1,460adults (2,920eyes) aged 55years and above were recruited consecutively from the Study. A sub-set of 100 optic disc images from both methods were further used to validate a grading app for the optic nerves. Main outcome(s) and measure(s) Vertical cup-to-disc-ratio (VCDR) for each test was compared, in terms of agreement (Bland-Altman & weighted Kappa) and test-retest variability (TRV). Results 2,152 optic nerve images were available from both methods (additionally 371 from reference but not Peek, 170 from Peek but not the reference and 227 from neither the reference camera or Peek). Bland-Altman analysis demonstrated a difference of the average of 0.02 with 95% limits of agreement between -0.21 and 0.17 and a weighted Kappa coefficient of 0.69 (excellent agreement). An experienced retinal photographer was compared to a lay photographer (no health care experience prior to the study) with no observable difference in image acquisition quality between them. Conclusions and relevance Non-clinical photographers using the low-cost Peek Retina adapter and smartphone were able to acquire optic nerve images at a standard that enabled comparable independent remote grading of the images to those acquired using a desktop retinal camera operated by an ophthalmic assistant. The potential for task-shifting and the detection of avoidable causes of blindness in the most at risk communities makes this an attractive public health intervention.

A low-cost alternative to the direct ophthalmoscope, a simple optical adapter for a smartphone, is described. It can overcome many of the technical challenges of fundoscopy, providing a high-resolution view of the retina through an un-dilated pupil. This can be used in locations with limited diagnostic resources to detect conditions such as glaucomatous optic neuropathy. Comparison of optic nerve images from commercial retinal screening cameras with the smartphone adapter demonstrates strong evidence for no difference in performance in glaucomatous disc grading (p=0.98, paired student t test, n=300).

Complications of diabetes mellitus, namely diabetic retinopathy and diabetic maculopathy, are the leading cause of blindness in working aged people. Sufferers can avoid blindness if identified early via retinal imaging. Systematic screening of the diabetic population has been shown to greatly reduce the prevalence and incidence of blindness within the population. Many national screening programs have digital fundus photography as their basis. In the past 5 years several techniques and adapters have been developed that allow digital fundus photography to be performed using smartphones. We review recent progress in smartphone-based fundus imaging and discuss its potential for integration into national systematic diabetic retinopathy screening programs. Some systems have produced promising initial results with respect to their agreement with reference standards. However further multisite trialling of such systems' use within implementable screening workflows is required if an evidence base strong enough to affect policy change is to be established. If this were to occur national diabetic retinopathy screening would, for the first time, become possible in low-and middle-income settings where cost and availability of trained eye care personnel are currently key barriers to implementation. As diabetes prevalence and incidence is increasing sharply in these settings, the impact on global blindness could be profound.

The digitization of ophthalmic images has opened up a number of exciting possibilities within eye care such as automated pathology detection, as well as electronic storage and transmission. However, technology capable of capturing digital ophthalmic images remains expensive. We review the latest progress in creating ophthalmic imaging devices based around smartphones, which are readily available to most practicing ophthalmologists and other medical professionals. If successfully developed to be inexpensive and to offer high-quality imaging capabilities, these devices will have huge potential for disease detection and reduction of preventable blindness across the globe. We discuss the specific implications of such devices in high-, middle-and low-income settings

PurposeContrast sensitivity (CS) testing is an important measure of visual function reflecting variations in everyday visual experience in different conditions and helps to identify more subtle vision loss. However, it is only infrequently used. To make this more accessible, we have developed and validated a smartphone-based CS test.MethodsA new tumbling-E smartphone-based CS test was developed, Peek Contrast Sensitivity (PeekCS). This was field tested and refined through several iterations. Reference standard was a tumbling-E Pelli-Robson CS test (PRCS). The validation study was conducted in community clinics in Ethiopia. Test-retest variability was measured for both PRCS and PeekCS. PRCS and PeekCS were then compared. Correlation coefficients and 95% confidence intervals (CIs) were calculated; 95% limits of agreement were calculated and displayed on Bland-Altman plots.ResultsPeekCS showed strong repeatability (correlation coefficient: 0.93; 95% CI: 0.91–0.95), which was comparable with PRCS (correlation coefficient: 0.96; 95% CI: 0.95–0.97). The 95% limit of agreement for test-retest variability of PRCS and PeekCS were −0.20 to 0.21 and −0.31 to 0.29, respectively. PRCS and PeekCS were highly correlated: 0.94 (95% CI: 0.93–0.95); 95% limits of agreement −0.27 to 0.29; and mean difference 0.010 (95% CI: −0.001 to 0.022). PeekCS had a faster testing time (44.6 seconds) than PRCS (48.6 seconds): mean difference −3.98 (95% CI: −5.38 to −2.58); P < 0.001.ConclusionsThe smartphone-based PeekCS is a repeatable and rapid test, providing results that are highly comparable with the commonly used PRCS test.Translational RelevancePeekCS provides an accessible and easy to perform alternative for CS testing, particularly in the community setting.

Retinal imaging is a fundamental tool in ophthalmic diagnostics. The potential use of retinal imaging within screening programs, with consequent need to analyze large numbers of images with high throughput, is pushing the digital image analysis field to find new solutions for the extraction of specific information from the retinal image. The aim of this review is to explore the latest progress in image processing techniques able to recognize specific retinal image features. and potential features of disease. In particular, this review aims to describe publically available retinal image databases, highlight different performance evaluators commonly used within the field, outline current approaches in feature-based retinal image analysis, and to map related trends. This review found two key areas to be addressed for the future development of automatic retinal image analysis: fundus image quality and the affect image processing may impose on relevant clinical information within the images. Performance evaluators of the algorithms reviewed are very promising, however absolute values are difficult to interpret when validating system suitability for use within clinical practice

Background: Attendance rates for eye clinics are low across low- and middle-income countries (LMICs) and exhibit marked sociodemographic (SD) inequalities. We aimed to quantify the association between a range of SD domains and attendance rates from vision screening in programmes launching in Botswana, Kenya and Nepal. Methods: We will develop a set of sociodemographic questions and introduce them into routine community-based eye screening programmes in Kenya, Botswana and Nepal, targeting children aged 5-18 years and adults. Our study design is a rolling survey, embedded within the Peek screening programme. The sociodemographic questions will be asked of 10% of all those presenting to be screened, and 100% of those identified with an eye problem. We will also collect data on whether people referred to ophthalmic clinic for treatment or further assessment attended, and we will use logistic regression to report odds ratios for this outcome attendance) for each socioeconomic domain in each country. We hypothesise that attendance rates will be lowest among marginalised sociodemographic groups such as older, less educated, less wealthy women. To identify the most appropriate sociodemographic items we will perform a literature review, and then hold workshops with researchers, academics, programme implementers, and programme designers in each country to tailor the domains and response options to the national context. We will report outcome data at 6 and 12 months, identifying the groups facing the highest barriers to access. Discussion: This low-risk, embedded, pragmatic, observational data collection will enable eye screening programme managers to accurately identify which sociodemographic groups are facing the highest systematic barriers to accessing care at any point in time. This information will be used to inform the development of service improvements to improve equity.

IntroductionGathering data on socioeconomic status (SES) is a prerequisite for any health programme that aims to assess and improve the equitable distribution of its outcomes. Many different modalities can be used to collect SES data, ranging from (1) face-to-face elicitation, to (2) telephone-administered questionnaires, to (3) automated text message-based systems. The relative costs and perceived benefits to patients and providers of these different data collection approaches is unknown. This protocol is for a systematic review that aims to compare the resource requirements, performance characteristics, and acceptability to participants and service providers of these three approaches to collect SES data from those enrolled in health programmes.Methods and analysisAn information specialist will conduct searches on the Cochrane Library, MEDLINE, Embase, Global Health, ClinicalTrials.gov, the WHO ICTRP and OpenGrey. All databases will be searched from 1999 to present with no language limits used. We will also search Google Scholar and check the reference lists of relevant articles for further potentially eligible studies. Any empirical study design will be eligible if it compares two or more modalities to elicit SES data from the following three; in-person, voice call, or automated phone-based systems. Two reviewers will independently screen titles, abstracts and full-text articles; and complete data extraction. For each study, we will extract data on the modality characteristics, primary outcomes (response rate and equivalence) and secondary outcomes (time, costs and acceptability to patients and providers). We will synthesise findings thematically without meta-analysis.Ethics and disseminationEthical approval is not required, as our review will include published and publicly accessible data. This review is part of a project to improve equitable access to eye care services in low-ioncome and middle-income countries. However, the findings will be useful to policy-makers and programme managers in a range of health settings and non-health settings. We will publish our findings in a peer-reviewed journal and develop an accessible summary of results for website posting and stakeholder meetings.PROSPERO registration numberCRD42021251959.