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.