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. 2022 Nov 2;1(11):e0000131.
doi: 10.1371/journal.pdig.0000131. eCollection 2022 Nov.

Diagnostic accuracy of handheld fundus photography: A comparative study of three commercially available cameras

Affiliations

Diagnostic accuracy of handheld fundus photography: A comparative study of three commercially available cameras

Louisa Lu et al. PLOS Digit Health. .

Abstract

The objective of this study was to compare the sensitivity and specificity of handheld fundus cameras in detecting diabetic retinopathy (DR), diabetic macular edema (DME), and macular degeneration. Participants in the study, conducted at Maharaj Nakorn Hospital in Northern Thailand between September 2018 and May 2019, underwent an ophthalmologist examination as well as mydriatic fundus photography with three handheld fundus cameras (iNview, Peek Retina, Pictor Plus). Photographs were graded and adjudicated by masked ophthalmologists. Outcome measures included the sensitivity and specificity of each fundus camera for detecting DR, DME, and macular degeneration, relative to ophthalmologist examination. Fundus photographs of 355 eyes from 185 participants were captured with each of the three retinal cameras. Of the 355 eyes, 102 had DR, 71 had DME, and 89 had macular degeneration on ophthalmologist examination. The Pictor Plus was the most sensitive camera for each of the diseases (73-77%) and also achieved relatively high specificity (77-91%). The Peek Retina was the most specific (96-99%), although in part due to its low sensitivity (6-18%). The iNview had slightly lower estimates of sensitivity (55-72%) and specificity (86-90%) compared to the Pictor Plus. These findings demonstrated that the handheld cameras achieved high specificity but variable sensitivities in detecting DR, DME, and macular degeneration. The Pictor Plus, iNview, and Peek Retina would have distinct advantages and disadvantages when applied for utilization in tele-ophthalmology retinal screening programs.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Quality assessment and learning curve of three handheld retina cameras.
Each plot depicts the quality scores as a stacked bar graph over quintiles of enrollment, with quintile 1 representing the earliest enrollments. Plots are depicted stratified both by quality metric and camera. For image clarity, 0 = poor, 1 = fair, 2 = good, 3 = excellent; for coverage, 0 = absent, 1 = partly visualized, 2 = fully visualized.
Fig 2
Fig 2. Representative images from the Pictor Plus, Peek Retina, and iNview.
Fundus photos in the top, middle, and bottom rows were taken with the Pictor Plus, Peek Retina, and iNview, respectively. Each column shows photographs from the same eye, captured with different cameras; the first column depicts an eye classified by the reference standard examination as diabetic retinopathy, the second column as diabetic macular edema, and the third column as macular degeneration. Photographs are shown as captured and graded; they have been compressed in this composite image but were not otherwise manipulated with photo-editing software.
Fig 3
Fig 3. Positive and negative predictive values.
Predictive values were estimated across a range of possible disease prevalences for age-related macular degeneration (AMD), diabetic macular edema (DME) and diabetic retinopathy (DR). The top row of graphs show negative predictive value (NPV) and the bottom row positive predictive value (PPV).
Fig 4
Fig 4. Pairwise differences in diagnostic accuracy between three handheld fundus cameras.
Points represent the difference in diagnostic accuracy between two cameras, with bootstrapped 95% confidence intervals. Each panel compares the diagnostic accuracy of a different pair of cameras for diabetic retinopathy (circle), diabetic macular edema (triangle), and macular degeneration (square), with sensitivity (SENS) on the left side of the panel and specificity (SPEC) on the right.

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