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. 2025 Jan-Mar;19(1):15-27.
doi: 10.5005/jp-journals-10078-1468. Epub 2025 Mar 24.

Evaluating the Consistency of Online Circular Contrast Perimetry Across Different Computer Monitors: A Cross-sectional Study

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Evaluating the Consistency of Online Circular Contrast Perimetry Across Different Computer Monitors: A Cross-sectional Study

Angela Gong et al. J Curr Glaucoma Pract. 2025 Jan-Mar.

Abstract

Aim and background: The aim of this study is to evaluate the agreement between perimetric findings of a novel 24°, 52-loci online circular contrast perimetry (OCCP) application on three different computer monitors to determine its stability of testing across varying displays.

Materials and methods: Sixty-one participants (19 healthy controls, 42 with glaucoma) underwent SAP testing followed by OCCP testing on three uncalibrated computer monitors in randomized order: a large-screen (24-inch) desktop personal computer (DPC) (Dell, Texas, US), a 17-inch laptop (LPC) (Dell), and a 14-inch MacBook Pro (MP) (Apple, California, US).

Results: Agreement of mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI)/visual index (VI) values between MP, DPC, and LPC OCCP were strong, with intraclass correlations and Deming's coefficients ranging from 0.96 to 1.00 and 0.93 to 1.03, respectively. When OCCP tests were compared to SAP, ICCs and Deming's coefficients were less strong, ranging from 0.89 to 0.95 and 0.72 to 0.89. Bland-Altman analyses revealed higher biases (2.90 to 3.59 dB) and wider limits of agreement when comparing OCCP to SAP than when comparing OCCP on different monitors. Bland-Altman bias of contrast sensitivities for each 24-2 testing location revealed stronger relationships between OCCP tests on different monitors (-0.82 to 0.78) than between OCCP and SAP tests (-1.53 to 1.32).

Conclusion: OCCP demonstrates strong levels of test-retest agreement when performed on computer monitors of varying display and moderate to strong levels of correlation to SAP perimetric indices.

Clinical significance: With further enhancements, OCCP could potentially be used on different personal computers, which could help address current challenges in glaucoma care, such as limited access to traditional perimetric testing. This has the potential to expand the scope of glaucoma detection and monitoring, particularly in remote and underserved areas of our community.

How to cite this article: Gong A, Busija L, Skalicky SE. Evaluating the Consistency of Online Circular Contrast Perimetry Across Different Computer Monitors: A Cross-sectional Study. J Curr Glaucoma Pract 2025;19(1):15-27.

Keywords: Computer monitor; Cross-sectional study; Glaucoma; Perimetry; Visual field test.

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Conflict of interest statement

Source of support: Nil Conflict of interest: A/Prof Simon Skalicky is the director of Eyeonic Pty Ltd which owns patent WO2021051162A1 regarding online circular contrast perimetry.Conflict of interest: A/Prof Simon Skalicky is the director of Eyeonic Pty Ltd which owns patent WO2021051162A1 regarding online circular contrast perimetry.

Figures

Figs 1A to E:
Figs 1A to E:
Online circular contrast perimetry test settings. (A) Flickering test target; (B) Map of lower right quadrant in 24-2 perimetry loci testing with a magnification factor to peripheral loci that grows with eccentricity. The fixation target moves to all four corners of the screen for maximization of the sampling area at a comfortable viewing distance; (C) Sequence of target presentation: targets appear for three counterphase flicker cycles lasting 360 ms; contrast is graded at the start and end of target presentation; ms: millisecond. Figure adapted from Alawa et al.; (D) Fixation target: spinning golden star; (E) Blind spot localization optimizes the user's viewing distance; (B and E) The dark gray homogeneous circles are a diagrammatic representation of where test targets may appear and are not present during the live test
Figs 2A to D:
Figs 2A to D:
Testing computers and testing output. (A) Laptop personal computer; (B) Large-screen (24-inch) desktop personal computer; (C) MacBook (Apple); (D) Output from OCCP testing on three separate computers
Figs 3A and B:
Figs 3A and B:
Reliability indices. (A) OCCP averaged over all tests (MacBook Pro laptop (MP), desktop personal computer (DPC), laptop personal computer (LPC)) compared to SAP; (B) Comparison among OCCP on MP, DPC, and LPC; FP, false positive; FN, false negative; FL, fixation loss; TD, test duration
Figs 4A to F:
Figs 4A to F:
Bland-Altman plots (A–F) of MD values for online circular contrast perimetry (OCCP) and standard automated perimetry (SAP) tests. MacBook Pro laptop (MP) vs desktop personal computer (DPC) OCCP MD values are shown by (A) Laptop personal computer (LPC) vs DPC OCCP MD values are shown by (B) LPC vs MP OCCP MD values are shown by (C) MP OCCP vs SAP MD values are shown by (D) DPC OCCP vs SAP MD values are shown by (E) LPC OCCP vs SAP MD values are shown by (F). The continuous horizontal line represents the mean difference (bias) between tests; dashed and dotted horizontal lines represent the 95% limits of agreement (bias ± 1.96 SD). Black-colored circles represent controls, and white-colored circles represent glaucomatous eyes
Figs 5A to F:
Figs 5A to F:
Heatmaps representing Bland-Altman bias and 95% limits of agreement for pointwise sensitivities across each 24-2 test location (left eye orientation) for online circular contrast perimetry (OCCP) and standard automated perimetry (SAP) tests. (A) Desktop personal computer (DPC) vs MacBook Pro laptop (MP); (B) Laptop personal computer (LPC) vs MP; (C) LPC vs DPC; (D) MP vs SAP; (E) DPC vs SAP; (F) LPC vs SAP. Pointwise sensitivities are represented as bias ± 1.96 × standard deviation

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