ArticleTranslational vision science & technology2024
A Practical Framework for the Integration of Structural Data Into Perimetric Examinations.
Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: We sought to develop and evaluate a practical framework that supports structurally enhanced perimetric examinations. Methods: Two perimetric strategies were compared: standard Zippy Estimation through Sequential Testing (ZEST) procedure, a traditional visual field test with population-based prior distributions, and structural-ZEST (S-ZEST), enhanced with individual optical coherence tomography data to determine the starting parameters. The integration and collection of data was facilitated by a bespoke application developed in Shiny R (R Studio). The test was implemented using the Open Perimetry Interface on the Compass perimeter (CentreVue-iCare, Italy). The strategies were evaluated via simulations and on 10 visually healthy participants. The usability of the application was assessed in a simulated environment with 10 test users. Results: In simulations, the S-ZEST improved test speed in patients with glaucoma. In the practical implementation, there was a statistically significant decrease in the testing time (approximately 26%) and in the number of presentations per test with S-ZEST (P < 0.001). The structure-function relationship was similar between the two strategies. The time taken for users to complete the sequence of actions on the application was 52.9 ± 11.5 seconds (mean ± standard deviation). Conclusions: Structurally enhanced perimetric examination can significantly improve test time in healthy subjects and can be delivered through a user-friendly interface. Further testing will need to assess feasibility and performance of S-ZEST in patients with glaucoma. Translational Relevance: We have developed a user-friendly web application based within the Shiny environment for R, which implements an automated extraction of optical coherence tomography data from raw files and performs real-time calculations of structural features to inform the perimetric strategy.
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