A Practical Framework for the Integration of Structural Data Into Perimetric Examinations.

Area of Science:

• Ophthalmology
• Medical Technology
• Data Science

Background:

• Perimetric examinations are crucial for diagnosing and monitoring visual field defects.
• Traditional visual field tests like Zippy Estimation through Sequential Testing (ZEST) rely on population-based data.
• Integrating structural information could potentially enhance the efficiency of perimetric testing.

Purpose of the Study:

• To develop and evaluate a practical framework for structurally enhanced perimetric examinations.
• To compare the efficiency of standard ZEST with a novel structural-ZEST (S-ZEST) approach.

Main Methods:

• S-ZEST was developed, incorporating individual optical coherence tomography (OCT) data to optimize starting parameters for visual field testing.
• A bespoke application was created using Shiny R for data integration and real-time calculations.
• The Compass perimeter (CentreVue-iCare) and Open Perimetry Interface were used for test implementation.
• Strategies were evaluated through simulations and in 10 visually healthy participants.

Main Results:

• Simulations indicated S-ZEST improved test speed in simulated glaucoma patients.
• Practical implementation showed a statistically significant reduction in testing time (approx. 26%) and presentations per test with S-ZEST (P < 0.001).
• The structure-function relationship remained similar between standard ZEST and S-ZEST.

Conclusions:

• Structurally enhanced perimetric examinations, like S-ZEST, can significantly decrease testing time in healthy subjects.
• The S-ZEST approach is deliverable via a user-friendly interface.
• Further research is needed to assess S-ZEST's feasibility and performance in glaucoma patients.