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Pattern Recognition Analysis Reveals Unique Contrast Sensitivity Isocontours Using Static Perimetry Thresholds Across

Jack Phu^1,2, Sieu K Khuu², Lisa Nivison-Smith^1,2

¹Centre for Eye Health, University of New South Wales, Sydney, New South Wales, Australia.

Investigative Ophthalmology & Visual Science

|October 4, 2017

Summary

This study identified similar age-related visual sensitivity declines across specific visual field locations. These findings can refine glaucoma testing by grouping similar sensitivity areas, improving structure-function analysis.

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Area of Science:

Ophthalmology
Visual Science
Medical Imaging

Background:

Age-related decline in visual sensitivity is a known phenomenon.
Current visual field testing methods may not optimally group areas with similar age-related sensitivity changes.

Purpose of the Study:

To identify test locations with statistically similar age-related sensitivity decline and age-corrected contrast sensitivity isocontours (CSIs) in the central visual field (VF).
To compare these identified CSIs with existing test point clusters used by the Glaucoma Hemifield Test (GHT).

Main Methods:

Sixty healthy participants were tested using the Humphrey Field Analyzer 30-2 grid with Goldmann (G) stimulus sizes I-V.
Linear regression determined age-correction factors, and pattern recognition analysis clustered test locations into age-related and age-corrected CSIs.

Main Results:

A significant, test size-dependent age-related sensitivity decline was observed, with smaller stimuli declining faster and more rapidly in the periphery.
Smaller stimuli revealed a greater number of unique age-related CSIs, particularly in the mid-periphery.
Cluster analysis of age-corrected thresholds showed unique CSIs for each stimulus size, with smaller stimuli yielding more clusters; GHT zones did not always align with these CSIs.

Conclusions:

Cluster analysis successfully identified statistically significant groups of test locations with similar age-related decline.
Contrast sensitivity isocontours (CSIs) can help pool sensitivities, reducing variability and potentially guiding future structure-function and asymmetry analyses by matching areas with similar sensitivity signatures.