Literature DB >> 16412491

Modeling the sensitivity to variability relationship in perimetry.

S K Gardiner1, S Demirel, C A Johnson.   

Abstract

PURPOSE: Studies in glaucoma patients show that standard automated perimetry results increase in variability as sensitivity decreases. However, the reasons for this change are unclear. This study presents the principle of Divergent Dysfunction as a possible explanation for this change in variability, and incorporates it into a model that can be used to simulate perimetry.
METHODS: A computer program was written to simulate visual field test results based on the model, using a Full Threshold testing strategy. The validity of the simulation was tested by comparing it with normal sensitivity values, and with test-retest data from 63 participants evaluated five times each over the course of 1 month. The effect on the simulated data of varying parameters of the model was investigated, such as changing the magnitude of variability and the percentages of false positive and negative responses.
RESULTS: The correlation between subject and simulated test-retest data was 0.987. Several factors were found to affect the sensitivity-variability relationship for the simulated data, most notably the rate of sensitivity decline, the percentage of false positives, and the starting luminance of the test procedure.
CONCLUSIONS: The principle of Divergent Dysfunction presented here provides a plausible explanation for the sensitivity-variability relationship for standard automated perimetry in glaucomatous eyes. The model and resultant simulation program aim to provide an intuitive demonstration of the principle, which can also be used to examine the effectiveness of different testing strategies. These findings have great implications for future clinical research.

Entities:  

Mesh:

Year:  2006        PMID: 16412491     DOI: 10.1016/j.visres.2005.11.019

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  9 in total

1.  A cortical pooling model of spatial summation for perimetric stimuli.

Authors:  Fei Pan; William H Swanson
Journal:  J Vis       Date:  2006-10-13       Impact factor: 2.240

2.  Differences in the Relation Between Perimetric Sensitivity and Variability Between Locations Across the Visual Field.

Authors:  Stuart K Gardiner
Journal:  Invest Ophthalmol Vis Sci       Date:  2018-07-02       Impact factor: 4.799

3.  Linking structure and function in glaucoma.

Authors:  R S Harwerth; J L Wheat; M J Fredette; D R Anderson
Journal:  Prog Retin Eye Res       Date:  2010-03-11       Impact factor: 21.198

4.  Point-wise variability of threshold sensitivity of 24-2 and 10-2 visual fields.

Authors:  Aparna Rao; Harsha L Rao; Debananda Padhy
Journal:  Taiwan J Ophthalmol       Date:  2022-05-26

5.  Is there evidence for continued learning over multiple years in perimetry?

Authors:  Stuart K Gardiner; Shaban Demirel; Chris A Johnson
Journal:  Optom Vis Sci       Date:  2008-11       Impact factor: 1.973

6.  Seasonal changes in visual field sensitivity and intraocular pressure in the ocular hypertension treatment study.

Authors:  Stuart K Gardiner; Shaban Demirel; Mae O Gordon; Michael A Kass
Journal:  Ophthalmology       Date:  2013-01-26       Impact factor: 12.079

7.  A two-stage neural spiking model of visual contrast detection in perimetry.

Authors:  S K Gardiner; W H Swanson; S Demirel; A M McKendrick; A Turpin; C A Johnson
Journal:  Vision Res       Date:  2008-07-21       Impact factor: 1.886

8.  A Method Using Goldmann Stimulus Sizes I to V-Measured Sensitivities to Predict Lead Time Gained to Visual Field Defect Detection in Early Glaucoma.

Authors:  Jack Phu; Sieu K Khuu; Bang V Bui; Michael Kalloniatis
Journal:  Transl Vis Sci Technol       Date:  2018-06-07       Impact factor: 3.283

9.  Reducing Spatial Uncertainty Through Attentional Cueing Improves Contrast Sensitivity in Regions of the Visual Field With Glaucomatous Defects.

Authors:  Jack Phu; Michael Kalloniatis; Sieu K Khuu
Journal:  Transl Vis Sci Technol       Date:  2018-03-23       Impact factor: 3.283

  9 in total

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