Variability of visual field measurements is correlated with the gradient of visual sensitivity

Abstract

Conventional static automated perimetry provides important clinical information, but its utility is limited by considerable test-retest variability. Fixational eye movements during testing could contribute to variability. To assess this possibility, it is important to know how much sensitivity change would be caused by a given eye movement. To investigate this, we have evaluated the gradient, the rate at which sensitivity changes with location. We tested one eye each, twice within 3 weeks, of 29 patients with glaucoma, 17 young normal subjects and 13 older normal subjects. The 10-2 test pattern with the SITA Standard algorithm was used to assess sensitivity at locations with 2 degrees spacing. Variability and gradient were calculated at individual test locations. Matrix correlations were determined between variability and gradient, and were substantial for the patients with glaucoma. The results were consistent with a substantial contribution to test-retest variability from small fixational eye movements interacting with visual field gradient. Successful characterization of the gradient of sensitivity appears to require sampling at relatively close spacing, as in the 10-2 test pattern.

Choice of Stimulus Range and Size Can Reduce Test-Retest Variability in Glaucomatous Visual Field Defects

“…The soft edges and larger size for the blobs are important because primate ganglion cells are responsive when the size III stimulus is centered within 60.28 of the midpoint of the ganglion receptive field and become unresponsive when the stimulus is 0.58 from the midpoint. 22 This is in accord with a proposal that fixational instability in perimetry with SD ¼~0.58 can account for high variability for the size III stimulus in regions of the visual field with gradients in sensitivity 21,45 or with ''holes'' in ganglion cell arrays damaged by glaucoma. 20,26 Both of these explanations for the effect are consistent with our finding that test-retest variability may be decreased with only a modest increase in stimulus size when soft edges are used.…”

“…For the Gabor stimuli, variability was only 4% high in the outer zone. These findings are consistent with both ganglion saturation 22 and visual field gradients 21 as explanations for elevated variability because, for size III, more central locations have higher mean normal sensitivities and more shallow visual field gradients while Gabors yield high mean normal sensitivities across the tested locations, with very slight gradients.…”

“…Perimetry with Gabor stimuli is similar to perimetry with frequencydoubling stimuli in that test-retest variability does not increase in glaucomatous defects. 18 These variability properties of sinusoidal stimuli could be due to increased stimulus size [19][20][21] or to decreased stimulus range. [22][23][24] The current study was designed to assess the effects of stimulus size and range and to provide guidelines for selecting perimetric stimuli that reduce test-retest variability.…”

Predicting Visual Function from the Measurements of Retinal Nerve Fiber Layer Structure

“…This likely reflects the difficulty the prediction from RNFLT images have in identifying small, focal defects. Moreover, the floor effect in the VFs and SLP images 41,42 and the atypical scan pattern in SLP images, which may be associated with glaucoma severity, 43 may be additional causes of the overestimation at the lower end of the VF sensitivity. Furthermore, because the diagnosis of subjects in REH datasets includes structural criteria, the normal subjects in the training dataset may have supernormal structure and the glaucomatous subjects have greater than average structural damage.…”

Optimizing Structure–Function Relationship by Maximizing Correspondence Between Glaucomatous Visual Fields and Mathematical Retinal Nerve Fiber Models

“…However, the reproducibility of such visual field sensitivity measurements is rather poor, due to high levels of noise caused by, for example, eye movement, blinking, or imprecisions of the measuring device, and most importantly the variability of the patient's response. [2][3][4][5] A number of different factors have been shown to affect visual field measurements. 6 While noise may be reduced by using summary parameters, such as the mean defect (MD) or visual field index (VFI), these parameters hide important details of the visual field, such as its spatial structure.…”