A novel strategy for the estimation of the general height of the visual field in patients with glaucoma

Abstract

Background More accurate estimation of the general height of the visual field may improve our ability to detect and monitor progression of diseases affecting visual function such as glaucoma. General height (GH) can be affected by factors such as cataracts, pupillary miosis, refractive error, and learning and fatigue effects. The conventional GH index, consisting of subtracting the 85th largest value from the total-deviation map, has been shown to overestimate the height in patients with moderate and advanced glaucoma. We aimed at developing an improved estimator for general height based on ranking of total-deviation values that are within normal limits (GHr). Methods Two datasets were used for the comparisons between GH and GHr estimates: one with 369 visual fields for 102 controls and another with 500 visual fields for 124 patients. For controls, we compared the distributions of mean of total deviation (MD) and of mean of pattern deviation (MPD) derived from both the GH and the GHr estimates. For patients, we assessed agreement between both estimates and between pairs of consecutive visits. We also compared linear fits in progression analyses. All data were collected with 24-2 SITA Standard. Results For control subjects and patients with MD above −5.5 dB, estimates with the GHr estimator were not significantly different than with the GH estimator. For patients with glaucoma with MD below −5.5 dB, as MD became more negative the GH estimates were increasingly greater than GHr estimates. For patients with glaucoma, test-retest variability was lower with the GHr estimator: between visits agreement was better for GHr estimates than for GH estimates (SD of 0.8 dB versus 1.5 dB; p < 0.0001). Linear progression analysis fitted better the data from the GHr estimator. Root mean square error for GHr was 0.4 dB; lower than the 0.8 dB for GH (p < 0.0001). Conclusions The novel GHr estimator is very different from the conventional GH estimator, has more solid foundations and better statistical properties. Nevertheless, it is not always better than the GH estimator, in particular, if no focal loss is present. Pattern-deviation maps obtained with GHr reduce systematic underestimation of glaucomatous damage.

Customizing Perimetric Locations Based on En Face Images of Retinal Nerve Fiber Bundles With Glaucomatous Damage

“…These correspond to 25 and 28 dB, respectively, on the HFA. 14 These two contrast levels were used to compensate for differences in the height of the hill of vision 15 100% contrast would be appropriate for those with a low hill of vision and 50% contrast for a high hill of vision. For each contrast level, one presentation of the stimulus was made at each location, selected randomly.…”

Functional characteristics of glaucoma related arcuate defects seen on OCT en face visualisation of the retinal nerve fibre layer

“…The 24‐2 total deviation values were obtained from the patients’ routine clinic visits with the Humphrey Field Analyzer using a G‐III stimulus. The total deviation maps provided a raw estimate of the perimetric deviation from age norms without further adjustments to the data such as in a pattern deviation map, which uses a method that can overestimate the adjustment factor in eyes with perimetric defects 24,25 …”

Using perimetric data to estimate ganglion cell loss for detecting progression of glaucoma: a comparison of models

“…We have found that forced‐choice methods can reduce between‐visit variability in glaucomatous defects by a factor of two as compared to perimetry . Perimetric indices provide an adjustment for homogeneous fluctuation with the ‘pattern deviation’ (PD) analysis, which attempts to compensate for fluctuations in the height of the hill of vision but is known to have limitations . In a follow‐up analysis we used PD to estimate the height of hill of vision, but correcting for this did not reduce variability in ganglion cell number.…”

“…39 Perimetric indices provide an adjustment for homogeneous fluctuation with the 'pattern deviation' (PD) analysis, which attempts to compensate for fluctuations in the height of the hill of vision but is known to have limitations. 40 In a follow-up analysis we used PD to estimate the height of hill of vision, but correcting for this did not reduce variability in ganglion cell number. The determination of visual progression in logarithmic units appears to be more robust than determination of visual progression in ganglion cell numbers.…”