Dataset Information

Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data.

ABSTRACT: To test the hypothesis that specific locations and patterns of threshold findings within the visual field have predictive value for progressive glaucomatous optic neuropathy (pGON).Age-adjusted standard automated perimetry thresholds, along with other clinical variables gathered at the initial examination of 168 individuals with high-risk ocular hypertension or early glaucoma, were used as predictors in a classification tree model. The classification variable was a determination of pGON, based on longitudinally gathered stereo optic nerve head photographs. Only data for the worse eye of each individual were included. Data from 100 normal subjects were used to test the specificity of the models.Classification tree models suggest that patterns of baseline visual field findings are predictive of pGON with sensitivity 65% and specificity 87% on average. Average specificity when data from normal subjects were run on the models was 69%.Classification trees can be used to determine which visual field locations are most predictive of poorer prognosis for pGON. Spatial patterns within the visual field convey useable predictive information, in most cases when thresholds are still well within the classically defined normal range.

SUBMITTER: Demirel S

PROVIDER: S-EPMC2759404 | biostudies-literature | 2009 Feb

REPOSITORIES: biostudies-literature

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Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data.

Demirel Shaban S Fortune Brad B Fan Juanjuan J Levine Richard A RA Torres Rodrigo R Nguyen Hau H Mansberger Steven L SL Gardiner Stuart K SK Cioffi George A GA Johnson Chris A CA

Investigative ophthalmology & visual science 20081020 2

<h4>Purpose</h4>To test the hypothesis that specific locations and patterns of threshold findings within the visual field have predictive value for progressive glaucomatous optic neuropathy (pGON).<h4>Methods</h4>Age-adjusted standard automated perimetry thresholds, along with other clinical variables gathered at the initial examination of 168 individuals with high-risk ocular hypertension or early glaucoma, were used as predictors in a classification tree model. The classification variable was ...[more]

PMID: 18936149

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Project description:PurposeThe Olleyes VisuALL-K is a pediatric videogame-based static threshold perimeter using a virtual reality headset. We determined normal threshold sensitivities for the 24-2 test locations using the virtual reality perimetry (VRP) and also tested patients on the Humphrey Field Analyzer (HFA). Patient satisfaction for the two instruments was compared.MethodsThis exploratory study tested 50 normal pediatric participants aged 8 to 17 years on the HFA and VRP. The main outcome measure was threshold sensitivity at the 24-2 test locations for the two instruments.ResultsThe mean participant age was 13.0 ± 2.6 years; 50% were female. The threshold values for VRP are reported as measured on the device and after conversion to an HFA-equivalent scale. Age-adjusted thresholds showed a mean sensitivity of 31.8 ± 1.1 dB (46.1 ± dB HFA equivalent) diminution from the maximum light intensity in the VRP and 31.0 ± 1.5 dB diminution from the maximum light intensity in the HFA; interparticipant variability in mean threshold sensitivity was 2.7 ± 0.4 dB for the VRP and 2.7 ± 0.6 dB for the HFA. The HFA demonstrated decreased threshold sensitivity with increasing eccentricity, whereas the VRP threshold did not seem to vary with eccentricity. Mild age effects on threshold sensitivity were seen in the VRP and the HFA (R2 = 0.11, P < 0.001 and R2 = 0.05, P < 0.05, respectively). The mean time to completion for VRP and HFA was 7.6 ± 1.5 and 5.3 ± 0.9 min/eye, respectively (P < 0.0001). Patient satisfaction scores favored VRP (P < 0.01) despite the longer test duration.ConclusionsThe Olleyes game-based VRP and HFA can be used to map out the peripheral vision in normal children. The VRP has a higher patient satisfaction when used in children than the HFA. The portability of the test allows it to be performed in a myriad of environments, lending a flexibility that can benefit this population.Translational relevanceThis virtual reality perimetry device provides an alternative to the Humphrey Field Analyzer for children.

Project description:To quantify the morphological features of the optic nerve head using radial polynomials, to use these morphometric models as the basis for classification of glaucomatous optic neuropathy via an automated decision tree induction algorithm, and to compare these classification results with established procedures.A cohort of patients with high-risk ocular hypertension or early glaucoma (n=179) and a second cohort of normal subjects (n=96) were evaluated for glaucomatous optic neuropathy using stereographic disc photography and confocal scanning laser tomography. Morphological features of the optic nerve head region were modeled from the tomography data using pseudo-Zernike radial polynomials and features derived from these models were used as the basis for classification by a decision tree induction algorithm. Decision tree classification performance was compared with expert classification of stereographic disc photographs and analysis of neural retinal rim thickness by Moorfields Regression Analysis (MRA).Root mean squared error of the morphometric models decreased asymptotically with additional polynomial coefficients, from 62±0.5 (32 coefficients) to 32±5.7 ?m (256 coefficients). Optimal morphometric classification was derived from a subset of 64 total features and had low sensitivity (69%), high specificity (88%), very good accuracy (80%), and area under the receiver operating characteristic curve (AUROC) was 88% (95% confidence interval, 78%-98%). In comparison, MRA classification of the same records had a comparatively poorer sensitivity (55%), but had higher specificity (95%), with similar overall accuracy (78%) and AUROC curve, 83% (95% CI, 70%-96%).Pseudo-Zernike radial polynomials provide a mathematically compact and faithful morphological representation of the structural features of the optic nerve head. This morphometric method of glaucomatous optic neuropathy classification has greater sensitivity, and similar overall classification performance (AUROC) when compared with classification by neural retinal rim thickness by MRA in patients with high-risk ocular hypertension and early glaucoma.

Dataset Information

Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data.

Publications

Predicting progressive glaucomatous optic neuropathy using baseline standard automated perimetry data.

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