A perimetric nerve fiber bundle map

Weber, Jörg; Ulrich, Holger

doi:10.1007/bf00153928

Cited by 50 publications

(38 citation statements)

References 10 publications

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“…18 The PNFB cluster layout was derived by correlating high-resolution visual field defects with nerve fibre layer defects. 19,20 Subsequent work adapted the field clusters to the test points on a Humphrey Field Analyzer. 27 The ONH clusters were derived by overlaying nerve fibre layer photographs with the corresponding test points from a 24-2 field.…”

Section: Discussionmentioning

confidence: 99%

“…By exploring the change detected with new criteria on one data set and then validating the changes on an additional data set, it is possible to select an optimal criterion. A criterion that requires 2 points to change in a modified Perimetric Nerve Fibre Bundle Cluster 19,34 offers the best detection of progression without detecting improvement. The simple change criterion tested here requiring change over consecutive analyses was not as effective.…”

Section: Discussionmentioning

confidence: 99%

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Pointwise linear progression criteria and the detection of visual field change in a glaucoma trial

Wilkins

Fitzke²,

Khaw

2005

Eye

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Background Current pointwise linear regression (PLR) change criteria for visual field analysis are largely empirical. Methods Two independent sets of Humphrey Field Analyzer fields were analysed using PLR. Set i, 56 patients, and set ii, 97 patients, were followed over 16 months. Criteria were tested against set i, and then validated using set ii. Each criterion specified a fixed critical slope of 1 dB/year and with a range of significance from Po0.001 to 0.05. The criteria were varied by altering location number, cluster arrangement, and by requiring points to show change over both 12 and 16 months. True glaucomatous change was differentiated from noise by looking for exclusive progression (EP), the detection of progression without detection of improvement. Results Set i required 1 point to have a slope of 1 dB/year and Po0.05 labelled 64% progressing and 58% improving, whereas several stricter criteria were capable of detecting EP. Two points in a perimetric nerve fibre bundle (PNFB) cluster gave optimal EP detection, labelling 8.9% progressing in set i and 7.2% progressing in set ii with a cutoff P-value of 0.026 inset i and 0.013 inset ii. Conclusion Lax PLR criteria detect large amounts of change. Validating criteria using two data sets allow selection of better criteria, capable of detecting EP. The criterion involving 2 points changing in a PNFB cluster offers the best option for exclusively detecting progression.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Pointwise linear progression criteria and the detection of visual field change in a glaucoma trial

Wilkins

Fitzke²,

Khaw

2005

Eye

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“…Many studies 3,4,9,10,13,15,18 have used the Garway-Heath map, 19 which maps VF test point locations to specific regions of the ONH. Weber et al 20 described another structure-function map that correlated VF test points to optic disc margin locations, which were then extrapolated to OCT RNFL defects. Weber's method has since been used by others.…”

Section: Introductionmentioning

confidence: 99%

Correlation of localized glaucomatous visual field defects and spectral domain optical coherence tomography retinal nerve fiber layer thinning using a modified structure–function map for OCT

Boer

Chen

et al. 2015

Eye

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Purpose To study the correlation between glaucomatous visual field (VF) defects assessed by standard automated perimetry (SAP) and peripapillary retinal nerve fiber layer (RNFL) thinning measured by spectral domain optical coherence tomography (OCT) using a modified OCT-based peripapillary RNFL structure-function map. Patients and methods Perimetric glaucoma patients and age-matched normal control subjects were recruited from a university hospital clinic. All eyes underwent testing with the Spectralis spectral domain OCT and SAP on the same day. An OCT-based correspondence map, which correlated VF areas with peripapillary RNFL sectors was created to evaluate the relationship between glaucomatous RNFL thinning and VF loss in six nerve fiber layer bundle areas. Correlations of RNFL thinning with corresponding VF defects were examined using Spearman rankorder correlations. To demonstrate the association between localized VF defects and RNFL thickness, the theoretical curves were made according to an established log-linear model. The measured RNFL thickness values and VF defects were presented in the same scatterplot for each sector. Results Fifty-six glaucoma patients and 85 normal subjects were included in the study.Significant association between localized VF loss and RNFL thinning was found in corresponding areas. Data from the current study fit well with established log-linear models, which compare RNFL thickness values with VF defects. Conclusion Analysis of RNFL thinning in eyes with localized glaucomatous VF defects showed good structure-function correlation in a new OCT-based structure-function correspondence map.

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“…These classifiers attempt to take account of the spatial relationship between neighboring locations. Some approaches cluster the locations based on known physiological retinal cell maps [18,24], and apply regression to the mean of the clusters [20,22]. Others use neural networks as classifiers, relying on the network to learn any spatial relations [3,11,16, and references therein].…”

Section: Determining Progressionmentioning

confidence: 99%

“…• Using physiologically clustered data where the 76 test locations are reduced into several cluster based on physiological criteria [24].…”

Section: Other Approachesmentioning

confidence: 99%

Determining Progression in Glaucoma Using Visual Fields

Turpin

Frank

Hall

et al. 2001

Advances in Knowledge Discovery and Data Mining

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Abstract. The standardized visual field assessment, which measures visual function in 76 locations of the central visual area, is an important diagnostic tool in the treatment of the eye disease glaucoma. It helps determine whether the disease is stable or progressing towards blindness, with important implications for treatment. Automatic techniques to classify patients based on this assessment have had limited success, primarily due to the high variability of individual visual field measurements. The purpose of this paper is to describe the problem of visual field classification to the data mining community, and assess the success of data mining techniques on it. Preliminary results show that machine learning methods rival existing techniques for predicting whether glaucoma is progressing-though we have not yet been able to demonstrate improvements that are statistically significant. It is likely that further improvement is possible, and we encourage others to work on this important practical data mining problem.

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A perimetric nerve fiber bundle map

Cited by 50 publications

References 10 publications

Pointwise linear progression criteria and the detection of visual field change in a glaucoma trial

Pointwise linear progression criteria and the detection of visual field change in a glaucoma trial

Correlation of localized glaucomatous visual field defects and spectral domain optical coherence tomography retinal nerve fiber layer thinning using a modified structure–function map for OCT

Determining Progression in Glaucoma Using Visual Fields

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