Patterns of functional vision loss in glaucoma determined with archetypal analysis

Elze, Tobias; Pasquale, Louis R.; Shen, Lucy Q.; Chen, Teresa C.; Wiggs, Janey L.; Bex, Peter J.

doi:10.1098/rsif.2014.1118

Cited by 105 publications

(92 citation statements)

References 32 publications

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“…MD was slightly positive in AT1 (no focal defect; 2.0±1.0 dB) and significantly more negative in AT6 (central island; -31.5±1.6 dB vs. al. 17 The low mean PSDs in AT1 (no focal defect) and AT6 (central island) are consistent with the concept that PSD will be low in both cases of minimal VF loss and cases of diffuse VF loss (where VF sensitivities at particular points in the VF testing field become harder to differentiate from surrounding points because of the globally depressed VF sensitivities).…”

Section: Section 32 Visual Field Characteristicssupporting

confidence: 56%

Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic

Cai

Elze

Bex

et al. 2016

Current Eye Research

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Purpose: To assess the clinical validity of visual field (VF) archetypal analysis, a previously developed machine learning method for decomposing any Humphrey VF (24‒2) into a weighted sum of clinically recognizable VF loss patterns. Materials and Methods: For each of 16 previously identified VF loss patterns (“archetypes,” denoted AT1 through AT16), we screened 30,995 reliable VFs to select 10–20 representative patients whose VFs had the highest decomposition coefficients for each archetype. VF global indices and patient ocular and demographic features were extracted retrospectively. Based on resemblances between VF archetypes and clinically observed VF patterns, hypotheses were generated for associations between certain VF archetypes and clinical features, such as an association between AT6 (central island, representing severe VF loss) and large cup-to-disk ratio (CDR). Distributions of the selected clinical features were compared between representative eyes of certain archetypes and all other eyes using the two-tailed t-test or Fisher exact test. Results: 243 eyes from 243 patients were included, representative of AT1 through AT16. CDR was more often ≥ 0.7 among eyes representative of AT6 (central island; p = 0.002), AT10 (inferior arcuate defect; p = 0.048), AT14 (superior paracentral defect; p = 0.016), and AT16 (inferior paracentral defect; p = 0.016) than other eyes. CDR was more often < 0.7 among eyes representative of AT1 (no focal defect; p < 0.001) and AT2 (superior defect; p = 0.027), which was also associated with ptosis (p < 0.001). AT12 (temporal hemianopia) was associated with history of stroke (p = 0.022). AT11 (concentric peripheral defect) trended toward association with trial lens correction > 6D (p = 0.069). Conclusions: Shared clinical features between computationally derived VF archetypes and clinically observed VF patterns support the clinical validity of VF archetypal analysis.

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Section: Section 32 Visual Field Characteristicssupporting

confidence: 56%

Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic

Cai

Elze

Bex

et al. 2016

Current Eye Research

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“…18 The DD-IVFs are calculated at locations with horizontal coordinates of -57°to 57°with a step size of 6°and vertical coordinates the same as in the commonly used 24-2 test pattern. 19 and its recoded binary version included in the current simulation.…”

Section: Binocular Field Simulationmentioning

confidence: 99%

“…Using this technique, DD-IVFs were simulated using 12 out of the 17 archetypes identified in a previous study. 19 Archetypes 7,11,12,15, and 17 identified in their article were excluded for various reasons. Archetype 7 was excluded because of its similarity to archetype 13.…”

Section: Glaucomatous Archetypesmentioning

confidence: 99%

“…This dichotomizing judgment was applied to all 12 archetypes based on both expert knowledge of glaucoma vision loss and the color-coding values in Figure 6 of the study. 19 The coordinates of the center of blind spot were assumed at 15°temporal and 3°below the horizontal meridian. Although a blind spot is not a glaucomatous defect, it leads to functional IVF defects when interacting with glaucomatous defects in the other eye.…”

Section: Glaucomatous Archetypesmentioning

confidence: 99%

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A Depth-Dependent Integrated VF Simulation for Analysis and Visualization of Glaucomatous VF Defects

Liu

McKendrick

Ma-Wyatt

et al. 2020

Trans. Vis. Sci. Tech.

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Citation: Liu P, McKendrick A, Ma-Wyatt A, Turpin A. A depth-dependent integrated VF simulation for analysis and visualization of glaucomatous VF defects. Trans Vis Sci Tech. 2020;9(3):8, https://doi.org/10.1167/tvst.9.3.8Purpose: Visual fields (VF) are measured monocularly at a single depth, yet real-life activities require people to interact with objects binocularly at multiple depths. To better characterize visual functioning in clinical vision conditions such as glaucoma, analyzing visual impairment in a depth-dependent fashion is required. We developed a depthdependent integrated VF (DD-IVF) simulation and demonstrated its usefulness by evaluating DD-IVF defects associated with 12 glaucomatous archetypes of 24-2 VF. Methods:The 12 archetypes included typical variants of superior and inferior nasal steps, arcuate and altitudinal defects, temporal wedge, biarcuate, and intact VFs. DD-IVF simulation maps the monocular 24-2 VF archetypes to binocular ones as a function of depth by incorporating three parameters of fixation, object, and interpupillary distances. At each location and depth plane, sensitivities are linearly interpolated from corresponding locations in monocular VF and returned as the higher value of the two. Results:The simulation produced 144 DD-IVFs for multiple depths from combinations of 12 glaucomatous archetypes. The DD-IVFs are included as a Shiny app in the binovisualfields package. The number of impaired locations in the DD-IVFs varied according to the overlap of VF loss between eyes. Conclusions:Our DD-IVF program revealed binocular functional visual defects associated with glaucomatous archetypes of the 24-2 pattern and is designed to do the same for empirically measured VFs. The comparison of identified visual impairments across depths may be informative for future empirical exploration of functional visual impairments in depth in glaucoma and other conditions leading to bilateral VF loss.Translational Relevance: Our DD-IVF program can reveal depth-dependent functional visual defects for clinical vision conditions where 24-2 test patterns are available.

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“…Measurements on such scans are typically related to visual field test locations by the end points of retinal nerve fibre bundle trajectories passing through the RNFL . These bundles form an arcuate pattern that results in some of the common patterns of visual field loss seen in glaucoma . To relate OCT measurements taken at or around the optic nerve head to visual field locations or regions, we require a map that describes this spatial relationship.…”

Section: Relating Oct Measurements To the Visual Fieldmentioning

confidence: 99%

Relating optical coherence tomography to visual fields in glaucoma: structure–function mapping, limitations and future applications

Denniss

Turpin

McKendrick

2019

Clinical and Experimental Optometry

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Combining information from optical coherence tomography (OCT) imaging and visual field testing is useful in the clinical assessment and monitoring of patients with glaucoma. Measurements of retinal nerve fibre layer thickness or neuroretinal rim width taken around the optic nerve head may be related to the visual field using a structure-function map. In this review, the structure-function mapping methods in clinical use are discussed. Typical clinical maps provide a population average, 'one size fits all' representation, but in recent years methods for customising structure-function maps to individual eyes have been developed and these are reviewed here. In the macula, visual field stimuli stimulate photoreceptors for which associated retinal ganglion cells are peripherally displaced. Recently developed methods that relate OCT measurements to visual field test locations in the macula are therefore also reviewed. The use of structure-function maps to relate OCT measurements to localised visual field sensitivity in new applications is also explored. These new applications include the selection of visual field test locations and stimulus intensities based on OCT data, and the formal post-test combination of results across modalities. Such applications promise to exploit the structure-function relationship in glaucoma to improve disease diagnosis and monitoring of progression. Limitations in the validation and use of current structure-function mapping techniques are discussed.

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Patterns of functional vision loss in glaucoma determined with archetypal analysis

Cited by 105 publications

References 32 publications

Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic

Clinical Correlates of Computationally Derived Visual Field Defect Archetypes in Patients from a Glaucoma Clinic

A Depth-Dependent Integrated VF Simulation for Analysis and Visualization of Glaucomatous VF Defects

Relating optical coherence tomography to visual fields in glaucoma: structure–function mapping, limitations and future applications

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