Detecting Visual Field Progression in Glaucoma – Using the Right Tools for the Job

2013 ◽  
Vol 07 (01) ◽  
pp. 20 ◽  
Author(s):  
Luke J Saunders ◽  
Richard A Russell ◽  
David P Crabb ◽  
◽  
◽  
...  
Keyword(s):  
Visual Field ◽  
Visual Fields ◽  
Field Measurements ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Visual Disability ◽  
New Research ◽  
The Right ◽  
Over Time

Monitoring disease progression is at the centre of managing a patient with glaucoma. This article focuses specifically on how visual field measurements from standard automated perimetry (SAP) can be monitored over time. Various options for analysis on the Humphrey and Octopus perimeters are discussed, from summary indices to event and trend-based analyses; their respective merits and flaws evaluated. It is strongly recommended that quantitative analysis methods and software are used in assessing progression, as variability in threshold measurements makes detecting true deterioration non-trivial. Recommendations on the frequency of visual fields that should be taken per year are also discussed. The article concludes by putting the spotlight on new research being undertaken to improve the methods of measuring and predicting progression, as well as relating visual fields to patient visual disability and quality of life.

Detecting Visual Field Progression in Glaucoma—Using the Right Tools for the Job

2014 ◽  
Vol 07 (01) ◽  
pp. 32
Author(s):  
Luke J Saunders ◽  
Richard A Russell ◽  
David P Crabb ◽  
◽  
◽  
...  
Keyword(s):  
Visual Field ◽  
Visual Fields ◽  
Field Measurements ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Visual Disability ◽  
New Research ◽  
The Right ◽  
Over Time

Monitoring disease progression is at the centre of managing a patient with glaucoma. This article focuses specifically on how visual field measurements from standard automated perimetry (SAP) can be monitored over time. Various options for analysis on the Humphrey and Octopus perimeters are discussed, from summary indices to event and trend-based analyses, and their respective merits and flaws are evaluated. It is strongly recommended that quantitative analysis methods and software are used in assessing progression, as variability in threshold measurements makes detecting true deterioration non-trivial. Recommendations on the frequency of visual fields that should be taken per year are also discussed. The article concludes by putting the spotlight on new research being undertaken to improve the methods of measuring and predicting progression, as well as relating visual fields to patient visual disability and quality of life.

scholarly journals Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Samuel I. Berchuck ◽  
Sayan Mukherjee ◽  
Felipe A. Medeiros
Keyword(s):  
Visual Field ◽  
Learning Algorithm ◽  
Visual Fields ◽  
Visual Field Loss ◽  
Absolute Error ◽  
Rate Of Change ◽  
Mean Deviation ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Deep Learning Algorithm

AbstractIn this manuscript we develop a deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma. A generalized variational auto-encoder (VAE) was trained to learn a low-dimensional representation of standard automated perimetry (SAP) visual fields using 29,161 fields from 3,832 patients. The VAE was trained on a 90% sample of the data, with randomization at the patient level. Using the remaining 10%, rates of progression and predictions were generated, with comparisons to SAP mean deviation (MD) rates and point-wise (PW) regression predictions, respectively. The longitudinal rate of change through the VAE latent space (e.g., with eight dimensions) detected a significantly higher proportion of progression than MD at two (25% vs. 9%) and four (35% vs 15%) years from baseline. Early on, VAE improved prediction over PW, with significantly smaller mean absolute error in predicting the 4th, 6th and 8th visits from the first three (e.g., visit eight: VAE8: 5.14 dB vs. PW: 8.07 dB; P < 0.001). A deep VAE can be used for assessing both rates and trajectories of progression in glaucoma, with the additional benefit of being a generative technique capable of predicting future patterns of visual field damage.

Compass fundus automated perimetry

2018 ◽  
Vol 28 (5) ◽  
pp. 481-490 ◽  
Author(s):  
Paolo Fogagnolo ◽  
Maurizio Digiuni ◽  
Giovanni Montesano ◽  
Chiara Rui ◽  
Marco Morales ◽  
...  
Keyword(s):  
Visual Field ◽  
Visual Fields ◽  
Field Testing ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Gaze Tracking ◽  
Intrinsic Factors ◽  
Global Indices ◽  
Humphrey Field Analyzer ◽  
The Impact

Background: Compass (CenterVue, Padova, Italy) is a fundus automated perimeter which has been introduced in the clinical practice for glaucoma management in 2014. The aim of the article is to review Compass literature, comparing its performances against Humphrey Field Analyzer (Zeiss Humphrey Systems, Dublin, CA, USA). Results: Analyses on both normal and glaucoma subjects agree on the fact that Humphrey Field Analyzer and Compass are interchangeable, as the difference of their global indices is largely inferior than test -retest variability for Humphrey Field Analyzer. Compass also enables interesting opportunities for the assessment of morphology, and the integration between morphology and function on the same device. Conclusion: Visual field testing by standard automated perimetry is limited by a series of intrinsic factors related to the psychophysical nature of the examination; recent papers suggest that gaze tracking is closely related to visual field reliability. Compass, thanks to a retinal tracker and to the active dislocation of stimuli to compensate for eye movements, is able to provide visual fields unaffected by fixation instability. Also, the instrument is a true colour, confocal retinoscope and obtains high-quality 60° × 60° photos of the central retina and stereo-photos details of the optic nerve. Overlapping the image of the retina to field sensitivity may be useful in ascertaining the impact of comorbidities. In addition, the recent introduction of stereoscopic photography may be very useful for better clinical examination.

scholarly journals Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder

2019 ◽  
Author(s):  
Samuel I. Berchuck ◽  
Sayan Mukherjee ◽  
Felipe A. Medeiros
Keyword(s):  
Visual Field ◽  
Learning Algorithm ◽  
Visual Fields ◽  
Visual Field Loss ◽  
Ordinary Least Squares ◽  
Rate Of Change ◽  
Feature Representation ◽  
Mean Deviation ◽  
Automated Perimetry ◽  
Standard Automated Perimetry

ABSTRACTPurposeTo develop a novel deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma.DesignProspective observational cohort.MethodsA variational auto-encoder (VAE) was trained to learn a low-dimensional feature representation of standard automated perimetry (SAP) visual fields using 29,161 fields from 3,832 patients. The VAE was trained on a 90% sample of the data, with randomization at the patient level. Using the remaining 10%, rates of progression and predictions were generated, with comparisons to SAP mean deviation (MD) rates and point-wise (PW) regression predictions, respectively. From the VAE, rates were calculated using the average of slopes across latent features from ordinary least squares (OLS) regression and trajectories of the features were used to generate predictions.ResultsThe longitudinal rate of change through the VAE latent space (e.g., with eight dimensions) detected a significantly higher proportion of progression than MD at two (19% vs. 6%) and four (40% vs 14%) years from baseline. Early on, VAE improved prediction over PW, with significantly smaller mean absolute error in predicting the 4th, 6th and 8th visits from the first three (e.g., visit eight: VAE8: 4.06 dB vs. PW: 6.06 dB; P<0.001).ConclusionA deep VAE can be used for assessing both rates and trajectories of progression in glaucoma, with the additional benefit of being a generative technique capable of predicting future patterns of visual field damage in the disease.

scholarly journals Global Glaucoma Staging System (GGSS): A New Method to Simultaneously Assess the Severity of Both Functional and Structural Damage in Glaucoma

2021 ◽  
Vol 10 (19) ◽  
pp. 4414
Author(s):  
Paolo Brusini
Keyword(s):  
Visual Field ◽  
Structural Damage ◽  
Open Angle Glaucoma ◽  
Visual Fields ◽  
Staging System ◽  
Normal Subjects ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Fiber Layer ◽  
Spectral Domain Oct

Background: The classification of damage in glaucoma is usually based either on visual field or optical coherent tomography (OCT) assessment. No currently available method is able to simultaneously categorize functional and structural damage. Material and Methods: In this study, 283 patients with chronic open-angle glaucoma (OAG) at different stages and 67 healthy subjects were tested with both standard automated perimetry and spectral domain OCT for retinal nerve fiber layer (RNFL) assessment. The visual field data were classified using the Glaucoma Staging System 2, whereas OCT results were processed with the OCT Glaucoma Staging System. These data were used to create a new staging system (global glaucoma staging system, GGSS), in which the severity of visual field and RNFL damage is reported on the Y and X axis, respectively. The GGSS was tested in a different sample of 147 patients with manifest OAG, 56 with preperimetric glaucoma and 43 normal subjects. A six-stage clinical classification, based on the analysis of visual fields and optic disc appearance, was used as gold standard. Results: The GGSS was able to correctly classify in the same stage or within the immediately adjacent stages 145 cases on 147 (98.6%). Fifty-four preperimetric cases (96.4%) were classified as borderline or abnormal (Stage 1 or 2). Here, 41 normal eyes out of 43 were correctly classified as Stage 0, with a specificity of 95.3%. Conclusions: Preliminary results from this study are encouraging and suggest that the new GGSS is able to provide information concerning the severity of structural and functional damage in an integrated manner.

scholarly journals Association between visual field damage and corneal structural parameters

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexandru Lavric ◽  
Valentin Popa ◽  
Hidenori Takahashi ◽  
Rossen M. Hazarbassanov ◽  
Siamak Yousefi
Keyword(s):  
Machine Learning ◽  
Visual Field ◽  
Structural Parameters ◽  
Corneal Thickness ◽  
Anterior Segment ◽  
Mean Deviation ◽  
Automated Perimetry ◽  
Standard Automated Perimetry ◽  
Visual Field Damage ◽  
Corneal Shape

AbstractThe main goal of this study is to identify the association between corneal shape, elevation, and thickness parameters and visual field damage using machine learning. A total of 676 eyes from 568 patients from the Jichi Medical University in Japan were included in this study. Corneal topography, pachymetry, and elevation images were obtained using anterior segment optical coherence tomography (OCT) and visual field tests were collected using standard automated perimetry with 24-2 Swedish Interactive Threshold Algorithm. The association between corneal structural parameters and visual field damage was investigated using machine learning and evaluated through tenfold cross-validation of the area under the receiver operating characteristic curves (AUC). The average mean deviation was − 8.0 dB and the average central corneal thickness (CCT) was 513.1 µm. Using ensemble machine learning bagged trees classifiers, we detected visual field abnormality from corneal parameters with an AUC of 0.83. Using a tree-based machine learning classifier, we detected four visual field severity levels from corneal parameters with an AUC of 0.74. Although CCT and corneal hysteresis have long been accepted as predictors of glaucoma development and future visual field loss, corneal shape and elevation parameters may also predict glaucoma-induced visual functional loss.

On the Relation between Visual Spatial Attention and Visual Field Asymmetries

1992 ◽  
Vol 44 (3) ◽  
pp. 529-555 ◽  
Author(s):  
T. A Mondor ◽  
M.P. Bryden
Keyword(s):  
Visual Field ◽  
Visual Attention ◽  
Visual Fields ◽  
Stimulus Onset ◽  
Right Visual Field ◽  
Structural Factors ◽  
Letter Identification ◽  
Functional Capabilities ◽  
Visual Spatial ◽  
The Right

In the typical visual laterality experiment, words and letters are more rapidly and accurately identified in the right visual field than in the left. However, while such studies usually control fixation, the deployment of visual attention is rarely restricted. The present studies investigated the influence of visual attention on the visual field asymmetries normally observed in single-letter identification and lexical decision tasks. Attention was controlled using a peripheral cue that provided advance knowledge of the location of the forthcoming stimulus. The time period between the onset of the cue and the onset of the stimulus (Stimulus Onset Asynchrony—SOA) was varied, such that the time available for attention to focus upon the location was controlled. At short SO As a right visual field advantage for identifying single letters and for making lexical decisions was apparent. However, at longer SOAs letters and words presented in the two visual fields were identified equally well. It is concluded that visual field advantages arise from an interaction of attentional and structural factors and that the attentional component in visual field asymmetries must be controlled in order to approximate more closely a true assessment of the relative functional capabilities of the right and left cerebral hemispheres.

Distracted Driving and Driving Patterns in Older Drivers With Glaucoma

2021 ◽  
pp. 155982762110428
Author(s):  
Purva Jain ◽  
Jonathan T. Unkart ◽  
Fabio B. Daga ◽  
Linda Hill
Keyword(s):  
Visual Acuity ◽  
Visual Field ◽  
Visual Fields ◽  
Distracted Driving ◽  
Night Vision ◽  
Driving Ability ◽  
Safe Driving ◽  
Ability To Drive ◽  
Acuity Score

Limited research exists examining self-perceived vision and driving ability among individuals with glaucoma, and this study assessed the relationship between glaucoma, visual field, and visual acuity with driving capability. 137 individuals with glaucoma and 75 healthy controls were asked to evaluate self-rated vision, self-perceived driving ability, and self-perceived distracted driving. Visual acuity and visual field measurements were also obtained. Multivariable linear regressions were run to test each visual measure with driving outcomes. The average age was 72.2 years, 57.3% were male, and 72.5% were White. There were significant associations for a one-point increase in visual field and quality of corrected vision (RR = 1.06; 95% CI = 1.03–1.10), day vision (RR = 1.05; 95% CI = 1.03–1.08), night vision (RR = 1.08; 95% CI = 1.05–1.13), visual acuity score and higher quality of corrected of vision (RR = .41; 95% CI = .22-.77), day vision (RR = .39; 95% CI=.22–.71), and night vision (RR = .41; 95% CI = .18–.94); visual acuity score and ability to drive safely compared to other drivers your age (RR = .53; 95% CI = .29–.96). Individuals with poorer visual acuity and visual fields rate their vision and ability to drive lower than those with better vision, and this information will allow clinicians to understand where to target interventions to enhance safe driving practices.

Sign in / Sign up

Export Citation Format

Share Document