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Assessment Of The Reliability Of Standard Automated Perimetry In Regions Of Glaucomatous Damage.

S. Gardiner, W. Swanson, D. Goren, S. Mansberger, S. Demirel
Published 2014 · Medicine

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PURPOSE Visual field testing uses high-contrast stimuli in areas of severe visual field loss. However, retinal ganglion cells saturate with high-contrast stimuli, suggesting that the probability of detecting perimetric stimuli may not increase indefinitely as contrast increases. Driven by this concept, this study examines the lower limit of perimetric sensitivity for reliable testing by standard automated perimetry. DESIGN Evaluation of a diagnostic test. PARTICIPANTS A total of 34 participants with moderate to severe glaucoma; mean deviation at their last clinic visit averaged -10.90 dB (range, -20.94 to -3.38 dB). A total of 75 of the 136 locations tested had a perimetric sensitivity of ≤ 19 dB. METHODS Frequency-of-seeing curves were constructed at 4 nonadjacent visual field locations by the Method of Constant Stimuli (MOCS), using 35 stimulus presentations at each of 7 contrasts. Locations were chosen a priori and included at least 2 with glaucomatous damage but a sensitivity of ≥ 6 dB. Cumulative Gaussian curves were fit to the data, first assuming a 5% false-negative rate and subsequently allowing the asymptotic maximum response probability to be a free parameter. MAIN OUTCOME MEASURES The strength of the relation (R(2)) between perimetric sensitivity (mean of last 2 clinic visits) and MOCS sensitivity (from the experiment) for all locations with perimetric sensitivity within ± 4 dB of each selected value, at 0.5 dB intervals. RESULTS Bins centered at sensitivities ≥ 19 dB always had R(2) >0.1. All bins centered at sensitivities ≤ 15 dB had R(2) <0.1, an indication that sensitivities are unreliable. No consistent conclusions could be drawn between 15 and 19 dB. At 57 of the 81 locations with perimetric sensitivity <19 dB, including 49 of the 63 locations ≤ 15 dB, the fitted asymptotic maximum response probability was <80%, consistent with the hypothesis of response saturation. At 29 of these locations the asymptotic maximum was <50%, and so contrast sensitivity (50% response rate) is undefined. CONCLUSIONS Clinical visual field testing may be unreliable when visual field locations have sensitivity below approximately 15 to 19 dB because of a reduction in the asymptotic maximum response probability. Researchers and clinicians may have difficulty detecting worsening sensitivity in these visual field locations, and this difficulty may occur commonly in patients with glaucoma with moderate to severe glaucomatous visual field loss.
This paper references
Series length used during trend analysis affects sensitivity to changes in progression rate in the ocular hypertension treatment study.
S. Gardiner (2013)
Variability components of standard automated perimetry and frequency-doubling technology perimetry.
P. Spry (2001)
The original Michaelis constant: translation of the 1913 Michaelis-Menten paper.
L. Michaelis (2011)
Repeatability of automated perimetry: a comparison between standard automated perimetry with stimulus size III and V, matrix, and motion perimetry.
M. Wall (2009)
Response variability in the visual field: comparison of optic neuritis, glaucoma, ocular hypertension, and normal eyes.
D. Henson (2000)
A new generation of algorithms for computerized threshold perimetry, SITA.
B. Bengtsson (1997)
Ocular Hypertension Treatment Study Group. Confirmation of visual field abnormalities in the Ocular Hypertension Treatment Study
JL Keltner (2000)
Test-retest variability of frequency-doubling perimetry and conventional perimetry in glaucoma patients and normal subjects.
B. Chauhan (1999)
The Open Perimetry Interface: an enabling tool for clinical visual psychophysics.
A. Turpin (2012)
Threshold variability using different Goldmann stimulus sizes
L. B. Gilpin (1990)
Structural and functional abnormalities of retinal ganglion cells measured in vivo at the onset of optic nerve head surface change in experimental glaucoma.
B. Fortune (2012)
Responses of primate retinal ganglion cells to perimetric stimuli.
W. Swanson (2011)
Classification of visual field abnormalities in the ocular hypertension treatment study.
J. Keltner (2003)
F. Hegelmaier: On memory for the length of a line
D. Laming (1992)
The effective dynamic ranges of standard automated perimetry sizes III and V and motion and matrix perimetry.
M. Wall (2010)
Longitudinal data analysis using generalized linear models
K. Liang (1986)
Con fi rmation of visual fi eld abnormalities in the Ocular Hypertension Treatment Study
JL Keltner (2000)
Frequency of testing for detecting visual field progression
S. Gardiner (2002)
Reconstruction of the electrical responses of turtle cones to flashes and steps of light
D. Baylor (1974)
Peripheral Refraction Profiles in Subjects with Low Foveal Refractive Errors
Juan Tabernero (2011)
Development and evaluation of a contrast sensitivity perimetry test for patients with glaucoma.
A. Hot (2008)
Author response: On alternative methods for measuring visual field decay: Tobit linear regression.
J. Caprioli (2012)
Confirmation of visual field abnormalities in the Ocular Hypertension Treatment Study. Ocular Hypertension Treatment Study Group.
J. Keltner (2000)
A method to measure and predict rates of regional visual field decay in glaucoma.
J. Caprioli (2011)
Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma.
P. Artes (2005)
Linking structure and function in glaucoma
Samantha McGinnigle
Test-Retest Variability in Structural and Functional Parameters of Glaucoma Damage in the Glaucoma Imaging Longitudinal Study
H. Jampel (2006)
The effect of test variability on the structure–function relationship in early glaucoma
S. Gardiner (2012)
A framework for comparing structural and functional measures of glaucomatous damage
D. Hood (2007)
Reducing noise in suspected glaucomatous visual fields by using a new spatial filter
S. Gardiner (2004)
Intratest variability in conventional and high-pass resolution perimetry.
B. Chauhan (1991)
Development and evaluation of a linear staircase strategy for the measurement of perimetric sensitivity
R. Malik (2006)
Increased scatter of responses as a precursor of visual field changes in glaucoma.
E. Werner (1977)
Practical recommendations for measuring rates of visual field change in glaucoma
B. Chauhan (2008)
On alternative methods for measuring visual field decay: Tobit linear regression.
Richard A. Russell (2011)
Structure-function relations of parasol cells in the normal and glaucomatous primate retina.
A. Weber (2005)
A quantitative description of membrane current and its application to conduction and excitation in nerve
A. Hodgkin (1952)
The Ocular Hypertension Treatment Study: design and baseline description of the participants.
M. O. Gordon (1999)
Intraocular light scattering in age-related cataracts.
P. D. de Waard (1992)
Financial Disclosure(s): The author(s) have no proprietary or commercial interest in any materials
The primate retina contains two types of ganglion cells, with high and low contrast sensitivity.
E. Kaplan (1986)
Test-retest variability in glaucomatous visual fields.
A. Heijl (1989)
Properties of perimetric threshold estimates from full threshold, ZEST, and SITA-like strategies, as determined by computer simulation.
A. Turpin (2003)
Comparison of methods to detect visual field progression in glaucoma .
K. Nouri-Mahdavi (1997)
A two-stage neural spiking model of visual contrast detection in perimetry
S. Gardiner (2008)
Increased scatter of responses as a precursor of visual field changes in glaucoma.
Werner Eb (1977)
Normal variability of static perimetric threshold values across the central visual field.
A. Heijl (1987)
Final revision
Uncertainty explains many aspects of visual contrast detection and discrimination.
D. Pelli (1985)
The original Michaelis constant: translation of the 1913 MichaeliseMenten paper. Biochemistry 2011;50:8264–9
KA Johnson (2011)
The ocular hypertension treatment study.
M. Kass (1994)
Estimating progression of visual field loss in glaucoma.
J. Katz (1997)
Evaluating several sources of variability for standard and SWAP visual fields in glaucoma patients, suspects, and normals.
E. Blumenthal (2003)

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S. Gardiner (2018)
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L. Rountree (2018)
Improving Spatial Resolution and Test Times of Visual Field Testing Using ARREST
A. Turpin (2018)
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W. Swanson (2014)
The Relative Odds of Progressing by Structural and Functional Tests in Glaucoma
Ricardo Y Abe (2016)
Evaluation of a Method for Estimating Retinal Ganglion Cell Counts Using Visual Fields and Optical Coherence Tomography.
A. Raza (2015)
Retest Variability in the Medmont M700 Automated Perimeter
J. G. Pearce (2016)
Predicting Global Test-Retest Variability of Visual Fields in Glaucoma.
E. Choi (2020)
Reducing variability in visual field assessment for glaucoma through filtering that combines structural and functional information.
L. Deng (2014)
Deep Multi-Task Learning for SSVEP Detection and Visual Response Mapping
Hong Jing Khok (2020)
Recent developments in visual field testing for glaucoma
Zhichao Wu (2018)
Management of advanced glaucoma: Characterization and monitoring.
C. G. De Moraes (2016)
Estimating the Usefulness of Humphrey Perimetry Gaze Tracking for Evaluating Structure-Function Relationship in Glaucoma.
Yukako Ishiyama (2015)
Effect of a variability-adjusted algorithm on the efficiency of perimetric testing.
S. Gardiner (2014)
Artificial Intelligence Mapping of Structure to Function in Glaucoma
E. B. Mariottoni (2020)
Comparison of Visual Field Progression Rates Among the High Tension Glaucoma, Primary Angle Closure Glaucoma, and Normal Tension Glaucoma.
Shonraj Ballae Ganeshrao (2019)
Multidimensional Functional and Structural Evaluation Reveals Neuroretinal Impairment in Early Diabetic Retinopathy
K. Joltikov (2017)
An Investigation into the Effect of Increasing Target Size for Visual Sensitivity Measurement in Normals and in Early Glaucoma
Sarah Bishop (2014)
Effective Dynamic Range and Retest Reliability of Dark-Adapted Two-Color Fundus-Controlled Perimetry in Patients With Macular Diseases.
M. Pfau (2017)
Structural Measurements for Monitoring Change in Glaucoma: Comparing Retinal Nerve Fiber Layer Thickness With Minimum Rim Width and Area.
S. Gardiner (2015)
Comparison of Standard Automated Perimetry, Short-Wavelength Automated Perimetry, and Frequency-Doubling Technology Perimetry to Monitor Glaucoma Progression
Rongrong Hu (2016)
Validating the usefulness of sectorwise regression of visual field in the central 10°
Takashi Omoto (2021)
Improving the Structure-Function Relationship in Glaucomatous Visual Fields by Using a Deep Learning-Based Noise Reduction Approach.
R. Asaoka (2020)
Bayesian hierarchical modeling of longitudinal glaucomatous visual fields using a two-stage approach.
S. Bryan (2017)
The Effect of Testing Reliability on Visual Field Sensitivity in Normal Eyes: The Singapore Chinese Eye Study.
Nicholas Y. Q. Tan (2018)
Glaucoma home-monitoring using a tablet-based visual field test (Eyecatcher): An assessment of accuracy and adherence over six months
P. R. Jones (2020)
Effect of Restricting Perimetry Testing Algorithms to Reliable Sensitivities on Test-Retest Variability
S. Gardiner (2016)
OCT Circle Scans Can Be Used to Study Many Eyes with Advanced Glaucoma.
S. Lee (2019)
Assessing the GOANNA Visual Field Algorithm Using Artificial Scotoma Generation on Human Observers
L. Chong (2016)
Measurement precision in a series of visual fields acquired by the standard and fast versions of the Swedish interactive thresholding algorithm: analysis of large-scale data from clinics.
L. Saunders (2015)
Equating spatial summation in visual field testing reveals greater loss in optic nerve disease
M. Kalloniatis (2016)
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