Repeatability of automated perimetry: a comparison between standard automated perimetry with stimulus size III and V, matrix, and motion perimetry.

PURPOSE Standard automated perimetry (SAP) shows a marked increase in variability in damaged areas of the visual field. This study was conducted to test the hypothesis that larger stimuli are associated with more uniform variability, by investigating the retest variability of four perimetry tests: standard automated perimetry size III (SAP III), with the SITA standard strategy; SAP size V (SAP V), with the full-threshold strategy; Matrix (FDT II), and Motion perimetry. METHODS One eye each of 120 patients with glaucoma was examined on the same day with these four perimetric tests and retested 1 to 8 weeks later. The decibel scales were adjusted to make the test's scales numerically similar. Retest variability was examined by establishing the distributions of retest threshold estimates, for each threshold level observed at the first test. The 5th and 95th percentiles of the retest distribution were used as point-wise limits of retest variability. Regression analyses were performed to quantify the relationship between visual field sensitivity and variability. RESULTS With SAP III, the retest variability increased substantially with reducing sensitivity. Corresponding increases with SAP V, Matrix, and Motion perimetry were considerably smaller or absent. With SAP III, sensitivity explained 22% of the retest variability (r(2)), whereas corresponding data for SAP V, Matrix, and Motion perimetry were 12%, 2%, and 2%, respectively. CONCLUSIONS Variability of Matrix and Motion perimetry does not increase as substantially as that of SAP III in damaged areas of the visual field. Increased sampling with the larger stimuli of these techniques is the likely explanation for this finding. These properties may make these stimuli excellent candidates for early detection of visual field progression.

[1]  B C Chauhan,et al.  The psychometric function and reaction times of automated perimetry in normal and abnormal areas of the visual field in patients with glaucoma. , 1996, Investigative ophthalmology & visual science.

[2]  C. Richter.  Automatic Perimetry in Glaucoma , 1986 .

[3]  Chris A. Johnson,et al.  Frequency-doubling technology perimetry. , 2003, Ophthalmology clinics of North America.

[4]  K. Woodward,et al.  The effect of attention on conventional automated perimetry and luminance size threshold perimetry. , 2004, Investigative ophthalmology & visual science.

[5]  Chris A Johnson,et al.  Classification of visual field abnormalities in the ocular hypertension treatment study. , 2000, Archives of ophthalmology.

[6]  Chris A. Johnson,et al.  Characteristics of the normative database for the Humphrey matrix perimeter. , 2005, Investigative ophthalmology & visual science.

[7]  F. Fankhauser,et al.  Differential light threshold in automated static perimetry. Factors influencing short-term fluctuation. , 1984, Archives of ophthalmology.

[8]  M Schulzer,et al.  Errors in the diagnosis of visual field progression in normal-tension glaucoma. , 1994, Ophthalmology.

[9]  Contestabile Maria Teresa,et al.  The Influence of Learning Effect on Frequency Doubling Technology Perimetry (Matrix) , 2007 .

[10]  Paul H Artes,et al.  Threshold and variability properties of matrix frequency-doubling technology and standard automated perimetry in glaucoma. , 2005, Investigative ophthalmology & visual science.

[11]  M. Wall,et al.  Effect of instructions on conventional automated perimetry. , 2000, Investigative ophthalmology & visual science.

[12]  J L Keltner,et al.  Long- and short-term variability of automated perimetry results in patients with optic neuritis and healthy subjects. , 1998, Archives of ophthalmology.

[13]  M W Levine.  Variability of responses to sinusoidal modulation. , 1994, Visual neuroscience.

[14]  M. Wall,et al.  Random dot motion perimetry in patients with glaucoma and in normal subjects. , 1995, American journal of ophthalmology.

[15]  J M Wild,et al.  Long‐term follow‐up of baseline learning and fatigue effects in the automated perimetry of glaucoma and ocular hypertensive patients , 1991, Acta ophthalmologica.

[16]  B Petrig,et al.  Variability of automated visual fields in clinically stable glaucoma patients. , 1989, Investigative ophthalmology & visual science.

[17]  E. Montgomery,et al.  Using motion perimetry to detect visual field defects in patients with idiopathic intracranial hypertension , 1995, Neurology.

[18]  William H Swanson,et al.  Evaluation of a Two-Stage Neural Model of Glaucomatous Defect: An Approach to Reduce Test–Retest Variability , 2006, Optometry and vision science : official publication of the American Academy of Optometry.

[19]  A. Perdicchi,et al.  The influence of learning effect on frequency doubling technology perimetry (Matrix). , 2007, Journal of glaucoma.

[20]  H Bebie,et al.  STATIC PERIMETRY: ACCURACY AND FLUCTUATIONS , 1976, Acta ophthalmologica.

[21]  H. J. Wyatt,et al.  Variability of visual field measurements is correlated with the gradient of visual sensitivity , 2007, Vision Research.

[22]  J Flammer,et al.  Differential light threshold. Short- and long-term fluctuation in patients with glaucoma, normal controls, and patients with suspected glaucoma. , 1984, Archives of ophthalmology.

[23]  J. Movshon,et al.  The statistical reliability of signals in single neurons in cat and monkey visual cortex , 1983, Vision Research.

[24]  D. Ferster,et al.  The contribution of noise to contrast invariance of orientation tuning in cat visual cortex. , 2000, Science.

[25]  P. Artes,et al.  Response variability in the visual field: comparison of optic neuritis, glaucoma, ocular hypertension, and normal eyes. , 2000, Investigative ophthalmology & visual science.

[26]  K. Nakayama,et al.  Psychophysical isolation of movement sensitivity by removal of familiar position cues , 1981, Vision Research.

[27]  F. Fitzke,et al.  Scaling the hill of vision: the physiological relationship between light sensitivity and ganglion cell numbers. , 2000, Investigative ophthalmology & visual science.

[28]  K. Purpura,et al.  Response variability in retinal ganglion cells of primates. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[29]  B. Bengtsson,et al.  The effect of perimetric experience in patients with glaucoma. , 1996, Archives of ophthalmology.

[30]  D. Dacey.  Morphology of a small-field bistratified ganglion cell type in the macaque and human retina , 1993, Visual Neuroscience.

[31]  J L Keltner,et al.  Confirmation of visual field abnormalities in the Ocular Hypertension Treatment Study. Ocular Hypertension Treatment Study Group. , 2000, Archives of ophthalmology.

[32]  William H Swanson,et al.  Ganglion Cell Loss and Age-Related Visual Loss: A Cortical Pooling Analysis , 2006, Optometry and vision science : official publication of the American Academy of Optometry.

[33]  J. Piltz,et al.  Test-retest variability in glaucomatous visual fields. , 1990, American journal of ophthalmology.

[34]  M. Kass.  The ocular hypertension treatment study. , 1994, Journal of glaucoma.

[35]  B. Chauhan,et al.  Variability in patients with glaucomatous visual field damage is reduced using size V stimuli. , 1997, Investigative ophthalmology & visual science.

[36]  J Caprioli,et al.  Long-term fluctuation of the visual field in glaucoma. , 1992, American journal of ophthalmology.

[37]  Yuko Ohno,et al.  Properties of perimetric threshold estimates from Full Threshold, SITA Standard, and SITA Fast strategies. , 2002, Investigative ophthalmology & visual science.

[38]  E. Werner,et al.  Variability of static visual threshold responses in patients with elevated IOPs. , 1982, Archives of ophthalmology.

[39]  Josef Flammer,et al.  The learning and fatigue effect in automated perimetry , 2004, Graefe's Archive for Clinical and Experimental Ophthalmology.