Biomedical subjects

Andrew Turpin

Publications and source records attributed to Andrew Turpin.

8 recordsLinked to original sources

PubMed2006

A comparison of algorithms for calculating glaucoma change probability confidence intervals.

PURPOSE: To evaluate the ability to detect change in standard automated perimetry data using 4 different methods for calculating the glaucoma change probability (GCP). METHODS: A database of stable visual fields, collected within 1 week from 35 glaucoma patients and within 6 months from 15 normal patients, was used to determine confidence intervals for GCP using 4 different methods. The methods classified visual field locations on the basis of either defect or mean threshold, and used test-retest data or baseline-less-follow-up data to determine values for the confidence intervals. The specificity of the 4 methods was measured using 3700 locations artificially generated to simulate stable visual field data. The sensitivity of the methods was measured using 3330 artificially generated locations that decreased in either a linear, curvilinear, or bi-linear fashion by 2, 3, or 4 dB per year on average. RESULTS: Using GCP with confidence intervals built using the methods described in the literature (on the basis of defect and test-retest differences) resulted in a higher specificity than techniques based on mean threshold. However, the mean-based methods were more sensitive at detecting a decrease in a location. Building confidence intervals using the difference between a baseline and the current measurement (baseline-less-follow-up), rather than test-retest differences, also improved the detection of visual field progression. CONCLUSIONS: Stratifying baseline visual field measurements based on defect and eccentricity as described in the literature results in an unusually high specificity: 98% accuracy in classifying the same stable data that generated the 95% confidence intervals, rather than the expected 95% accuracy. By stratifying measurements based on mean threshold, and using baseline-less-follow-up rather than test-retest differences to build 95% confidence intervals, sensitivity is increased by 14.1%. This increase in sensitivity comes with a corresponding 2.2% decrease in specificity.

Adult↗

PubMed2005

Observer-based rather than population-based confidence limits for determining probability of change in visual fields.

Determining confidence intervals on psychophysical thresholds is straight forward if the psychometric function is known. In clinical settings, however, there is only partial information about the psychometric function, hence confidence limits are usually derived from test-retest data collected from many subjects. In this paper, we introduce a computational technique for deriving confidence limits for an individual's endpoint threshold using data typically obtained in a clinical setting, rather than a database of test-retest performance. The technique uses probabilistic analysis of all possible response sequences in a test procedure. We then extend this procedure to allow for levels of typical uncertainty in data measurement.

Algorithms↗

PubMed2005

Combining perimetric suprathreshold and threshold procedures to reduce measurement variability in areas of visual field loss.

PURPOSE: Several current perimetric test strategies use information from neighboring test locations to seed the procedure. When this initial estimate is close to the true threshold, the algorithms terminate quickly with low error. However, when neighboring thresholds are dissimilar, seeding procedures in this manner results in poor accuracy and repeatability. This study aims to develop a test procedure that avoids assumptions based on neighboring locations yet terminates with an acceptable number of presentations. We explore the utility of a combined screening and threshold approach. METHODS: Our approach [estimation minimizing uncertainty (EMU)] first applies suprathreshold screening and then in those locations that fail the screening, a ZEST procedure commencing with a uniform probability density function (pdf). EMU was compared with full threshold (FT) using computer simulation. Input to the simulation was empirical standard automated perimetry data (FT) from 265 normal subjects and 163 observers with glaucomatous visual field loss. Test performance was assessed using four patient error models designed to represent patients who respond with no errors, typical false-positive errors, typical false-negative errors, and extremely unreliable patients. RESULTS: When patients made typical false-positive errors, EMU required about 20% fewer presentations than FT averaged across the visual field. EMU required a greater number of presentations than FT when false-negative errors were made. The percentage of locations misclassified as either normal (defined as the thresholds greater than the lower 95% confidence limit of age-corrected norms) or abnormal by EMU was lower than for FT. Point-wise analysis demonstrated that in the presence of false-positive errors, the average error and SD of error of thresholds returned by EMU were reduced compared with FT. CONCLUSIONS: EMU enabled accurate estimates of threshold for situations in which neighboring locations are a poor predictor of true threshold. Combining suprathreshold and threshold strategies enables an acceptable number of total visual field presentations, while improving the accuracy and repeatability of threshold estimates in regions of abnormal sensitivity.

Computer Simulation↗

PubMed2005

Advantages of terminating Zippy Estimation by Sequential Testing (ZEST) with dynamic criteria for white-on-white perimetry.

PURPOSE: A number of automated perimeters use the Zippy Estimation by Sequential Testing (ZEST) algorithm, which is an adaptive Bayesian method, for determining sensitivity measures. There are two popular rules for deciding when to terminate Bayesian procedures: (1) after a fixed number of presentations; or (2) when the probability density function (pdf) over all thresholds modified by the procedure becomes sufficiently narrow (a dynamic termination criterion). It has recently been argued that fixed termination criteria perform equally as well as dynamic criteria when applied in a fashion typical of laboratory-based visual psychophysics. Perimetry, however, has specific requirements; the tests must be very short, there is a wide range of possible sensitivities, and erroneous responses from the patient must be tolerated. This study used computer simulation to compare fixed and dynamic termination criteria for the ZEST algorithm using conditions typical of white-on-white perimetry. METHODS: Eight ZEST procedures were compared using the following termination criteria: fixed termination after 4, 5, 6, 7, and 8 presentations; dynamic termination when the standard deviation of the pdf was 1 dB, 1.5 dB, and 2 dB. Four patient error models were used: ideal, typical false-positive, typical false-negative, and unreliable patients. We also ran a version of ZEST that set the likelihood function exactly equal to the patient's frequency of seeing curve. RESULTS: The mean absolute error and standard deviation of error in threshold measurement was higher for the fixed termination criteria than for dynamic termination criteria of the same average number of presentations. CONCLUSIONS: The results of our simulations indicate that dynamic procedures have some distinct benefits over fixed termination procedures when a minimum of presentations are required and response errors are made as in a white-on-white perimetric setting. Dynamic termination criteria are at least partially successful in expending more presentations when required to enhance test precision.

Algorithms↗

PubMed2003

Properties of perimetric threshold estimates from full threshold, ZEST, and SITA-like strategies, as determined by computer simulation.

PURPOSE: To investigate the accuracy and precision of threshold estimates returned by two Bayesian perimetric strategies, staircase-QUEST or SQ (a Swedish interactive threshold algorithm [SITA]-like strategy) and ZEST (zippy estimation by sequential testing), and to compare these measures with those of the full-threshold (FT) algorithm. METHODS: A computerized visual field simulation model was developed to compare the performance (accuracy, precision, and number of presentations) of the three algorithms. SQ implemented aspects of the SITA algorithm that are in the public domain. The simulation was tested by using standard automated perimetry (SAP) visual field data from 265 normal subjects and 163 observers with glaucomatous visual field loss and by exploring the effect of response variability and response errors on algorithm performance. RESULTS: SQ was faster than FT or ZEST, with a comparable mean error when simulating field tests on patients. Point-wise analysis revealed similar error and standard deviation of error as a function of threshold for FT and SQ. If the initial estimate of threshold for either procedure was incorrect, the means and standard deviations of the error increased markedly. ZEST produced more accurate thresholds than did the other two strategies when the initial estimate was removed from the true threshold. CONCLUSIONS: When simulated patients made errors, the accuracy and precision of sensitivity estimates were poor when the initial estimate of threshold either overestimated or underestimated the true threshold. This was particularly so for FT and SQ. ZEST demonstrated more consistent error properties than the other two measures.

Algorithms↗

PubMed2002

Spatial and temporal processing of threshold data for detection of progressive glaucomatous visual field loss.

OBJECTIVE: To evaluate the effect of spatial and temporal filtering of threshold visual field data on the ability of pointwise linear regression (PLR) to detect progressive glaucomatous visual field loss. METHODS: Longitudinal visual field data (Full-Threshold Program 30-2 test point pattern) were simulated using a computer model of glaucomatous visual field progression. This approach permitted construction of a "gold standard" because matching visual field data without variability could be generated and analyzed. Four clustered progressive defects were produced, consisting of 2, 3, 9, and 18 locations, respectively, each with progression rates of -1 and -2.5 dB/y. Pointwise linear regression was used to identify progressive test locations (criterion for progression of statistically significant slope of < or =-1 dB/y, P<.05). Each visual field series was analyzed after the following 3 procedures: (1) no filtering (unprocessed data), (2) Gaussian spatial possessing (3 x 3 grid), and (3) temporal processing (2 field moving average). The effect of spatial and temporal processing on PLR discriminatory power for progression detection was quantified by comparison with the gold standard. RESULTS: Spatial processing reduced PLR sensitivity to levels below that achieved for analysis of unprocessed data for small progressive defects (< or =9 locations) or at the low true progression rate (-1 dB/y). Under these conditions, spatial processing caused small PLR specificity improvement. Spatial processing only improved PLR sensitivity above unprocessed levels when progressive defects were large and changing rapidly (progression rate of -2.5 dB/y). Temporal processing gave consistent PLR improvement in sensitivity for all defect sizes and true progression rates. Pointwise linear regression sensitivity gain provided by temporal processing allowed progression to be detected 2 to 3 visual fields earlier than for analysis of raw data. Specificity dropped slightly as a result of temporal processing but remained at 89% or above for all conditions studied. CONCLUSIONS: Gaussian spatial processing reduces PLR discriminatory power with low true progression rates or small progressive defect sizes and, therefore, is of limited use for detection of progressive visual field loss. Temporal processing improves the sensitivity of PLR and reduces the number of tests required to detect progressive loss with minimal loss of specificity. CLINICAL RELEVANCE: Image processing techniques can be applied to threshold visual field data to enhance sensitivity or specificity of PLR for the determination of progressive change. This investigation demonstrates that temporal processing may assist with the detection of significant progressive visual field loss with fewer test results than unprocessed data.

Computer Simulation↗

PubMed2002

Development of efficient threshold strategies for frequency doubling technology perimetry using computer simulation.

PURPOSE: To develop new test procedures for frequency-doubling technology (FDT) perimetry that improve performance beyond those currently used. METHODS: Two novel threshold estimation procedures were evaluated: a rapid, efficient binary search technique (REBS) and a maximum-likelihood estimation (ZEST) procedure. A computerized visual field simulation model was developed to determine the accuracy and efficiency of these procedures. This model was constructed using previously derived characteristics of FDT perimetry from both normal observers (n = 506) and those with glaucomatous visual field loss (n = 352). The computer simulation program was used to determine the best parameters for the two new procedures and the effect of variability and response errors on algorithm performance. Comparisons were made to the performance of the modified binary search (MOBS) procedure used in the current commercial implementation of the FDT perimeter. RESULTS: Both the optimized REBS and ZEST procedures approximately halved the time required for FDT threshold testing without loss of accuracy or reproducibility. CONCLUSIONS: With suitable parameter choices, comparable performance was achieved using either ZEST or REBS. Simulation results indicate that accurate thresholds can be measured with an optimized ZEST or REBS procedure in approximately half the time required by traditional estimation methods.

Aged↗

PubMed2002

Performance of efficient test procedures for frequency-doubling technology perimetry in normal and glaucomatous eyes.

PURPOSE: To validate the clinical performance of two new efficient threshold-estimation procedures for frequency-doubling technology (FDT) perimetry in both visually normal individuals and patients with glaucomatous visual field loss. METHODS: Forty-one normal subjects (mean age, 48.3 +/- 11.6 years) and 50 patients with glaucomatous visual field loss (mean age, 72.7 +/- 10.0 years) were tested. Some of these participants were retested within a 3-month period. FDT perimetry was performed on a color monitor driven by a visual-stimulus-generating video board, with stimulus parameters designed to closely mimic those of the commercial FDT test. Visual field sensitivity was measured using three procedures: a modified binary search (MOBS) identical with the one used in the commercial FDT device, a rapid efficient binary search (REBS), and a procedure the uses Bayesian methods (zippy estimation of sequential testing; ZEST). The selection of optimum parameters for REBS and ZEST were based on results from previous simulations. RESULTS: Both ZEST and REBS were 40% to 50% faster than MOBS. All three methods produced similar visual field sensitivity measures, with 95% of the differences occurring between +/-2 dB for normal subjects and +/-3 dB for glaucoma patients. Test-retest performance was similar for all three procedures. CONCLUSIONS: The test time for full-threshold FDT perimetry can be approximately halved, by using either the ZEST or REBS procedure, without affecting the accuracy or reliability of the measurements. These findings in normal subjects and patients with glaucoma provide clinical confirmation of our previous investigations of these test strategies that use computer simulation.

Aged↗