Biomedical subjects

David P Crabb

Publications and source records attributed to David P Crabb.

8 recordsLinked to original sources

PubMed2007

Monitoring glaucomatous visual field progression: the effect of a novel spatial filter.

PURPOSE: To assess the impact of a novel visual field spatial filtering technique on the detection of glaucomatous progression. METHODS: One hundred ninety-eight ocular hypertensive (OHT) and 21 control subjects were examined prospectively (1994-2001) with regular full-threshold Humphrey visual field (VF) testing. VF progression was assessed by point-wise linear regression (PLR) of sensitivity/time in Progressor for Windows software modified to include a novel spatial filter. Standard progression criteria (slope > -1 dB/year, P < 0.01) were applied to both "raw" (unfiltered) and "filtered" VF series. Three-omitting confirmatory VF criteria were also applied to unfiltered VF series. Specificity was estimated as the proportion of progressing control subjects and as the proportion of significantly improving subjects (both OHT and control) at the end of the study period. RESULTS: Applying standard PLR, specificity was estimated at 91.8% to 97.5% using unfiltered standard PLR, compared with 93.5% to 98.4% using filtered standard PLR and 95.4% to 99.3% using unfiltered three-omitting PLR. The rate of identified VF progression in the OHT cohort was 32.3% with unfiltered standard PLR, 28.7% with filtered standard PLR, and 18.6% with unfiltered three-omitting PLR. There was no significant difference in time to detected progression between filtered and unfiltered standard PLR. CONCLUSIONS: The use of confirmatory tests resulted in improved specificity using unfiltered data; however, application of the spatial filter resulted in similar specificity but with a higher rate of detected progression. This filter may therefore be useful in the monitoring of glaucomatous progression as it may reduce the dependence on confirmatory testing, although it has yet to be applied to longitudinal SITA data.

Adult↗

PubMed2006

Structure and function in glaucoma: The relationship between a functional visual field map and an anatomic retinal map.

PURPOSE: To examine the relationship between an anatomic map relating the retinal nerve fiber layer (RNFL) distribution to the optic nerve head and a functional map derived from the interpoint correlation of raw sensitivities in visual field (VF) testing. METHODS: Previously, interpoint correlations were generated for all possible pairs of VF test points in a dataset of 98,821 Humphrey VF test results taken from the Moorfields Eye Hospital archive. The relationship between these correlations and the physical distance between the VF test point pairs was evaluated by Pearson's correlation coefficient and multiple regression analysis. The distance between the pairs of VF test points was calculated in two ways. First, the anatomic map was used to estimate the angular distance at the optic nerve head (ONH), between the RNFL bundles corresponding to the VF test points in each pair (ONHd). Second, the retinal distance between pairs of test points was calculated from the Humphrey VF template (RETd). A best-fit model for predicting functional correlation (FC) from ONHd and RETd was constructed and used to formulate a filter incorporating the anatomic-functional correlation data. RESULTS: All scatterplots showed a negative association between interpoint retinal sensitivity correlation values and distance between points: ONHd (R2 = 0.60) and RETd (R2 = 0.33). The raw sensitivity correlation values could be predicted from a multiple regression model using ONHd, RETd, and a combined interaction of ONHd and RETd (R2 = 0.75, P < 0.00001). The construction of a new filter was based on the equation FC = 0.9325 - (0.0029 . ONHd) - (0.0077 . RETd) + (0.0001 . ONHd . RETd). CONCLUSIONS: A good level of association was observed between the strength of correlation between points in the VF and the relative location of those test points in the peripheral retina and in corresponding RNFL bundles at the ONH. These results help to validate the relationship between structure and function and may be of use in the further refinement of physiologically derived VF filters to reduce measurement noise.

Glaucoma, Open-Angle↗

PubMed2006

Measurement variability in Heidelberg Retina Tomograph imaging of neuroretinal rim area.

PURPOSE: To investigate the optimal frequency of imaging during follow-up to detect glaucoma progression by characterizing variability (noise) in neuroretinal rim area (RA) measured by Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Heidelberg, Germany). METHODS: RA noise was estimated from patient data and characterized by fitting theoretical distributions to the observed data. Multilevel regression was used to determine factors that significantly affect noise. Computer simulations of disease progression were performed by adding noise generated from the distribution derived from the observed data to the average rate of loss in RA estimated from longitudinal data. Rates of detection of disease progression were investigated for various progression rates, follow-up periods, and rates of imaging. RESULTS: Noise was not normally distributed and was best characterized by the hyperbolic distribution, which fit averages well while allowing for extreme values. Noise was greatly influenced by image quality, but age did not have a significant effect. Rates of detection improved for more frequent imaging, better quality images, and faster rates of disease progression. CONCLUSIONS: Noise in HRT measurement of RA is well characterized by the hyperbolic distribution. Sensitivity of detection improves with more frequent testing, but if consistently poor-quality images are yielded for a patient, the probability of detection is low. Results from this work could be used to tailor individual follow-up patterns for patients with different rates of RA loss and image quality, especially in a clinical trial setting.

Cross-Sectional Studies↗

PubMed2006

Improving the repeatability of topographic height measurements in confocal scanning laser imaging using maximum-likelihood deconvolution.

PURPOSE: To evaluate maximum likelihood (ML) blind deconvolution as a technique for improving the repeatability of topographic height measurements obtained from scanning laser tomography (Heidelberg Retinal Tomograph [HRT]; Heidelberg Engineering, Heidelberg, Germany). METHODS: ML blind deconvolution is an image-processing technique that estimates the original scene from a degraded image. This technique has been used in confocal scanning laser microscopy to remove "out-of-focus" haze in three-dimensional confocal image stacks. ML blind deconvolution requires no prior estimation of the point-spread function (PSF), as opposed to classic linear deconvolution methods. Instead, the algorithm estimates an initial PSF based on the optical setup of the confocal scanning device and optics of the eye and iteratively proceeds to a solution. The improvement in repeatability of height measurements from mean topography images within scan (intrascan) and between scans (interscan) afforded by ML deconvolution was evaluated in a test-retest series of HRT images from 40 ocular hypertensive and glaucomatous patients with varying degrees of media opacity. RESULTS: There was an improvement in intrascan repeatability in 38 out of the 40 mean topography images (median improvement 2.5 microm, inter-quartile range 2.19, P < 0.001), and an improvement in interscan repeatability in 33 of the 40 mean topographies (median improvement, 1.0 microm, interquartile range 3.49, P < 0.001). There was a positive association between the magnitude of the improvement in repeatability and the level of mean pixel height standard deviation (MPHSD), intrascan (P = 0.004) and interscan (P = 0.002). CONCLUSIONS: ML blind deconvolution algorithm improves the repeatability of topographic height measurements from the HRT. This improvement was greater in patients with poorer quality images.

Algorithms↗

PubMed2005

A new statistical approach for quantifying change in series of retinal and optic nerve head topography images.

PURPOSE: To describe and evaluate new statistical techniques for detecting topographic changes in series of retinal and optic nerve head images acquired by scanning laser tomography (Heidelberg Retinal Tomograph [HRT]; Heidelberg Engineering, Heidelberg, Germany). METHODS: Proven quantitative techniques, collectively referred to as statistic image mapping (SIM), are widely used in neuroimaging. These techniques are applied to HRT images. A pixel-by-pixel analysis of topographic height over time yields a statistic image that is generated by using permutation testing, derives significance limits for change wholly from the patient's own data, and removes the need for reference data sets. These novel techniques were compared to the Topographic Change Analysis (TCA super-pixel analysis) available in the current HRT software, by means of an extensive series of computer experiments. The SIM and TCA techniques were further tested and compared to linear regression of rim area (RA) against time, in real longitudinal HRT series of eyes of 20 normal subjects and 30 ocular hypertensive (OHT) patients that were known to have converted to glaucoma, on the basis of visual field criteria. RESULTS: Computer simulation indicated that SIM has better diagnostic precision at detecting change. In the real longitudinal series, SIM flagged false-positive structural progression in two (10%) of normal subjects, whereas TCA identified three (15%), and linear regression of RA against time identified two (10%). SIM identified 22 (73%) of the OHT converters as having structural progression, whereas the TCA and linear regression of RA against time each identified 16 (53%) over the course of the follow-up. CONCLUSIONS: SIM has better diagnostic precision in detecting change in series of HRT images when compared to current quantitative techniques. The clinical utility of these techniques will be established on further longitudinal data sets.

Adult↗

PubMed2004

Integrated visual fields: a new approach to measuring the binocular field of view and visual disability.

BACKGROUND: We have developed a method of quantifying the central binocular visual field by merging results from monocular fields (Integrated visual field). This study aims to compare the new measure with the binocular Esterman visual field test in identifying patients with self-reported visual disability. METHODS: Forty-eight patients with glaucoma each recorded Humphrey 24-2 fields for both eyes and an Esterman on the same day, and each completed a binary forced-choice questionnaire relating to perceived visual disability. Computer software merged sensitivity values from monocular fields to generate an integrated visual field and a related score of the number of defects at the <10 dB and <20 dB level. Receiver operating characteristic (ROC) analysis was used to compare the integrated visual field score and the Esterman disability score with individual responses to the questions on perceived difficulty with visual tasks. RESULTS: Comparison of areas under ROC curves revealed that a score based on the integrated visual field was generally better (median area: 0.79) than Esterman scores (median area: 0.70) in classifying patients with or without a self-reported perceived difficulty with visual tasks. CONCLUSIONS: The integrated visual field offers a rapid assessment of a glaucoma patient's binocular visual field without extra perimetric testing. As compared to an actual binocular field test (Esterman), the integrated visual field provides a better prediction of a glaucoma patient's perceived inability to perform certain visual tasks.

Adult↗

PubMed2004

Reducing noise in suspected glaucomatous visual fields by using a new spatial filter.

Visual field testing with automated perimetry is hampered by the amount of noise present in the readings. Here, we derive a physiologically accurate spatial filter to be applied to the data after patient examination. The filter was tested by a Virtual Eye computer simulation. By simulating series of stable fields it was shown that specificity of determining visual field changes was improved; while simulating progressing fields (based on a map of the optic nerve head) it was shown that sensitivity was also improved. The filter appears to reduce the noise in glaucomatous visual field data and may be clinically useful.

Computer Simulation↗

PubMed2002

Examination of different pointwise linear regression methods for determining visual field progression.

PURPOSE: To compare the specificity and sensitivity of several different methods for using pointwise linear regression (PLR) to detect progression (deterioration) in visual fields. METHODS: First, theoretical results were derived to predict which of the considered PLR methods would be the most specific and hence the least sensitive. Then, a "Virtual Eye" simulation model was developed that simulates series of sensitivity readings for a point over time. The model adds normally distributed noise (estimated from published results) to the sensitivity at each point to produce a series of fields to be analyzed using each method. Stable and deteriorating eyes were simulated, with the latter defined to have a noise-free loss of 2 dB/y at a significant cluster of points over the series. RESULTS: The most sensitive method tested was to flag a visual field as progressing if it had a point that exhibited a statistically significant slope (at the 1% level) of at least -1 dB/y in the sensitivity. The most specific was a new "Three-Omitting" method that is being proposed, using two confirmation fields in a novel way. Current methods of using confirmation fields to verify a significant slope incorrectly flagged up to twice as many stable eyes as having progressing fields as did our new method. CONCLUSIONS: Using the new proposed PLR method is recommended in preference to current PLR methods in any applications when a high degree of specificity is the main priority.

Computer Simulation↗