Visual Field Data Research Articles

Visual saliency and potential field data enhancements: Where is your attention drawn?

Interpretation of gravity and magnetic data for exploration applications may be based on pattern recognition in which geophysical signatures of geologic features associated with localized characteristics are sought within data. A crucial control on what comprises noticeable and comparable characteristics in a data set is how images displaying those data are enhanced. Interpreters are provided with various image enhancement and display tools to assist their interpretation, although the effectiveness of these tools to improve geologic feature detection is difficult to measure. We addressed this challenge by analyzing how image enhancement methods impact the interpreter’s visual attention when interpreting the data because features that are more salient to the human visual system are more likely to be noticed. We used geologic target-spotting exercises within images generated from magnetic data to assess commonly used magnetic data visualization methods for their visual saliency. Our aim was achieved in two stages. In the first stage, we identified a suitable saliency detection algorithm that can computationally predict visual attention of magnetic data interpreters. The computer vision community has developed various image saliency detection algorithms, and we assessed which algorithm best matches the interpreter’s data observation patterns for magnetic target-spotting exercises. In the second stage, we applied this saliency detection algorithm to understand potential visual biases for commonly used magnetic data enhancement methods. We developed a guide to choosing image enhancement methods, based on saliency maps that minimize unintended visual biases in magnetic data interpretation, and some recommendations for identifying exploration targets in different types of magnetic data.

Reducing variability in visual field assessment for glaucoma through filtering that combines structural and functional information.

To reduce variability and improve measurements of true change signal in visual field (VF) assessments through the use of filters that combine functional and structural test results. Humphrey VF data (Swedish Interactive Thresholding Algorithm [SITA] Standard, 24-2) and confocal scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]) data from 1057 eyes of 637 participants were used to derive a filter. Another dataset, consisting of VF and HRT data from 112 eyes of 62 participants each with ≥5 visits, was used to test the filter. At each VF location per eye, the trend over time was modeled by a linear model (LM), and a nonlinear model (NLM), using filtered or unfiltered data, but with the last visit excluded. The SD of residuals from the trends, and prediction errors (PE) for the last visit were compared between filtered and unfiltered data. The filter was reconstructed and analyses were repeated after truncating VF data so that thresholds < 19 dB were replaced by 19 dB to reduce noise. The SD of the residuals at all 52 VF locations for all analyses was reduced by filtering (P < 0.001). The PE was reduced by filtering at 43 and 47 VF locations (P < 0.05) for LM analyses on observed and truncated data, and all 52 VF locations (P < 0.05) for both NLM analyses. Truncating data before filtering reduced variability (P < 0.01) at 41 and 40 VF locations for LM and NLM analyses. Filtering can reduce variability about trends in longitudinal sequences of VF data, and improves the accuracy of predicting the next test result.

Evaluation of Visual Field Progression in Glaucoma

Detection of visual field progression is of critical importance in the management of patients with glaucoma; however, there is no agreed upon set of criteria for the definition of progression. The most commonly utilized method of progression detection in clinical practice may be subjective assessment of serial visual fields. Event-based and trend-based approaches to the analysis of serial visual field data are quite powerful and used in clinical practice and in clinical research. Recent advances in analysis of visual field progression are discussed in this review article.

Evaluation of various machine learning methods to predict vision-related quality of life from visual field data and visual acuity in patients with glaucoma

Background/aimsWe investigated whether it was useful to use machine learning algorithms to predict patients’ vision related quality of life (VRQoL) from visual field (VF) and visual acuity (VA).MethodsVRQoL was surveyed...

A New Index to Monitor Central Visual Field Progression in Glaucoma

The visual field index (VFI) summarizes global visual field (VF) data and was developed to monitor glaucoma progression using 24-2 and 30-2 strategies. We applied similar principles and statistical procedures to develop a new parameter, the central field index (CFI), to monitor 10-2 VF progression. Retrospective cohort. Glaucoma patients with paracentral defects seen on 24-2 perimetry and followed up with at least 5 10-2 VF tests. The CFI was developed by calculating age-corrected defect depth at test points obtained during 10-2 examinations. The sensitivities at these points were scored as percentages similar to the method described for the VFI: 100-[(|total deviation|/age-corrected normal threshold) × 100]. A weighting procedure was applied based on published estimates of the occipital cortical spatial magnification. For validation, we performed mixed linear model testing for the association between CFI rates of change (%/year) and known risk factors for glaucoma progression in a population with established glaucoma and at least 5 10-2 VF tests. To determine whether the CFI was affected by cataract, as is known to occur with mean deviation (MD), we conducted a pilot evaluation comparing rates of CFI change in 3 groups: (1) eyes with cataract, (2) pseudophakic eyes, and (3) eyes in which cataract surgery was performed in the middle of the series. Rates of CFI and MD change. Central field index values were calculated for 176 eyes of 142 patients. The mean rate of CFI change of the entire sample was -1.10%/year (95% confidence interval, -1.03 to -1.16%/year). Elevated intraocular pressure (P<0.001) was associated significantly with faster CFI change, whereas lens status did not influence CFI rates of change (P>0.100) CONCLUSIONS: We developed and validated a new index to monitor central field progression that is minimally affected by the presence or removal of cataract and that correlates significantly with an important risk factor for glaucoma progression. This new index may become useful for glaucoma management, especially when combined with conventional static perimetry strategies.

Learning From Data: Recognizing Glaucomatous Defect Patterns and Detecting Progression From Visual Field Measurements

A hierarchical approach to learn from visual field data was adopted to identify glaucomatous visual field defect patterns and to detect glaucomatous progression. The analysis pipeline included three stages, namely, clustering, glaucoma boundary limit detection, and glaucoma progression detection testing. First, cross-sectional visual field tests collected from each subject were clustered using a mixture of Gaussians and model parameters were estimated using expectation maximization. The visual field clusters were further estimated to recognize glaucomatous visual field defect patterns by decomposing each cluster into several axes. The glaucoma visual field defect patterns along each axis then were identified. To derive a definition of progression, the longitudinal visual fields of stable glaucoma eyes on the abnormal cluster axes were projected and the slope was approximated using linear regression (LR) to determine the confidence limit of each axis. For glaucoma progression detection, the longitudinal visual fields of each eye on the abnormal cluster axes were projected and the slope was approximated by LR. Progression was assigned if the progression rate was greater than the boundary limit of the stable eyes; otherwise, stability was assumed. The proposed method was compared to a recently developed progression detection method and to clinically available glaucoma progression detection software. The clinical accuracy of the proposed pipeline was as good as or better than the currently available methods.

Optimizing Structure–Function Relationship by Maximizing Correspondence Between Glaucomatous Visual Fields and Mathematical Retinal Nerve Fiber Models

To introduce a method to optimize structural retinal nerve fiber layer (RNFL) models based on glaucomatous visual field data and to show how such an optimized model can be used to reduce noise in visual fields while probably preserving clinically important features. Correlation coefficients between age-adjusted deviation values of pairs of visual field test locations were calculated from 103 visual fields of eyes with moderate glaucomatous damage. Distances between those test locations were defined for various parameters of a mathematical RNFL model. Then, the correspondence between the structural and functional data was defined by the spread, or variance, of the correlation coefficients for all distances. The model parameters that minimized this spread constituted the optimized model. To reduce noise in visual fields, the optimized model was used to smooth visual field data according to the RNFL's structure. The resulting fields were compared with visual fields that were smoothed based on the regular testing grid. The optimal parameters for the RNFL model reduced the variance of the correlation coefficients by 78% and were well within the range of parameters previously determined from fundus photographs. Smoothing the visual fields based on the optimized RNFL model strongly reduced noise while keeping important features. Mathematic RNFL models can be optimized based on visual field data, resulting in a strong structure-function relationship. Taking the RNFL's shape, as defined by such an optimized model, into account when smoothing visual fields results in better noise reduction while preserving important details.

Development and Validation of an Improved Neurological Hemifield Test to Identify Chiasmal and Postchiasmal Lesions by Automated Perimetry

To improve the neurological hemifield test (NHT) using visual field data from both eyes to detect and classify visual field loss caused by chiasmal or postchiasmal lesions. Visual field and clinical data for 633 patients were divided into a training set (474 cases) and a validation set (159 cases). Each set had equal numbers of neurological, glaucoma, or glaucoma suspect cases, matched for age and for mean deviation between neurological and glaucoma cases. NHT scores as previously described and a new NHT laterality score were calculated. The ability of these scores to distinguish neurological from other fields was assessed with receiver operating characteristic (ROC) analysis. Three machine classifier algorithms were also evaluated: decision tree, random forest, and least absolute shrinkage and selection operator (LASSO). We also evaluated the ability of NHT to identify the type of neurological field defect (homonymous or bitemporal). The area under the ROC curve (AUC) for the maximum NHT score was 0.92 (confidence interval [CI]: 0.87, 0.97). Using NHT laterality scores from each eye combined with the sum of NHT scores, the AUC improved to 0.93 (CI: 0.88, 0.98). The largest AUC for machine learning algorithms was for the LASSO method (0.96, CI: 0.92, 0.99). The NHT scores identified the type of neurological defect in 96% (158/164) of patients. The new NHT distinguished neurological field defects from those of glaucoma and glaucoma suspects, providing accurate categorization of defect type. Its implementation may identify unsuspected neurological disease in clinical visual field testing.

Robust and Censored Modeling and Prediction of Progression in Glaucomatous Visual Fields

Classic regression is based on certain assumptions that conflict with visual field (VF) data. We investigate and evaluate different regression models and their assumptions in order to determine point-wise VF progression in glaucoma and to better predict future field loss for personalised clinical glaucoma management. Standard automated visual fields of 130 patients with primary glaucoma with a minimum of 6 years of follow-up were included. Sensitivity estimates at each VF location were regressed on time with classical linear and exponential regression models, as well as different variants of these models that take into account censoring and allow for robust fits. These models were compared for the best fit and for their predictive ability. The prediction was evaluated at six measurements (approximately 3 years) ahead using varying numbers of measurements. For fitting the data, the classical uncensored linear regression model had the lowest root mean square error and 95th percentile of the absolute errors. These errors were reduced in all models when increasing the number of measurements used for the prediction of future measurements, with the classical uncensored linear regression model having the lowest values for these errors irrespective of how many measurements were included. All models performed similarly. Despite violation of its assumptions, the classical uncensored linear regression model appeared to provide the best fit for our data. In addition, this model appeared to perform the best when predicting future VFs. However, more advanced regression models exploring any temporal-spatial relationships of glaucomatous progression are needed to reduce prediction errors to clinically meaningful levels.

Use of optical coherence tomography in predicting post-treatment visual outcome in anterior visual pathway meningiomas

PurposeTo determine the prognostic value of pretreatment optical coherence tomography (OCT) measurement of the peripapillary retinal nerve fibre layer (PRNFL) in final visual outcomes of patients with anterior visual pathway...

Extended Endonasal Solo Endoscopic Approach for the Resection of Craniopharyngiomas

Background: Extended endonasal solo endoscopic approach for the non-pituitary lesions of the sellar and suprasellar regions are not new in the field of neurosurgery. Following endoscopic surgical approach of the pituitary adenoma, endoscopic neurosurgeon is eager to develop the skill for non-pituitary sellar &amp; suprasellar lesions. Common sellar &amp; suprasellar lesions are pituitary adenoma, craniopharyngioma, tuberculumselle meningioma and suprasellar germinoma.&#x0D; Objective: Traditional transsphenoidal approach gives exposure to the pituitary fossa, whereas extended approach provides exposure to the optic nerve, chiasm, acom complex and basal frontal lobe ,mammillary body, mid brain and laterally to the cavernous sinuses.&#x0D; Material &amp; method: From November 2007 to March 2012, 12 cases of done by extended endonasal solo endoscopic approach among 12 cases of craniopharyngiomas. Patient’s history, clinical findings, pre-operative and post-operative visual acuity, visual field and radiological data were collected and analyzed. All patients underwent solo endoscopic extended transsphenoidal approach with or without nasoseptal flap technique for closure. Most of the patients were given lumbar drain as a treatment for CSF leak.&#x0D; Result: All patients were of age group of 10 to 60 years. Male were 8 (66.67%), female were 4 (33.33%) in number. Gross total removals were done in 7 cases out of 12 (58.33%) craniopharyngiomas and subtotal removal done in 5 (41.67%) cases. Visual acuity and field of vision were improved in all cases of craniopharyngiomas. One case (8.33%) of craniopharyngioma had prolong period of unconsciousness probably from hypothalamic disturbance. CSF leak developed in 2 (16.67%) cases. Patients with craniopharyngioma were required thyroxin and cortisol for replacement. Permanent diabetes insipidus developed in 5 cases (41.67%). Three patients required permanent CSF diversion via a ventriculoperitoneal shunt after documentation of postoperative HCP. There was one case of chemical meningitis, and two cases confirmed bacterial infections. Craniopharyngioma can be successfully resected via a purely endoscopic, endonasal approach. Craniopharyngioma have a higher rate of perioperative hydrocephalus and postoperative CSF leak compared with other tumor types in the same area.&#x0D; Conclusion: Extended transsphenoidal approach is an excellent alternative of skull base approach for the removal of most of the craniopharyngioma.The endoscopic endonasal route provides a good exposure, especially of the sub-chiasmatic and retro-chiasmatic areas, as well as of the stalk– infundibulum axis and the third ventricle chamber. It gives better visualization, improved postoperative visual outcome for less manipulation and low complication then craniotomy. However CSF leak and diabetes insipidus is common known complications which have to be manage promptly and appropriately.&#x0D; Bangladesh Journal of Neuroscience 2013; Vol. 29 (2) : 108-114

Spatial Modeling of Visual Field Data for Assessing Glaucoma Progression

In order to reduce noise and account for spatial correlation, we applied disease mapping techniques to visual field (VF) data. We compared our calculated rates of progression to other established techniques. Conditional autoregressive (CAR) priors, weighted to account for physiologic correlations, were employed to describe spatial and spatiotemporal correlation over the VF. Our model is extended to account for several physiologic features, such as the nerve fibers serving adjacent loci on the VF not mapping to the adjacent optic disc regions, the presence of the blind spot, and large measurement fluctuation. The models were applied to VFs from 194 eyes and fitted within a Bayesian framework using Metropolis-Hastings algorithms. Our method (SPROG for Spatial PROGgression) showed progression in 42% of eyes. Using a clinical reference, our method had the best receiver operating characteristics compared with the point-wise linear regression methods. Because our model intrinsically accounts for the large variation of VF data, by adjusting for spatial correlation, the effects of outliers are minimized, and spurious trends are avoided. by using CAR priors, we have modeled the spatial correlation in the eye. combining this with physiologic information, we are able to provide a novel method for VF analysis. model diagnostics, sensitivity, and specificity show our model to be apparently superior to CURRENT POINT-wise linear regression methods. (http://www.anzctr.org.au number, ACTRN12608000274370.).

Clinical Phenotypes and Prognostic Full-Field Electroretinographic Findings in Stargardt Disease

To investigate the relationships between clinical and full-field electroretinographic (ERG) findings and progressive loss of visual function in Stargardt disease. Retrospective cohort study. We performed a retrospective review of data from 198 patients with Stargardt disease. Measures of visual function over time, including visual acuity, quantified Goldmann visual fields, and full-field ERG data were recorded. Data were analyzed using SAS statistical software. Subgroup analyses were performed on 148 patients with ERG phenotypic data, 46 patients with longitudinal visual field data, and 92 patients with identified ABCA4 mutations (46 with 1 mutation, and 47 with 2 or more mutations). Of 46 patients with longitudinal visual field data, 8 patients with faster central scotoma progression rates had significantly worse scotopic B-wave amplitudes at their initial assessment than 20 patients with stable scotomata (P = .014) and were more likely to have atrophy beyond the arcades (P = .047). Overall, 47.3% of patients exhibited abnormal ERG results, with rod-cone dysfunction in 14.2% of patients, cone-rod dysfunction in 17.6% of patients, and isolated cone dysfunction in 15.5% of patients. Abnormal values in certain ERG parameters were associated significantly with (maximum-stimulation A- and B-wave amplitudes) or tended toward (photopic and scotopic B-wave amplitudes) a higher mean rate of central scotoma progression compared with those patients with normal ERG values. Scotoma size and ERG parameters differed significantly between those with a single mutation versus those with multiple mutations. Full-field ERG examination provides clinically relevant information regarding the severity of Stargardt disease, likelihood of central scotoma expansion, and visual acuity deterioration. Patients also may exhibit an isolated cone dystrophy on ERG examination.

Rates of visual field progression in clinical glaucoma care

Purpose: To investigate rates of visual field progression and factors associated with progression rate in open-angle glaucoma in clinical glaucoma care.Methods: We performed a retrospective chart review of all patients with manifest primary open-angle glaucoma (POAG) and pseudoexfoliation glaucoma (PEXG) followed ≥ 5 years with ≥5 SITA Standard fields. Exclusion criteria were minimal. Demographics, intraocular pressure values (IOP), treatment and treatment changes, and visual field (VF) data were recorded. VF progression rates were calculated as slopes of mean deviation (MD) over time.Results: Five hundred and eighty-three patients were eligible. Three hundred and sixty-seven (62%) had POAG and 221 (38%) PEXG. Median MD at study start was −10.0 dB. Mean follow-up time was 7.8 years (SD ± 1.2); mean number of VF tests was 8.9 (SD ± 2.8). Progression rates varied very much among patients with a mean of −0.80 dB/year (SD ± 0.82; median rate, −0.62), and 5.6% of patients progressed at rates worse than −2.5 dB per year A negative slope of MD values was observed in 89% of patients. Mean IOP of all visits decreased over the study period from 20.15 to 18.10 mmHg. Higher age and mean IOP, and more intensive treatment were associated with more rapid progression, while PEXG and IOP variation were not, if treatment intensity was taken into account.Conclusion: Rates of visual field progression in manifest glaucoma with field loss in ordinary clinical care were highly variable. Progression rates rapid enough to influence quality of life were common.

The Relationship between Variability and Sensitivity in Large-Scale Longitudinal Visual Field Data

Evaluation of progressive visual field (VF) damage is often based on pointwise sensitivity data from standard automated perimetry; however, frequency-of seeing and test-retest studies demonstrate that these measurements can be highly variable, especially in areas of damage. The aim of this study was to characterize VF variability by the level of sensitivity using a statistical method to quantify heteroscedasticity. A total of 14,887 Humphrey 24-2 SITA Standard VFs from 2736 patients (2736 eyes) attending Moorfields Eye Hospital from 1997 to 2009 were studied retrospectively. The VF series of each eye was analyzed using pointwise linear regression of sensitivity over time, with residuals (difference from fitted-value) from each regression pooled according to both observed and fitted sensitivities. The median (interquartile range) patient age, follow-up, and series length was 64 (54-71) years, 5.5 (3.9-7.0) years, and 6 (5-7) VFs, respectively. The inferred variability as a function of fitted-sensitivity was in good agreement with previous estimates. Variability was also described as a function of measured sensitivity, which confirmed that variability increased rapidly as the observed sensitivity decreased. This study highlights a new approach for characterizing VF variability by the level of sensitivity. A considerable strength of the method is that inference is based on thousands of clinic patients rather than the tens of subjects in test-retest studies. The results can help distinguish real VF progression from measurement variability and will be used in models for glaucoma progression detection.

Glaucoma Progression in Eyes with a History of Refractive Corneal Surgery

To evaluate the glaucoma progression in patients with a history of refractive corneal surgery (RCS). A total of 313 eyes of 313 glaucoma patients (RCS group, 34 eyes; non-RCS group, 279 eyes) with a mean follow-up period of 2.7 years were included. Glaucoma progression was determined either by experts' stereoscopic optic disc/retinal nerve fiber layer (RNFL) photographs or by serial visual field (VF) data. Uni- and multivariate Cox's proportional hazards models were used to determine associations between potential risk factors including a history of RCS and glaucoma progression. Among 313 eyes, 87 (27.8%) eyes showed progression either by optic disc/RNFL photographs or VF assessment during the follow-up period. Ten (29.4%) of eyes in the RCS group and 77 (27.6%) of eyes in the non-RCS group showed glaucoma progression; however, prevalence of progression did not differ between the two groups (P = 0.482). Among all participants, baseline age and VF pattern standard deviation (PSD; hazard ratios of 1.013 and 1.119; P = 0.026 and P < 0.001, respectively) were significant risk factors for progression. In both the RCS and the non-RCS group, only VF PSD was a significant risk factor for progression according to multivariate Cox proportional hazards (1.193, 1.099, P < 0.001, P < 0.001, respectively). Baseline VF PSD and age substantially affected glaucoma progression in all study participants, although their RCS history was not a significant risk factor for glaucoma progression.

Improved Estimates of Visual Field Progression Using Bayesian Linear Regression to Integrate Structural Information in Patients with Ocular Hypertension

To assess whether neuroretinal rim area (RA) measurements of the optic disc could be used to improve the estimate of the rate of change in visual field (VF) mean sensitivity in patients with ocular hypertension (OHT) using a Bayesian linear regression (BLR), compared to a standard ordinary least squares linear regression (OLSLR) of mean sensitivity (MS) measurements alone. MS and RA measurements were analyzed from a longitudinal series of 179 patients with OHT visiting Moorfields Eye Hospital between 1992 and 2000. For each patient, linear regression of RA was computed after an appropriate transformation to "scale" RA with MS measurements, and the slope coefficient from this regression was used as a prior for BLR of MS. The BLR then was compared with the OLSLR approach by evaluating how accurately each regression technique predicted future MS measurements. On average, BLR was significantly more accurate than OLSLR for series up to 8 measurements long (root-mean-square prediction error [RMSPE] was 0.14 decibels [dB] smaller with BLR than OLSLR; P < 0.001, Wilcoxon signed-rank test), with OLSLR of VF data alone being more accurate for longer series (RMSPE was 0.06 dB smaller with OLSLR than BLR). BLR provides a significantly more accurate estimate of the rate of change in MS than the standard OLSLR approach, especially in short time series, suggesting that structural measurements can be used successfully in statistical models to assist clinicians monitoring VF progression in patients with OHT. Further studies are necessary to validate the method in glaucoma patients.

Progressive enhancement of alpha activity and visual function in patients with optic neuropathy: A two-week repeated session alternating current stimulation study

IntroductionRepetitive transorbital alternating current stimulation (rtACS) can improve visual deficits in patients with optic nerve damage. Recent retrospective results suggest that rtACS enhances oscillatory brain activity. The exact mechanisms of rtACS are unclear and little is known about possibly frequency-specific neural-plastic mechanisms. An association between bandwidth-confined neural-entrainment and vision recovery maximization could offer a novel therapeutic option for patients with optic neuropathy. ObjectivesThe goal of this prospective open-label study was to investigate if the enhancement of rhythmic brain activity over 10 days of consecutive rtACS stimulation is associated with visual field recovery. The secondary goal was to investigate neurophysiological mechanisms related to frequency dependent adaptive plasticity. Methods18 Patients with visual field impairments resulting from pre-chiasmatic partial optic nerve damage received rtACS on 10 consecutive days. Daily, subject-specific treatment parameters (<500 μA, 9–37 Hz, 25–40 min/day) were defined and EEG-spectra collected prior to and after rtACS. Visual field data was collected at day 1 and 10. The change of spectral-power in classic bandwidths were investigated and correlated with visual field deficit recovery. ResultsAfter 10 days of rtACS alpha-power over bilateral occipital electrodes was significantly larger than at baseline (FTime x alpha-powerp < 0.01). This effect was progressive over subsequent days of stimulation (cubic-fit, R2 0.70, RMSE 0.008). Perimetric results improved significantly, but they were not associated with changes in alpha-synchronization. DiscussionrtACS can induce cumulative bandwidth-confined changes in brain rhythms over multiple sessions. These findings are in line with the notion of brain-state dependent [1] and bandwidth-confined entrainment [2] as well as rtACS facilitated visual recovery [3].

Relationship between central corneal thickness and progression of visual field loss in patients with open-angle glaucoma

ObjectiveTo determine whether a relationship exists between central corneal thickness (CCT) and visual field (VF) progression in treated patients with open-angle glaucoma and asymmetric corneal thickness. DesignRetrospective chart review. ParticipantsWe studied 100 charts of patients with open-angle glaucoma and also bilateral CCT and VF data. MethodsCharts from 2 glaucoma subspecialty practices were reviewed. The CCT and the rate of progression and event analysis of visual field data were assessed in all subjects. Subanalysis was performed for subjects whose CCT asymmetry was ≥ 16 μm. ResultsThe mean CCT was 544 ± 40 μm OD and 541 ± 40 μm OS. The mean CCT difference between fellow eyes was 15 ± 11 μm (range, 1 to 52 μm). There was no significant intrasubject difference in the mean deviation (MD) and the pattern standard deviation (PSD) (p =0.917 and p = 0.704, respectively; paired t test). The more advanced VF MDs and PSDs were found in the thin eyes of 47 and 50 subjects, respectively (p = 0.459 and p = 0.317, respectively; χ2). Of the 65 subjects whose visual field indexes were available, 34 had the more rapid visual field index rates of progression in the thin eye (p = 0.400; χ2). Of the 27 subjects for whom event analysis was available, 15 had the worse progression category in the thin eye (p = 0.453, χ2). Subgroup analysis of 48 subjects with ≥ 16 μm CCT asymmetry did not find any significant difference in analyses of field progression between fellow eyes. ConclusionsNo relationship was found between CCT and VF loss in treated patients with primary open-angle glaucoma or normal-tension glaucoma with asymmetrical CCT. Specifically, the thin eye did not have the more advanced VF loss or more rapid VF progression.

Combining Structural and Functional Measurements to Improve Estimates of Rates of Glaucomatous Progression

To evaluate whether a combination of topographic optic disc measurements and visual field data may improve the estimation of rates of structural and functional progression in glaucoma and the prediction of future outcomes in the disease. Observational cohort study. The study included 242 eyes of 179 glaucoma patients followed for an average of 6.4 ± 1.1 years. Subjects were longitudinally monitored with standard automated perimetry (SAP) and confocal scanning laser ophthalmoscopy (CSLO). Slopes of functional and structural change over time were evaluated by the parameters mean deviation (MD) and rim area, respectively. For each eye, the follow-up time was divided into 2 equal periods: the first half was used to obtain the slopes of change and the second period was used to test the predictions. Slopes of change were calculated using 2 methods, the conventional approach of ordinary least squares linear regression and a Bayesian joint regression model integrating structural and functional information. The mean square error (MSE) of the predictions was used to compare the predictive performance of the different methods. Bayesian slopes were more accurate than those obtained by the ordinary least squares method in predicting future MD (MSE: 5.13 vs 11.2, respectively; P < .001) and rim area values (MSE: 0.016 vs 0.027, respectively; P < .01). A Bayesian joint regression model combining structure and function resulted in more accurate and precise estimates of slopes of change compared to the conventional method of ordinary least squares linear regression.