Current Practice with Standard Automated Perimetry

Short Wavelength Automated Perimetry, Standard Automated Perimetry, and Optical Coherence Tomography in Dominant Optic Atrophy

Background: Blue-yellow axis dyschromatopsia is well-known in Autosomal Dominant Optic Atrophy (ADOA) patients, but there were no data on the correlation between retinal structure and short-wavelength automated perimetry (SWAP) values in this pathology. Methods: In this cross-sectional case-control study, we assessed the correlation between best corrected visual acuity (BCVA), standard automated perimetry (SAP), SWAP, and optical coherence tomography (OCT) parameters of 9 ADOA patients compared with healthy controls. Correlation analysis was performed between BCVA, mean deviation, pattern standard deviation (PSD), and fovea sensitivity (FS) values and the OCT thickness of each retinal layer and the peripapillary retinal nerve fiber layer (pRNFL). Results: The following significant and strong correlations were found: between BCVA and ganglion cell layer (GCL) and the global (G) pRNFL thicknesses; between SAP FS and GCL and the G-pRNFL thicknesses; between SWAP PSD and total retina, GCL, inner plexiform layer, inner nuclear layer, inner retinal layer and the temporal pRNFL thicknesses. We found a constant shorter duration of the SITA-SWAP compared with the SITA-STANDARD strategy. Conclusions: SWAP, SAP, and BCVA values provided relevant clinical information about retinal involvement in our ADOA patients. The perimetric functional parameters that seemed to correlate better with structure involvement were FS on SAP and PSD on SWAP.

Visual field indices in children and adults with comparable retinal nerve fiber layer thickness

PURPOSE

To compare visual field indices in normal children and adults with similar retinal nerve fiber layer (RNFL) thickness on optical coherence tomography (OCT).

METHODS

This cross-sectional study included 59 eyes of 59 normal children 6-18 years of age compared to normal adults. The children underwent visual field testing on the Humphrey Field Analyzer (HFA) and RNFL thickness measurement on OCT. Normal adults who had undergone OCT and visual field testing were retrieved from the OCT database. The mean deviation (MD) in each child was compared with the MD in RNFL thickness-matched eyes of normal adults. Children 6-11 years and 12-18 years were analyzed separately.

RESULTS

Overall, the MD of children was significantly less than that of the normal adults despite having the same RNFL thickness (-2.42 ± 1.42 dB vs -1.61 ± 1.47 dB [P = 0.006]). When stratified by age, the difference in MD of children <12 years was significantly less than normal adults (-2.72 ± 1.5dB vs -1.53 ± 1.2 dB [P = 0.003) while in children >12 years, the difference did not reach statistical significance (-2.18 ± 1.2 vs -1.51 ± 1.32 [P = 0.12]).

CONCLUSIONS

In our study cohort, children <12 years had lower visual field indices than adults. Their visual fields may appear worse than they would for an adult with the same RNFL thickness. Normal children >12 years of age seem to have a retinal sensitivity comparable to the adult normative database. It is worthwhile to consider the development of a separate pediatric normative database for the visual field assessment of children <12 years of age.

Comparing retinal sensitivities on blue-on-yellow and green-on-yellow perimetry in glaucoma suspects

Purpose

To compare the retinal sensitivities between the blue-on-yellow perimetry (BYP)/short-wavelength automated perimetry (SWAP) and green-on-yellow perimetry (GYP) among patients with and without nuclear sclerosis among glaucoma suspects.

Methods

After ophthalmic examination, patients were subjected to two perimetric tests: BYP and GYP. The visual field (VF) parameters were compared between the two perimeters (p < 0.05 was considered significant).

Results

Fifty-five eyes of 39 patients with a mean age of 60.53 ± 9.70 years were included in the study. Twenty-one eyes had clear lens or pseudophakia. Twenty-six eyes had lower grades of nuclear sclerosis (NO2NC2, NO3NC3) and eight eyes had higher grades of cataract (NO4NC4, NO5NC5). The mean retinal sensitivity (RS) in BYP was 22.08 ± 5.02 (dB) and in GYP was 23.84 ± 5.50 (dB) (p = 0.08). The mean defect in BYP was -2.56 ± 4.40 (dB) and in GYP was -3.24 ± 5.05 (dB), pattern standard deviation (PSD) in BYP was 3.65 ± 1.91 (dB) and in GYP was 3.83 ± 1.99 (dB), and foveal threshold (FT) was 24.20 ± 4.32 (dB) in BYP and 28.10 ± 4.50 (dB) in GYP. The two perimeters showed good agreement by the Bland-Altman plot for all parameters. Fourteen eyes showed perimetric changes suggestive of glaucoma by BYP. In these, GYP had a sensitivity of 92.86% (95% CI of 66.13% to 99.82%) and specificity of 95.12% (95% CI of 83.47% to 99.40%).

Conclusion

BYP and GYP show good agreement. They are comparable in clear media as well as in different grades of nuclear sclerosis. GYP showed good sensitivity and specificity compared to BYP.

Detecting glaucoma from multi-modal data using probabilistic deep learning

Objective

To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields.

Design

Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control study.

Subjects and participants

Fundus photograph and visual field data from 1,655 eyes of 929 normal and glaucoma subjects to develop and test deep learning models and an independent group of 196 eyes of 98 normal and glaucoma patients to validate deep learning models.

Main outcome measures

Accuracy and area under the receiver-operating characteristic curve (AUC).

Methods

Fundus photographs and OCT images were carefully examined by clinicians to identify glaucomatous optic neuropathy (GON). When GON was detected by the reader, the finding was further evaluated by another clinician. Three probabilistic deep convolutional neural network (CNN) models were developed using 1,655 fundus photographs, 1,655 visual fields, and 1,655 pairs of fundus photographs and visual fields collected from Compass instruments. Deep learning models were trained and tested using 80% of fundus photographs and visual fields for training set and 20% of the data for testing set. Models were further validated using an independent validation dataset. The performance of the probabilistic deep learning model was compared with that of the corresponding deterministic CNN model.

Results

The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and combined modalities using development dataset were 0.90 (95% confidence interval: 0.89-0.92), 0.89 (0.88-0.91), and 0.94 (0.92-0.96), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using the independent validation dataset were 0.94 (0.92-0.95), 0.98 (0.98-0.99), and 0.98 (0.98-0.99), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using an early glaucoma subset were 0.90 (0.88,0.91), 0.74 (0.73,0.75), 0.91 (0.89,0.93), respectively. Eyes that were misclassified had significantly higher uncertainty in likelihood of diagnosis compared to eyes that were classified correctly. The uncertainty level of the correctly classified eyes is much lower in the combined model compared to the model based on visual fields only. The AUCs of the deterministic CNN model using fundus images, visual field, and combined modalities based on the development dataset were 0.87 (0.85,0.90), 0.88 (0.84,0.91), and 0.91 (0.89,0.94), and the AUCs based on the independent validation dataset were 0.91 (0.89,0.93), 0.97 (0.95,0.99), and 0.97 (0.96,0.99), respectively, while the AUCs based on an early glaucoma subset were 0.88 (0.86,0.91), 0.75 (0.73,0.77), and 0.92 (0.89,0.95), respectively.

Conclusion and relevance

Probabilistic deep learning models can detect glaucoma from multi-modal data with high accuracy. Our findings suggest that models based on combined visual field and fundus photograph modalities detects glaucoma with higher accuracy. While probabilistic and deterministic CNN models provided similar performance, probabilistic models generate certainty level of the outcome thus providing another level of confidence in decision making.

Spotlight on iPad Visual Field Tests Efficacy

Tablet based perimetry has the potential to be used as a low-cost, portable method for glaucoma screening. With the advent of tablets with large dynamic luminance range and high spatial resolution, perimetry applications can test visual field locations within the central 30 degrees, just like bowl perimetry. Tablet perimetry has garnered interest in this COVID era as it can be promptly done in the waiting room or even from the comfort of home. The current review focuses on evaluating glaucoma detection sensitivities, diagnostic abilities and correlation of each parameter and examination time of the iPad based perimetry applications with those of HFA.

Should clinical automated perimetry be considered for routine functional assessment of early/intermediate age-related macular degeneration (AMD)? A systematic review of current literature

Purpose

There is growing interest in functional testing for early/intermediate age‐related macular degeneration (iAMD). However, systematic evaluation of existing clinical functional tests is lacking. This systematic review examines evidence for using clinical automated perimetry in routine assessment of early/iAMD.

Recent findings

PubMed, Web of Science Core Collection, and Embase were searched from inception to October 2020 to answer, is there evidence of visual field defects in early/iAMD, and if so, are early/iAMD visual field defects linked to real‐world patient outcomes? Articles using clinical automated perimetry (commercially accessible and non‐modified devices/protocols) were included. Microperimetry was excluded as this has yet to be incorporated into clinical guidelines. The primary outcome was global visual field indices including mean deviation (MD), pattern standard deviation (PSD), mean sensitivity (MS) and frequency of defects. The secondary outcome was any real‐world patient outcome including quality of life and/or activities of daily living indices. Twenty‐six studies were eligible for inclusion and all studies were observational. There was consistent evidence of worsened MD, PSD, MS and frequency of defects for early/iAMD compared to normal eyes under photopic, low‐photopic and scotopic conditions. Meta‐analysis of studies using standard automated perimetry (SAP) under photopic conditions revealed worsened MD (−1.52dB [−2.27, −0.78 dB]) and MS (−1.47dB [−2, −0.94 dB]) in early/iAMD compared to normal eyes, representing large statistical effect sizes but non‐clinically meaningful reductions. There was insufficient data for meta‐analyses regarding other clinical automated perimetry protocols. Only one study assessed a real‐world patient outcome (on‐road driving performance), with no significant link to visual field outcomes in early/iAMD.

Summary

Significant reduction of global visual field indices is present in early/iAMD, but not clinically meaningful using SAP under photopic conditions. Translational relevance of visual field outcomes to patient outcomes in early/iAMD remains unclear. Thus, SAP under photopic conditions is unlikely to be useful for routine assessment of early/iAMD.

Aspects of Tertiary Prevention in Patients with Primary Open Angle Glaucoma

The purpose of the study is to assess the health of patients in the activity of tertiary prevention dedicated to preventing blindness caused by POAG (primary glaucoma with open angle and high tension) and NTG (primary glaucoma with open-angle and statistically normal tension-particular form of glaucoma with open angle) and preservation of the remaining visual function. The design of the study is epidemiological, observational, descriptive and retrospective, and uses only the data recorded in the existing records in the archives of the Ophthalmology office within the Integrated Outpatient Clinic of the Emergency Clinical Hospital of Oradea (IOCECHO) during the years 1999-2019 (anamnestic data; objective examination and paraclinical examination: intraocular pressure-IOP and visual field-VF). The methods of the study included the standardized protocol: anamnesis, physical ophthalmological examination, IOP determination, and computerized perimetry with the "Fast Threshold" strategy performed with the "Opto AP-300" perimeter. The obtained results were statistically processed with a specialized software (S.P.S.S.-I.B.M. Statistics version 22). The study examined the available data of 522 patients of which 140 were men (26.8%) and 382 were women (73.2%). The gender ratio was 0.37. In the period 1999-2019, 150,844 people with ophthalmic pathology were consulted in the Ophthalmology office of IOCECHO out of which 522 patients (0.35%) were diagnosed with primitive open-angle glaucoma, 184 people (35.2%) presented high IOP (POAG), and 338 people (64.8%) had statistically normal IOP (NTG). The annual proportion of cases diagnosed with glaucoma in the total number of patients examined was between 0.1% (2005; 2008; 2010) and 2.4% in 2012, when 101 people were detected. In the studied records, no cases of uni- and/or bilateral blindness were mentioned. The mean age of glaucoma patients at the first consultation was 60.81 ± 12.14 years with high frequencies in the 55-69 age groups and at the last consultation it was 66.10 ± 12.47 years with high frequencies in the age groups between 60-74 years. Monitoring and treatment of glaucoma patients was beneficial; IOP decreased statistically significantly: in patients with POAG by 46.16%, from 30.50 ± 7.98 mmHg to 16.42 ± 3.01 mmHg (p = 0.000) and in those with NTG by 17.44%, at 16.39 ± 3.66 mmHg at 13.53 ± 1.92 mmHG (p = 0.000). The duration of treatment and monitoring was on average 5.1 ± 3.4 years, for 184 patients (35.2%) with POAG and 5.1 ± 3.8 years for 338 patients (64.8%) with NTG. Tertiary prevention of glaucoma, by providing specialized care, ensures effective control of IOP and implicitly of the long-term evolution of the disease. IOP is the only modifiable risk factor in patients with POAG and NTG and its decrease prevents the progression of the disease and emphasizes the importance of early diagnosis and treatment. The management of the glaucoma patient consisted of: complete ophthalmological examination (subjective and objective), paraclinical examination with IOP, and VF measurement (valuable ophthalmological diagnostic tool) for disease detection and effective assessment of disease progression in order to improve the process of therapeutic decision making.

Accuracy and reliability of measurements obtained with a noncontact tono-pachymeter for clinical use in mass screening

We evaluated the reliability and accuracy of the noncontact CT-1P tonopachymeter (Topcon, Japan) in terms of intraocular pressure (IOP) and central corneal thickness (CCT). One hundred sixty-three healthy participants and 33 patients with open angle glaucoma were enrolled. IOPs were measured by CT-1P (T-IOP) and Goldmann applanation tonometer (G-IOP), and CCTs were measured by the CT-1P (T-CCT) and an ultrasound pachymeter (US-CCT). Both CCT instrument-adjusted (T-IOP-C) and unadjusted T-IOPs (T-IOP-NC) were included. Pearson correlation coefficients and biases assessed with Bland-Altman analysis with 95% confidence interval (CI) were calculated for reliability evaluation. Intrasession repeatability was excellent for both T-IOP (intraclass correlation coefficient [ICC] 0.91) and T-CCT (ICC 0.98). Intersession reproducibility was also excellent for T-CCT (ICC 0.94). T-IOP-NC and T-IOP-C both showed significant correlations with G-IOP (r = 0.801, P  <  0.001 and r = 0.658, P  < 0.001, respectively). T-CCT was also strongly correlated with US-CCT (r = 0.958; P  < 0.001). T-IOP-NC and T-IOP-C both showed a positive bias (1.37 mmHg, 95% CI [1.14, 1.61] and 2.77 mmHg, 95% CI [2.49, 3.05], respectively). T-CCT showed a negative bias of - 17.3 µm (95% CI [-18.8, - 15.8]). With cautious interpretation, the CT-1P may offer good feasibility for IOP and CCT measurement in screening centers.

Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard

PURPOSE

To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.

DESIGN

Retrospective, cross-sectional, longitudinal cohort study.

PARTICIPANTS

Of 31 591 visual fields (VFs) on 8077 subjects, 13 231 VFs from the most recent visit of each patient were included to develop the AI dashboard. Longitudinal VFs from 287 eyes with glaucoma were used to validate the models.

METHOD

We entered VF data from the most recent visit of glaucomatous and nonglaucomatous patients into a "pipeline" that included principal component analysis (PCA), manifold learning, and unsupervised clustering to identify eyes with similar global, hemifield, and local patterns of VF loss. We visualized the results on a map, which we refer to as an "AI-enabled glaucoma dashboard." We used density-based clustering and the VF decomposition method called "archetypal analysis" to annotate the dashboard. Finally, we used 2 separate benchmark datasets-one representing "likely nonprogression" and the other representing "likely progression"-to validate the dashboard and assess its ability to portray functional change over time in glaucoma.

MAIN OUTCOME MEASURES

The severity and extent of functional loss and characteristic patterns of VF loss in patients with glaucoma.

RESULTS

After building the dashboard, we identified 32 nonoverlapping clusters. Each cluster on the dashboard corresponded to a particular global functional severity, an extent of VF loss into different hemifields, and characteristic local patterns of VF loss. By using 2 independent benchmark datasets and a definition of stability as trajectories not passing through over 2 clusters in a left or downward direction, the specificity for detecting "likely nonprogression" was 94% and the sensitivity for detecting "likely progression" was 77%.

CONCLUSIONS

The AI-enabled glaucoma dashboard, developed using a large VF dataset containing a broad spectrum of visual deficit types, has the potential to provide clinicians with a user-friendly tool for determination of the severity of glaucomatous vision deficit, the spatial extent of the damage, and a means for monitoring the disease progression.

Contrast sensitivity isocontours of the central visual field

Standard automated perimetry (SAP), the most common form of perimetry used in clinical practice, is associated with high test variability, impacting clinical decision making and efficiency. Contrast sensitivity isocontours (CSIs) may reduce test variability in SAP by identifying regions of the visual field with statistically similar patterns of change that can be analysed collectively and allow a point (disease)-to-CSI (normal) comparison in disease assessment as opposed to a point (disease)-to-point (normal) comparison. CSIs in the central visual field however have limited applicability as they have only been described using visual field test patterns with low, 6° spatial sampling. In this study, CSIs were determined within the central 20° visual field using the 10-2 test grid paradigm of the Humphrey Field Analyzer which has a high 2° sampling frequency. The number of CSIs detected in the central 20° visual field was greater than previously reported with low spatial sampling and stimulus size dependent: 6 CSIs for GI, 4 CSIs for GII and GIII, and 3 CSIs for GIV and GV. CSI number and distribution were preserved with age. Use of CSIs to assess visual function in age-related macular degeneration (AMD) found CSI guided analysis detected a significantly greater deviation in sensitivity of AMD eyes from normal compared to a standard clinical pointwise comparison (−1.40 ± 0.15 dB vs −0.96 ± 0.15 dB; p < 0.05). This work suggests detection of CSIs within the central 20° is dependent on sampling strategy and stimulus size and normative distribution limits of CSIs can indicate significant functional deficits in diseases affecting the central visual field such as AMD.

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

BACKGROUND

Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision ('progression') challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT).

OBJECTIVE

To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials.

DESIGN

Method 'hit rate' (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC).

SETTING

Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID).

PARTICIPANTS

UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable.

INTERVENTIONS

24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA).

MAIN OUTCOME MEASURES

Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size.

RESULTS

Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging.

LIMITATIONS

TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates.

CONCLUSIONS

The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN96423140.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath's chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning

PURPOSE

Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine learning-based index for glaucoma progression detection that outperforms global, region-wise, and point-wise indices.

DESIGN

Development and comparison of a prognostic index.

METHOD

Visual fields from 2085 eyes of 1214 subjects were used to identify glaucoma progression patterns using machine learning. Visual fields from 133 eyes of 71 glaucoma patients were collected 10 times over 10 weeks to provide a no-change, test-retest dataset. The parameters of all methods were identified using visual field sequences in the test-retest dataset to meet fixed 95% specificity. An independent dataset of 270 eyes of 136 glaucoma patients and survival analysis were used to compare methods.

RESULTS

The time to detect progression in 25% of the eyes in the longitudinal dataset using global mean deviation (MD) was 5.2 (95% confidence interval, 4.1-6.5) years; 4.5 (4.0-5.5) years using region-wise, 3.9 (3.5-4.6) years using point-wise, and 3.5 (3.1-4.0) years using machine learning analysis. The time until 25% of eyes showed subsequently confirmed progression after 2 additional visits were included were 6.6 (5.6-7.4) years, 5.7 (4.8-6.7) years, 5.6 (4.7-6.5) years, and 5.1 (4.5-6.0) years for global, region-wise, point-wise, and machine learning analyses, respectively.

CONCLUSIONS

Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods.

Six-month Longitudinal Comparison of a Portable Tablet Perimeter With the Humphrey Field Analyzer

PURPOSE

To establish the medium-term repeatability of the iPad perimetry app Melbourne Rapid Fields (MRF) compared to Humphrey Field Analyzer (HFA) 24-2 SITA-standard and SITA-fast programs.

DESIGN

Multicenter longitudinal observational clinical study.

METHODS

Sixty patients (stable glaucoma/ocular hypertension/glaucoma suspects) were recruited into a 6-month longitudinal clinical study with visits planned at baseline and at 2, 4, and 6 months. At each visit patients undertook visual field assessment using the MRF perimetry application and either HFA SITA-fast (n = 21) or SITA-standard (n = 39). The primary outcome measure was the association and repeatability of mean deviation (MD) for the MRF and HFA tests. Secondary measures were the point-wise threshold and repeatability for each test, as well as test time.

RESULTS

MRF was similar to SITA-fast in speed and significantly faster than SITA-standard (MRF 4.6 ± 0.1 minutes vs SITA-fast 4.3 ± 0.2 minutes vs SITA-standard 6.2 ± 0.1 minutes, P < .001). Intraclass correlation coefficients (ICC) between MRF and SITA-fast for MD at the 4 visits ranged from 0.71 to 0.88. ICC values between MRF and SITA-standard for MD ranged from 0.81 to 0.90. Repeatability of MRF MD outcomes was excellent, with ICC for baseline and the 6-month visit being 0.98 (95% confidence interval: 0.96-0.99). In comparison, ICC at 6-month retest for SITA-fast was 0.95 and SITA-standard 0.93. Fewer points changed with the MRF, although for those that did, the MRF gave greater point-wise variability than did the SITA tests.

CONCLUSIONS

MRF correlated strongly with HFA across 4 visits over a 6-month period, and has good test-retest reliability. MRF is suitable for monitoring visual fields in settings where conventional perimetry is not readily accessible.

Automated achromatic perimetry

Visual field (VF) testing is an important diagnostic tool for Glaucoma. The current gold standard for VF testing is automated perimetry. This article is an attempt to familiarize the reader with components of an achromatic (white on white) automated perimetry printout. It addresses use of Humphrey perimeter to interpret the results. For the purpose of this review, a PubMed search was made using perimetry, Humphrey VFs review as key words and the relevant articles were studied. The references appended with these articles were also analyzed, and any appropriate article was also included. A systematic approach has been outlined that results in a thorough interpretation of the printout. One should be able to identify a normal field and establish glaucomatous progression, detect the presence of a field defect, determine whether it is due to glaucoma or neuro-ophthalmic disease if any. Comprehensive evaluation using clinical examination, tonometry, and perimetry should be considered together to make a proper diagnosis of glaucoma and judge its progression over time.

Expert Evaluation of Visual Field Decay in Glaucoma Correlates With the Fast Component of Visual Field Loss

PURPOSE

To compare the assessment of serial visual fields (VFs) based on subjective expert evaluation with the fast and slow VF component rates determined with pointwise exponential regression (PER) and pointwise linear regression (PLR).

MATERIALS AND METHODS

A total of 5272 VF examinations from 376 eyes diagnosed with open-angle glaucoma were included. Three glaucoma specialists assessed each VF qualitatively to evaluate progression status and the qualitative rate of progression. The rates of VF decay were determined with PER and PLR at each VF location, which were ranked according to the regression coefficient and partitioned into 2 groups (fast and slow). A mean rate for the fast and slow partitions was obtained based on the average of the regression coefficients in each partition. κ-values were used to measure the agreement among the experts and the PER and PLR algorithms.

RESULTS

The average baseline VF mean deviation for the study sample was -6.6 (±5.9) dB. The agreement of the likelihood of progression among the dichotomized experts' score and PER was moderate (κ=0.41, P<0.01) and fair (κ=0.39, P<0.01) for PLR. The agreement of the likelihood of progression among the 3 dichotomized experts' scores was fair (κ=0.22, P<0.01). The agreement of the area of worsening among the dichotomized experts' score and PER and PLR were both moderate (κ=0.48, P<0.01; κ=0.46, P<0.01). The eyes flagged by experts as having "fast" progression rates had a higher average rates of decay for PER and PLR at -2.7 (±4.1) %/year and -0.8 (±1.2) dB/year; eyes flagged as "slow" had lower rates of decay at -0.3 (±1.5) %/year and -0.1 (±0.5) dB/year.

CONCLUSIONS

Expert qualitative evaluation of field series for change and rate of change correlate more closely with the fast component than with the slow component of VF decay.

A Comparison of Perimetric Results from a Tablet Perimeter and Humphrey Field Analyzer in Glaucoma Patients

Purpose

To determine the correlation between the perimetric outcomes from perimetry software Melbourne Rapid Fields (MRF) run on an Apple iPad tablet and those from the Humphrey Field Analyzer (HFA).

Methods

The MRF software was designed with features including variable fixation and fast thresholding using Bayes logic. Here, we report a cross-sectional study on 90 eyes from 90 participants: 12 had normal optic nerves and 78 had glaucoma with various degrees of visual field loss (41 mild and 37 moderate-severe). Exclusion criteria were patients with worse than 20/40 vision or recent intraocular surgery. The visual field outcomes of MRF were compared against those returned from the HFA 24-2 SITA standard. Participants were tested twice on the MRF to establish test–retest repeatability.

Results

The test durations were shorter on MRF than HFA (5.7 ± 0.1 vs. 6.3 ± 0.1 minutes, P < 0.001). MRF showed a high level of concordance in its outcomes with HFA (intraclass coefficient [ICC] = 0.93 for mean defect [MD] and 0.86 for pattern deviation [PD]) although the MRF tended to give a less negative MD (1.4 dB bias) compared with the HFA. MRF also showed levels of test–retest reliability comparable to HFA (ICC = 0.93 for MD and 0.89 for PD, 95% limits of agreement −4.5 to 4.3 dB).

Conclusion

The perimetry results from the MRF have a strong correlation to the HFA outcomes. MRF also has test–retest reliability comparable to HFA.

Translational Relevance

Portable tablet perimetry may allow accurate assessment of visual field when standard perimetry machines are unavailable or unsuitable.

Determining Spatial Summation and Its Effect on Contrast Sensitivity across the Central 20 Degrees of Visual Field

PURPOSE

Recent studies propose that the use of target stimuli within or close to complete spatial summation reveal larger threshold elevation in ocular disease. The Humphrey Visual Field Analyzer (HFA) is used to assess visual function yet the spatial summation characteristics are unexplored for the central macular region. We therefore wanted to establish the relationship between contrast sensitivity and stimulus size (spatial summation) within the central 20° visual field using the high sampling density of the 10-2 test grid.

METHODS

Thresholds were measured for one eye from 37 normal subjects using the HFA 10-2 test grid with all five Goldmann (G) targets (GI to GV). Subject data were converted to 50-year-old equivalent using published and calculated location-specific decade correction factors. Spatial summation curves were fitted for all data at all locations. The size of Ricco's critical area (Ac) within which complete spatial summation operates (k = 1), and the slope of partial summation (k < 1: to characterize partial summation), was established.

RESULTS

The 50-year-old age normative data were determined for all Goldmann stimulus sizes for the 10-2 HFA test grid and showed a marked change in contrast sensitivity for small test stimuli (e.g. GI) and little change in larger test stimuli (e.g. GV). Both the Ac and k values did not vary with age allowing for the application of the age correction factors. Ac and k values increased with eccentricity with GI remaining within complete spatial summation and GII was close or within complete spatial summation. GIII or larger test sizes were always outside complete spatial summation operating within various levels of partial summation.

CONCLUSIONS

The developed normative data now allows comparisons of data sets with high sampling density using the 10-2 grid irrespective of subject age. Test size is important when assessing ocular disease yet only GI or GII stimuli operate close to or within complete spatial summation in the macula. Current visual field testing protocols employ GIII which is always outside complete spatial summation and operates under various values of partial summation: GIII may not be the most suitable test size to assess ocular disease affecting the macula.

Equating spatial summation in visual field testing reveals greater loss in optic nerve disease

PURPOSE

To test the hypothesis that visual field assessment in ocular disease measured with target stimuli within or close to complete spatial summation results in larger threshold elevation compared to when measured with the standard Goldmann III target size. The hypothesis predicts a greater loss will be identified in ocular disease. Additionally, we sought to develop a theoretical framework that would allow comparisons of thresholds with disease progression when using different Goldmann targets.

METHODS

The Humphrey Field Analyser (HFA) 30-2 grid was used in 13 patients with early/established optic nerve disease using the current Goldmann III target size or a combination of the three smallest stimuli (target size I, II and III). We used data from control subjects at each of the visual field locations for the different target sizes to establish the number of failed points (events) for the patients with optic nerve disease, as well as global indices for mean deviation (MD) and pattern standard deviation (PSD).

RESULTS

The 30-2 visual field testing using alternate target size stimuli showed that all 13 patients displayed more defects (events) compared to the standard Goldmann III target size. The median increase for events was seven additional failed points: (range 1-26). The global indices also increased when the new testing approach was used (MD -3.47 to -6.25 dB and PSD 4.32 to 6.63 dB). Spatial summation mapping showed an increase in critical area (Ac) in disease and overall increase in thresholds when smaller target stimuli were used.

CONCLUSIONS

When compared to the current Goldmann III paradigm, the use of alternate sized targets within the 30-2 testing protocol revealed a greater loss in patients with optic nerve disease for both event analysis and global indices (MD and PSD). We therefore provide evidence in a clinical setting that target size is important in visual field testing.

Automated Perimetry and Visual Dysfunction in Blast-Related Traumatic Brain Injury

PURPOSE

To evaluate feasibility and results of automated perimetry in veterans with combat blast neurotrauma.

DESIGN

Prospective, longitudinal, observational case series.

PARTICIPANTS

Sixty-one patients in a Veterans Affairs Polytrauma Center diagnosed with traumatic brain injury (TBI) from combat blast exposure.

METHODS

Study participants underwent automated perimetry at baseline (median interval, 2 months after injury) (Humphrey Field Analyzer, Carl Zeiss Meditec, Dublin, CA, Swedish Interactive Threshold Algorithm 30-2 Standard or Fast), and 36 of them were followed up (median interval, 10 months after baseline). Presence of significant mean deviation and pattern standard deviation was determined for testing with reliability indices ≤20% for fixation loss, 15% for false-positives, and 33% for false-negatives. Test-retest stability of global visual field indices was assessed for tests with these cutoffs or with elevated fixation loss. Associations between global visual field defects and predictors were examined.

MAIN OUTCOME MEASURES

Global visual field indices (mean deviation and pattern standard deviation).

RESULTS

Among 61 study participants (109 study eyes) with baseline testing, a field that met reliability cutoffs was obtained for 48 participants (79%) and 78 eyes (72%). Fixation loss was found in 29% of eyes in initial testing. Nine study participants (15%) demonstrated hemianopia or quadrantanopia, and an additional 36% had an abnormal global visual field index. Global indices were relatively stable at follow-up testing for tests meeting fixation-loss cutoffs and tests that did not. Visual scotomas due to post-chiasmal lesions were associated with moderate to severe TBI or penetrating head injury, but other visual field deficits were prevalent across the range of mild to severe TBI. Ocular injury to the retina or choroid, poorer visual acuity, and pupillary defect were associated with visual field defects. Participants with depressed visual field sensitivity reported lower visual quality of life.

CONCLUSIONS

Reliable automated perimetry can be accomplished in most patients with TBI from combat blast exposure and reveals high rates of visual field deficits, indicating that blast forces may significantly affect the eye and visual pathways.

Compass: clinical evaluation of a new instrument for the diagnosis of glaucoma

AIMS

To evaluate Compass, a new instrument for glaucoma screening and diagnosis that combines scanning ophthalmoscopy, automated perimetry, and eye tracking.

MATERIALS AND METHODS

A total of 320 human subjects (200 normal, 120 with glaucoma) underwent full ophthalmological evaluation and perimetric evaluation using the Humphrey SITA standard 24° test (HFA), and the Compass test that consisted of a full-threshold program on the central 24° with a photograph of the central 30° of the retina. A subgroup of normal subjects and glaucoma patients underwent a second Compass test during the same day in order to study test-retest variability. After exclusion of 30 patients due to protocol rules, a database was created to compare the Compass to the HFA, and to evaluate retinal image quality and fixation stability.

RESULTS

The difference in mean sensitivity between Compass and HFA was -1.02 ± 1.55 dB in normal subjects (p<0.001) and -1.01 ± 2.81 dB in glaucoma (p<0.001). Repeatability SD for the average sensitivity was 1.53 for normal subjects and 1.84 for glaucoma. Test time with the Compass was 634±96 s (607±78 for normals, 678±108 for glaucoma). Compass analysis showed the percentage of fixation within the central 1° was 86.6% in normal subjects, and 79.3% in glaucoma patients. Color image quality was sufficient for diagnostic use in >65% of cases; Image-based diagnosis was in accordance with the initial diagnosis in 85% of the subjects.

CONCLUSIONS

Based on preliminary results, Compass showed useful diagnostic characteristics for the study of glaucoma, and combined morphological information with functional data.

Comparison of regression models for serial visual field analysis

PURPOSE

Our aim was to compare fit and predictive performance effectiveness of four pointwise regression models in measuring the visual field (VF) decay rate of progression in patients with open-angle glaucoma.

METHODS

We selected Humphrey VF data of patients with open-angle glaucoma with a minimum follow-up time of 6 years. For each eye (n = 798 from 588 patients), we regressed threshold sensitivity (y) at each VF test location for the entire VF series against follow-up time (x), with four candidate first-order regression models: (1) ordinary least-squares linear regression model (y = β 0 + β 1 x); (2) nondecay exponential regression model (y = β 0 + β 1e (x) ); (3) decay exponential regression model ([Formula: see text]); (4) Tobit-censored, maximum-likelihood linear regression model (y* = [Formula: see text], ε ~ N(0, σ(2))), where x is follow-up time and y is threshold sensitivity.

RESULTS

The average [± standard deviation (SD)] baseline VF mean deviation (MD) was -8.2 (±5.5) dB, the mean follow-up was 8.7 (±1.9) years, and the number of follow-up VFs was 14.7 (±4.4). The decay exponential model was the best-fitting (42.7 % of locations) and best-forecasting (65.5 % of locations) model. The decay exponential model was the best prediction model in all categories of severity.

CONCLUSIONS

It is not clear that the ordinary least-squares linear regression model is always the favored model for fitting and forecasting VF data in patients with glaucoma. The pointwise decay exponential regression (PER) model was the best-fitting and best-predicting model across a wide range of glaucoma severity and can be readily understood by clinicians.

Baseline visual field findings in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT)

PURPOSE

To characterize visual field (VF) loss at the baseline visit and to evaluate VF quality control (QC) procedures in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT).

METHODS

The Visual Field Reading Center (VFRC) evaluated 660 baseline VFs (1320 hemifields) from 165 enrolled patients. Three readers independently classified each superior and inferior hemifield and identified any abnormalities. A subset (20%) of the hemifields was reread to evaluate within- and between-reader agreements. The QC system addressed test parameters, patient data, and shipment errors.

RESULTS

The majority (60%) of the baseline hemifields consisted of localized nerve fiber bundle-type VF loss. Approximately one-third (31.5%) of all the classifications consisted of partial arcuate defects combined with an enlarged blind spot, making this the most common type of hemifield classification. Inferior hemifield loss was greater than superior loss for both study and nonstudy eyes. Reader agreements were >90% for both inferior and superior hemifields for two out of three readers. Test-retest reliability agreement for individual readers was 95% for both hemifields. There were few QC errors with only 5.48 error points per 100-point VF.

CONCLUSIONS

The most common type of IIHTT baseline hemifield abnormality was a localized nerve fiber bundle-like defect. Localized inferior hemifield loss was more common than superior hemifield loss. Quality control and within- and between-reader agreement were excellent for the IIHTT (ClinicalTrials.gov number, NCT01003639).