Optometry and Vision Sciences - Research Publications
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ItemDetecting glaucoma from multi-modal data using probabilistic deep learning(FRONTIERS MEDIA SA, 2022-09-29)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.
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ItemNo Preview AvailableDeveloping a Screening Tool for Areas of Abnormal Central Vision Using Visual Stimuli With Natural Scene Statistics(ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2022-02-01)PURPOSE: Previous studies show that some visual field (VF) defects are detectable from visual search behavior; for example, when watching video. Here, we developed and tested a VF testing approach that measures the number of fixations to find targets on a background with spatial frequency content similar to natural scenes. METHODS: Twenty-one older controls and 20 people with glaucoma participated. Participants searched for a Gabor (6 c/°) that appeared in one of 25 possible locations within a 15° (visual angle) 1/f noise background (RMS contrast: 0.20). Procedure performance was assessed by calculating sensitivity and specificity for different combinations of control performance limits (p = 95%, 98%, 99%), number of target locations with fixations outside control performance limits (k = 0 to 25) and number of repeated target presentations (n = 1 to 20). RESULTS: Controls made a median of two to three fixations (twenty-fifth to seventy-fifth percentile: two to four) to locate the target depending on location. A VF was flagged "abnormal" when the number of fixations was greater than the p = 99% for k = 3 or more locations with n = 2 repeated presentations, giving 85% sensitivity and 95.2% specificity. The median test time for controls was 85.71 (twenty-fifth to seventy-fifth percentile: 66.49-113.53) seconds. CONCLUSION: Our prototype test demonstrated effective and efficient screening of abnormal areas in central vision. TRANSLATIONAL RELEVANCE: Visual search behavior can be used to detect central vision loss and may produce results that relate well to performance in natural visual environments.
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ItemNo Preview AvailableDo Additional Testing Locations Improve the Detection of Macular Perimetric Defects in Glaucoma?(ELSEVIER SCIENCE INC, 2021-11-18)PURPOSE: To evaluate the ability of additional central testing locations to improve detection of macular visual field (VF) defects in glaucoma. DESIGN: Prospective cross-sectional study. PARTICIPANTS: Four hundred forty healthy people and 499 patients with glaucomatous optic neuropathy (GON) were tested with a fundus tracked perimeter (CMP; CenterVue) using a 24-2 grid with 12 additional macular locations (24-2+). METHODS: Glaucomatous optic neuropathy was identified based on expert evaluation of optic nerve head photographs and OCT scans, independently of the VF. We defined macular defects as locations with measurements outside the 5% and 2% normative limits on total deviation (TD) and pattern deviation (PD) maps within the VF central 10°. Classification was based on the total number of affected macular locations (overall detection) or the largest number of affected macular locations connected in a contiguous cluster (cluster detection). Criteria based on the number of locations and cluster size were used to obtain equivalent specificity between the 24-2 grid and the 24-2+ grids, calculated using false detections in the healthy cohort. Partial areas under the receiver operating characteristic curve (pAUCs) were also compared at specificities of 95% or more. MAIN OUTCOME MEASURES: Matched specificity comparison of the ability to detect glaucomatous macular defects between the 24-2 and 24-2+ grids. RESULTS: At matched specificity, cluster detection identified more macular defects with the 24-2+ grid compared with the 24-2 grid. For example, the mean increase in percentage of detection was 8% (95% confidence interval [CI], 5%-11%) and 10% (95% CI, 7%-13%) for 5% TD and PD maps, respectively, and 5% (95% CI, 2%-7%) and 6% (95% CI, 4%-8%) for the 2% TD and PD maps, respectively. Good agreement was found between the 2 grids. The improvement measured by pAUCs was also significant but generally small. The percentage of eyes with macular defects ranged from about 30% to 50%. Test time for the 24-2+ grid was longer (21% increase) for both cohorts. Between 74% and 98% of defects missed by the 24-2 grid had at least 1 location with sensitivity of < 20 dB. CONCLUSIONS: Visual field examinations with additional macular locations can improve the detection of macular defects in GON modestly without loss of specificity when appropriate criteria are selected.
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ItemA Method for Reducing the Number of Presentations in Perimetric Test Procedures.(Association for Research in Vision and Ophthalmology (ARVO), 2022-04-01)PURPOSE: To introduce a new method (ARBON) for decreasing the test time of psychophysical procedures and examine its application to perimetry. METHODS: ARBON runs in parallel with an existing psychophysical procedure injecting occasional responses of seen or unseen into that procedure. Using computer simulation to mimic human responses during perimetry, we assess the performance of ARBON relative to an underlying test procedure and a version of that procedure truncated to be faster. Simulations used 610 normal eyes (age 20 to 80 years) and 163 glaucoma eyes (median mean deviation = -1.81 dB, 5th percentile = +2.14 dB, 95th percentile = -22.55 dB). Outcome measures were number of presentations and mean absolute error in threshold estimation. We also examined the probability distribution of measured thresholds. RESULTS: ARBON and the Truncated procedure reduced presentations by 16% and 18%, respectively. Mean error was increased by 8% to 10% for the Truncated procedure but decreased by 5% to 7% for ARBON. The probability distributions of measured thresholds using ARBON overlapped with the Underlying procedure by over 80%, whereas the Truncated procedure overlapped by 50%. CONCLUSIONS: ARBON offers a principled method for reducing test time. ARBON can be added to any existing psychophysical procedure without requiring any change to the logic or parameters controlling the procedure, resulting in distributions of measured thresholds similar to those of the underlying procedure. TRANSLATIONAL RELEVANCE: ARBON can be added to a perimetry test procedure to speed up the test while largely preserving the distribution of returned sensitivities, thus producing normative data similar to the data for the original, underlying perimetric test.
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ItemThe Open Perimetry Initiative: A framework for cross-platform development for the new generation of portable perimeters(ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2022-04-01)The Open Perimetry Initiative was formed in 2010 with the aim of reducing barriers to clinical research with visual fields and perimetry. Our two principal tools are the Open Perimetry Interface (OPI) and the visualFields package with analytical tools. Both are fully open source. The OPI package contains a growing number of drivers for commercially available perimeters, head-mounted devices, and virtual reality headsets. The visualFields package contains tools for the analysis and visualization of visual field data, including methods to compute deviation values and probability maps. We introduce a new frontend, the opiApp, that provides tools for customization for visual field testing and can be used as a frontend to run the OPI. The app can be used on the Octopus 900 (Haag-Streit), the Compass (iCare), the AP 7000 (Kowa), and the IMO (CREWT) perimeters, with permission from the device manufacturers. The app can also be used on Android phones with virtual reality headsets via a new driver interface, the PhoneHMD, implemented on the OPI. The use of the tools provided by the OPI library is showcased with a custom static automated perimetry test for the full visual field (up to 50 degrees nasally and 80 degrees temporally) developed with the OPI driver for the Octopus 900 and using visualFields for statistical analysis. With more than 60 citations in clinical and translational science journals, this initiative has contributed significantly to expand research in perimetry. The continued support of researchers, clinicians, and industry are key in transforming perimetry research into an open science.
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ItemIncreased Depth, Reduced Extent, and Sharpened Edges of Visual Field Defects Measured by Compass Fundus Perimeter Compared to Humphrey Field Analyzer(ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2021-10-01)PURPOSE: The purpose of this study was to compare visual field results of the COMPASS fundus perimeter (CMP) and the Humphrey Field Analyzer (HFA) in the same eyes; to compare structure-function concordance between circumpapillary retinal nerve fiber layer (Cp-RNFL) profiles and the two perimetry results; and to evaluate whether differences between the two results reflect postulated advantages of real-time eye movement compensation during perimetry. METHODS: We retrospectively analyzed 24-2 visual field data measured with CMP and HFA together with Cp-RNFL optical coherence tomography (OCT) scan data from 95 eyes of 65 people with glaucoma. We defined visual field locations with total deviation (TD) less than -5 dB as defective. The CMP and HFA fields were compared on measures of: spatial extent (number of defective locations); depth (TD values); and sharpness of scotomata edges (maximum TD difference between defective locations and their neighbors). Structure-function concordance between Cp-RNFL profile and respective visual field was also compared. RESULTS: Compared to the HFA, scotomata measured by CMP were of reduced spatial extent (mean difference = -3.14 locations, p < 0.001), greater depth (median TD of CMP = -17 dB versus HFA = -13 dB, p = 0.029) and steeper edges (median of maximum TD difference of CMP = 10.6 dB versus HFA = 6 dB, p < 0.001). Structure-function concordance between Cp-RNFL profile and either visual field were comparable despite the reduced scotoma spatial extent measured by CMP. CONCLUSIONS: Glaucomatous visual fields measured by CMP displayed characteristics consistent with expected effects of using real-time eye movement compensation technology compared to the widely used HFA. TRANSLATIONAL RELEVANCE: Glaucomatous visual field defects measured by the CMP are more localized, deeper, and steeper than those of the HFA.
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ItemOptic nerve tissue displacement during mild intraocular pressure elevation: its relationship to central corneal thickness and corneal hysteresis(WILEY, 2018-07-01)PURPOSE: To determine the extent to which (1) optic nerve tissue is displaced following mild acute elevation of intraocular pressure, and (2) clinically accessible measures at the anterior eye can be used as a surrogate for such displacements. METHODS: We imaged the optic disc of 21 healthy subjects before and after intraocular pressure (IOP) elevation of ~10 mmHg delivered by ophthalmodynamometry. Steady-state tissue displacement during IOP elevation was assessed axially from OCT data, and laterally from SLO data. Recovery from IOP elevation was assessed by tracking a single vertical B-scan through the cup centre. Anatomical structures were demarcated by three masked clinicians to determine lateral shifts for temporal cup edge and central disc vessels, and axial shifts of disc surface and anterior lamina cribrosa. Spatial maps of deformation were constructed within the demarcated cup and disc to assess within-tissue displacement. Measured displacements were correlated with corneal hysteresis, corneal thickness, and IOP. RESULTS: The temporal cup edge moved more temporally with higher baseline IOP (R2 = 0.33, p = 0.006) and with lesser elevation of IOP (R2 = 0.43, p = 0.001); it moved more superiorly for thinner corneas (R2 = 0.35, p = 0.007). Thinner corneas also produced less within-cup deformation, relative to that of the disc (R2 = 0.39, p = 0.004). Axial displacement of the lamina and lateral displacement of vessels were often substantial (lamina 20 ± 15 μm, range 1-60 μm; vessels 37 ± 25 μm, range 2-102 μm) but did not correlate with measured parameters. Recovery from IOP elevation did not take more than 300-400 ms in any subject. CONCLUSIONS: Mild acute elevation of IOP produces large and rapidly reversible shifts in optic nerve tissue in young, healthy eyes. The resulting degree, direction and spatial distribution of cup movement are associated with IOP status and corneal thickness, but not corneal hysteresis.
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ItemImproving Personalized Structure to Function Mapping From Optic Nerve Head to Visual Field.(Association for Research in Vision and Ophthalmology, 2021-01-08)Purpose: Maps are required to relate visual field locations to optic nerve head regions. We compare individualized structure-to-function mapping (CUSTOM-MAP) to a population-derived mapping schema (POP-MAP). Methods: Maps were compared for 118 eyes with glaucomatous field loss, circumpapillary retinal nerve fiber layer (cpRNFL) thickness measured using spectral domain optical coherence tomography (OCT), and two landmarks: the optic nerve head (ONH) position relative to the fovea and the temporal raphe angle. Locations with visual field damage (total deviation < -6 dB) were mapped to 30° ONH sectors centered on the angle given by each mapping schema. The concordance between damaged function and damaged structure was determined per location for various cpRNFL damage probability levels, with the number of concordant locations divided by the total number of damaged field locations providing a concordance ratio per eye. Results: For the strictest concordance criteria (minimum cpRNFL thickness < 1% of normal), CUSTOM-MAP had higher mean concordance ratio than POP-MAP (60.5% c.f. 57.0% paired Wilcoxon, P = 0.005), with CUSTOM-MAP having a higher ratio in 43 eyes and POP-MAP having a higher ratio in 21 eyes. For all cpRNFL probability levels <20% of normal, more locations concorded for CUSTOM-MAP than POP-MAP. Inspection of the spatial patterns of differences revealed that CUSTOM-MAP often performed better in the arcuate regions, whereas POP-MAP had benefits inferior to the macula. Conclusions: Anatomic parameters required for individualized structure-function mapping are readily measured with OCT and can provide improved concordance for some eyes. Translational Relevance: Personalizing structure-function mapping may improve concordance between these measures. We provide a web-based tool for creating customized maps.
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ItemEffects of Criterion Bias on Perimetric Sensitivity and Response Variability in Glaucoma(ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2021-01-01)PURPOSE: The purpose of this study was to isolate and quantify the effects of observer response criterion on perimetric sensitivity, response variability, and maximum response probability. METHODS: Twelve people with glaucoma were tested at three locations in the visual field (age = 47-77 years, mean deviation = -0.61 to -14.54 dB, test location Humphrey field analyzer [HFA] sensitivities = 1 to 30 dB). Frequency of seeing (FoS) curves were measured using a method of constant stimuli with two response paradigms: a "yes-no" paradigm similar to static automated perimetry and a criterion-free two interval forced choice (2IFC) paradigm. Comparison measures of sensitivity, maximum response probability, and response variability were derived from the fitted FoS curves. RESULTS: Sensitivity differences between the tasks varied widely (range = -11.3 dB to 21.6 dB) and did not correlate with visual field sensitivity nor whether the visual field location was in an area of steep sensitivity gradient within the visual field. Due to the wide variation in differences between the methods, there was no significant difference in mean sensitivity between the 2IFC task relative to the yes-no task, but a trend for higher sensitivity (mean = 1.9 dB, SD = 6.0 dB, P = 0.11). Response variability and maximum response probability did not differ between the tasks (P > 0.99 and 0.95, respectively). CONCLUSIONS: Perimetric sensitivity estimates are demonstrably altered by observer response criterion but the effect varies widely and unpredictably, even within a single test. Response bias should be considered a factor in perimetric test variability and when comparing sensitivities to nonperimetric data. TRANSLATIONAL RELEVANCE: The effect of response criterion on perimetric response variability varies widely and unpredictably, even within a single test.
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ItemIncreasing the Spatial Resolution of Visual Field Tests Without Increasing Test Duration: An Evaluation of ARREST(Association for Research in Vision and Ophthalmology, 2020-12)Purpose: The Australian Reduced Range Extended Spatial Test (ARREST) approach was designed to improve visual field spatial resolution while maintaining a similar test duration to clinically used testing algorithms. ARREST does not completely threshold visual field locations with sensitivity < 17 dB, and uses the presentations saved to test new locations in areas of steep gradient within the visual field. Previous assessments of ARREST's performance have used computer simulation. In this study, we cross-sectionally assessed the performance of ARREST in people with visual field loss. Methods: We tested 23 people with glaucoma (mean age: 71 ± 8 years) with established visual field loss. Three visual field procedures were performed using the Open Perimetry Interface: cZEST and ARREST on the Octopus 900 perimeter (Haag-Streit AG, Switzerland), and a reference standard (best available estimate [BAE]) on the Compass perimeter (CenterVue SpA, Italy). ARREST was compared against the cZEST and the BAE. Results: On average, ARREST added seven new locations (range = 0-15) to a visual field test. There was no significant difference in the number of stimulus presentations between procedures (mean = 259 ± 25 [ARREST] vs. 261 ± 25 [cZEST], P = 0.78). In classifying threshold values < 17 dB, ARREST performed similarly when compared against BAE. Conclusions: This study provides empirical evidence to support conclusions from previous computer simulations that ARREST can be used to increase spatial sampling in regions of interest without increasing test time. Translational Relevance: ARREST is a new approach that augments current visual field testing procedures to provide better spatial description of visual field defects without increasing test duration.