Dataset Information

Mapping the Contrast Sensitivity of the Visual Field With Bayesian Adaptive qVFM.

ABSTRACT: Current clinical evaluation, which focuses on central vision, could be improved through characterization of residual vision with peripheral testing of visual acuity, contrast sensitivity, color vision, crowding, and reading speed. Assessing visual functions in addition to light sensitivity, a comprehensive visual field map (VFM) would be valuable for detecting and managing eye diseases. In a previous study, we developed a Bayesian adaptive qVFM method that combines a global module for preliminary assessment of the VFM's shape and a local module for assessment at individual retinal locations. The method was validated in measuring the light sensitivity VFM. In this study, we extended the qVFM method to measure contrast sensitivity across the visual field. In both simulations and psychophysics, we sampled 64 visual field locations (48 x 48 deg) and compared the qVFM method with a procedure that tested each retinal location independently (qFC; Lesmes et al., 2015). In each trial, subjects were required to identify a single optotype (size: 2.5 x 2.5 deg), one of 10 filtered Sloan letters. To compare the accuracy and precision of the two methods, three simulated eyes were tested in 1,280 trials with each method. In addition, data were collected from 10 eyes (5 OS, 5 OD) of five normal observers. For simulations, the average RMSE of the estimated contrast sensitivity with the qVFM and qFC methods were 0.057 and 0.100 after 320 trials, and 0.037 and 0.041 after 1,280 trials [all in log10 units, represent as log(sensitivity)], respectively. The average SD of the qVFM and qFC estimates were 0.054 and 0.096 after 320 trials, and 0.032 and 0.041 after 1,280 trials, respectively. The within-run variability (68.2% HWCIs) were comparable to the cross-run variability (SD). In the psychophysics experiment, the average HWCI of the estimated contrast sensitivity from the qVFM and qFC methods across the visual field decreased from 0.33 on the first trial to 0.072 and 0.16 after 160, and to 0.060 and 0.10 after 320 trials. The RMSE between the qVFM and qFC estimates started at 0.26, decreased to 0.12 after 160 and to 0.11 after 320 qVFM trials. The qVFM provides an accurate, precise, and efficient mapping of contrast sensitivity across the entire visual field. The method might find potential clinical applications in monitoring vision loss, evaluating therapeutic interventions, and developing effective rehabilitation for visual diseases.

SUBMITTER: Xu P

PROVIDER: S-EPMC7358309 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Mapping the Contrast Sensitivity of the Visual Field With Bayesian Adaptive qVFM.

Xu Pengjing P Lesmes Luis A LA Yu Deyue D Lu Zhong-Lin ZL

Frontiers in neuroscience 20200707

Current clinical evaluation, which focuses on central vision, could be improved through characterization of residual vision with peripheral testing of visual acuity, contrast sensitivity, color vision, crowding, and reading speed. Assessing visual functions in addition to light sensitivity, a comprehensive visual field map (VFM) would be valuable for detecting and managing eye diseases. In a previous study, we developed a Bayesian adaptive qVFM method that combines a global module for preliminar ...[more]

PMID: 32733188

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Project description:BackgroundImpairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS).ObjectiveTo study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls.MethodsWe recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set.ResultsWe identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129-373 s). The AULCSF had better test-retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01).ConclusionHigh precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS.

Project description:Visual deficits in children that result from brain injury, including cerebral/cortical visual impairment (CVI), are difficult to assess through conventional methods due to their frequent co-occurrence with cognitive and communicative disabilities. Such impairments hence often go undiagnosed or are only determined through subjective evaluations of gaze-based reactions to different forms, colors, and movements, which limits any potential for remediation. Here, we describe a novel approach to grading visual health based on eye movements and evidence from gaze-based tracking behaviors. Our approach-the "Visual Ladder"-reduces reliance on the user's ability to attend and communicate. The Visual Ladder produces metrics that quantify spontaneous saccades and pursuits, assess visual field responsiveness, and grade spatial visual function from tracking responses to moving stimuli. We used the Ladder to assess fourteen hospitalized children aged 3 to 18 years with a diverse range of visual impairments and causes of brain injury. Four children were excluded from analysis due to incompatibility with the eye tracker (e.g., due to severe strabismus). The remaining ten children-including five non-verbal children-were tested multiple times over periods ranging from 2 weeks to 9 months, and all produced interpretable outcomes on at least three of the five visual tasks. The results suggest that our assessment tasks are viable in non-communicative children, provided their eyes can be tracked, and hence are promising tools for use in a larger clinical study. We highlight and discuss informative outcomes exhibited by each child, including directional biases in eye movements, pathological nystagmus, visual field asymmetries, and contrast sensitivity deficits. Our findings indicate that these methodologies will enable the rapid, objective classification and grading of visual impairments in children with CVI, including non-verbal children who are currently precluded from most vision assessments. This would provide a much-needed differential diagnostic and prognostic tool for CVI and other impairments of the visual system, both ocular and cerebral.

Project description:PurposeRecent 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.MethodsThresholds 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.ResultsThe 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.ConclusionsThe 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.

Dataset Information

Mapping the Contrast Sensitivity of the Visual Field With Bayesian Adaptive qVFM.

Publications

Mapping the Contrast Sensitivity of the Visual Field With Bayesian Adaptive qVFM.

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