Relationship between contrast sensitivity and spherical aberration: comparison of 7 contrast sensitivity tests with natural and artificial pupils in healthy eyes

Analysis of Changes in High-order Aberration and Contrast Sensitivity After Epiblepharon Surgery

PURPOSE

To investigate changes in corneal anterior high-order aberration (HOA) and contrast sensitivity (CS) before and after epiblepharon surgery.

METHODS

A retrospective observational analysis of the degree of corneal erosion, HOAs and CS was conducted in the OD and OS, respectively, before and after epiblepharon surgery. The correlations between corneal erosion, HOAs, and CS were analyzed.

RESULTS

Forty-nine patients were included in the study. Among the anterior HOAs, total HOA, coma, and trefoil showed significant improvement after surgery ( P = 0.003, P = 0.009, and P = 0.018, respectively). In the CS test, there was a significant improvement in CS after surgery at 1.1 cycles per degree (cpd) under photopic conditions, regardless of glare. Preoperative correlation analysis between HOAs and corneal erosion showed a significant positive correlation with total HOA ( P = 0.001) and coma ( P = 0.001). Preoperative correlation analysis between CS and corneal erosion showed a significant negative correlation at 1.1 cpd with glare under photopic conditions ( P = 0.049). A negative correlation was also observed between CS under mesopic and photopic conditions and total HOA both before and after surgery.

CONCLUSION

Significant improvement in corneal anterior HOAs and CS at 1.1 cpd under photopic conditions was observed after epiblepharon surgery. Total HOA of anterior cornea showed a negative correlation with CS. A decrease in HOAs and recovery of corneal erosion after epiblepharon surgery will help improve CS.

Hierarchical Bayesian modeling of contrast sensitivity functions in a within-subject design

Recent development of the quick contrast sensitivity function (qCSF) method has made it possible to obtain accurate, precise, and efficient contrast sensitivity function (CSF) assessment. To improve statistical inference on CSF changes in a within-subject design, we developed a hierarchical Bayesian model (HBM) to compute the joint distribution of CSF parameters and hyperparameters at test, subject, and population levels, utilizing information within- and between-subjects and experimental conditions. We evaluated the performance of the HBM relative to a non-hierarchical Bayesian inference procedure (BIP) on an existing CSF dataset of 112 subjects obtained with the qCSF method in three luminance conditions (Hou, Lesmes, Kim, Gu, Pitt, Myung, & Lu, 2016). We found that the average d's of the area under log CSF (AULCSF) and CSF parameters between pairs of luminance conditions at the test-level from the HBM were 33.5% and 103.3% greater than those from the BIP analysis of AULCSF. The increased d' resulted in greater statistical differences between experimental conditions across subjects. In addition, simulations showed that the HBM generated accurate and precise CSF parameter estimates. These results have strong implications for the application of HBM in clinical trials and patient care.

Measuring the Contrast Sensitivity Function in Non-Neovascular and Neovascular Age-Related Macular Degeneration: The Quantitative Contrast Sensitivity Function Test

Age-related macular degeneration (AMD) affects various aspects of visual function compromising patients' functional vision and quality of life. Compared to visual acuity, contrast sensitivity correlates better with vision-related quality of life and subjectively perceived visual impairment. It may also be affected earlier in the course of AMD than visual acuity. However, lengthy testing times, coarse sampling and resolution, and poor test-retest reliability of the existing contrast testing methods have limited its widespread adoption into routine clinical practice. Using active learning principles, the qCSF can efficiently measure contrast sensitivity across multiple spatial frequencies with both high sensitivity in detecting subtle changes in visual function and robust test-retest reliability, emerging as a promising visual function endpoint in AMD both in clinical practice and future clinical trials.

Evaluating the Performance of qVFM in Mapping the Visual Field of Simulated Observers With Eye Diseases

PURPOSE

Recently, we developed a novel active learning framework, qVFM, to map visual functions in the visual field. The method has been implemented and validated in measuring light sensitivity and contrast sensitivity visual field maps (VFMs) of normal observers. In this study, we evaluated the performance of the qVFM method in mapping the light sensitivity VFM of simulated patients with peripheral scotoma, glaucoma, age-related macular degeneration (AMD), and cataract.

METHODS

For each simulated patient, we sampled 100 locations (60 × 60 degrees) of the visual field and compared the performance of the qVFM method with a procedure that tests each location independently (the qYN method) in a cued Yes/No task. Two different switch modules, the distribution sampling method (DSM) and parameter delivering method (PDM), were implemented in the qVFM method. Simulated runs of 1,200 trials were used to compare the accuracy and precision of the qVFM-DSM, qVFM-PDM and qYN methods.

RESULTS

The qVFM method with both switch modules can provide accurate, precise, and efficient assessments of the light sensitivity VFM for the simulated patients, with the qVFM-PDM method better at detecting VFM deficits in the simulated glaucoma.

CONCLUSIONS

The qVFM method can be used to characterize residual vision of simulated ophthalmic patients. The study sets the stage for further investigation with real patients and potential translation of the method into clinical practice.

Multi-Stage Cortical Plasticity Induced by Visual Contrast Learning

Perceptual learning, the improved sensitivity via repetitive practice, is a universal phenomenon in vision and its neural mechanisms remain controversial. A central question is which stage of processing is changed after training. To answer this question, we measured the contrast response functions and electroencephalography (EEG) before and after ten daily sessions of contrast detection training. Behavioral results showed that training substantially improved visual acuity and contrast sensitivity. The learning effect was significant at the trained condition and partially transferred to control conditions. Event-related potential (ERP) results showed that training reduced the latency in both early and late ERPs at the trained condition. Specifically, contrast-gain-related changes were observed in the latency of P1, N1-P2 complex, and N2, which reflects neural changes across the early, middle, and high-level sensory stages. Meanwhile, response-gain-related changes were found in the latency of N2, which indicates stimulus-independent effect in higher-level stages. In sum, our findings indicate that learning leads to changes across different processing stages and the extent of learning and transfer may depend on the specific stage of information processing.

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

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.

Effect of age and refractive error on quick contrast sensitivity function in Chinese adults: a pilot study

PURPOSE

To evaluate the potential effect of age and refractive error on visual acuity (VA) performance and quick contrast sensitivity function (qCSF) in normal Chinese adults.

METHOD

Ninety-two subjects with normal best corrected distance VA (BCDVA) were enrolled in this pilot study. Measurements included BCDVA, best corrected near VA (BCNVA), unaided VA (UNVA), habitual spectacle-corrected near VA (SCNVA) and qCSF. For analyses, subjects were categorized into three age groups (20~40 years, 41~60 year and >60 years) and four refractive groups (hyperopia, emmetropia, myopia and high myopia). Relationships between age, refractive error, types of VA and qCSF were tested using simple and multiple linear regressions analyses.

RESULT

Mean age and refractive error of the study participants were 44.04 ± 12.68 years and -1.86 ± 2.91D, respectively. Among the stratified age groups, a hyperopic shift of refraction (-3.24 ± 2.88D vs. -1.24 ± 2.64D vs. 0.39 ± 1.42D, respectively; P < 0.001) and a reduction in BCNVA (P = 0.014), SCNVA (P < 0.001) and cut-off spatial frequency (SF) (P = 0.032) were found with increasing age. Among the four refractive groups, the SCNVA and cut-off SF of hyperopia were worse compared to the other refractive statuses (all P < 0.05). Age was significantly associated with cut-off SF (standardized β = -0.29, P = 0.005) after adjustment for SER, gender and all types of VA.

CONCLUSION

For normal Chinese adults with normal BCDVA, age was the main factor associated with CSF, which may be independent of refractive error.

A novel Bayesian adaptive method for mapping the visual field

Measuring visual functions such as light and contrast sensitivity, visual acuity, reading speed, and crowding across retinal locations provides visual-field maps (VFMs) that are extremely valuable for detecting and managing eye diseases. Although mapping light sensitivity is a standard glaucoma test, the measurement is often noisy (Keltner et al., 2000). Mapping other visual functions is even more challenging. To improve the precision of light-sensitivity mapping and enable other VFM assessments, we developed a novel hybrid Bayesian adaptive testing framework, the qVFM method. The method combines a global module for preliminary assessment of the VFM's shape and a local module for assessing individual visual-field locations. This study validates the qVFM method in measuring light sensitivity across the visual field. In both simulation and psychophysics studies, we sampled 100 visual-field locations (60° × 60°) and compared the performance of qVFM with the qYN procedure (Lesmes et al., 2015) that measured light sensitivity at each location independently. In the simulations, a simulated observer was tested monocularly for 1,000 runs with 1,200 trials/run, to compare the accuracy and precision of the two methods. In the experiments, data were collected from 12 eyes (six left, six right) of six human subjects. Subjects were cued to report the presence or absence of a target stimulus, with the luminance and location of the target adaptively selected in each trial. Both simulations and a psychological experiment showed that the qVFM method can provide accurate, precise, and efficient mapping of light sensitivity. This method can be extended to map other visual functions, with potential clinical signals for monitoring vision loss, evaluating therapeutic interventions, and developing effective rehabilitation for low vision.

Evaluation of the precision of contrast sensitivity function assessment on a tablet device

The contrast sensitivity function (CSF) relates the visibility of a spatial pattern to both its size and contrast, and is therefore a more comprehensive assessment of visual function than acuity, which only determines the smallest resolvable pattern size. Because of the additional dimension of contrast, estimating the CSF can be more time-consuming. Here, we compare two methods for rapid assessment of the CSF that were implemented on a tablet device. For a single-trial assessment, we asked 63 myopes and 38 emmetropes to tap the peak of a “sweep grating” on the tablet’s touch screen. For a more precise assessment, subjects performed 50 trials of the quick CSF method in a 10-AFC letter recognition task. Tests were performed with and without optical correction, and in monocular and binocular conditions; one condition was measured twice to assess repeatability. Results show that both methods are highly correlated; using both common and novel measures for test-retest repeatability, however, the quick CSF delivers more precision with testing times of under three minutes. Further analyses show how a population prior can improve convergence rate of the quick CSF, and how the multi-dimensional output of the quick CSF can provide greater precision than scalar outcome measures.

Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes

The contrast sensitivity function (CSF) has shown promise as a functional vision endpoint for monitoring the changes in functional vision that accompany eye disease or its treatment. However, detecting CSF changes with precision and efficiency at both the individual and group levels is very challenging. By exploiting the Bayesian foundation of the quick CSF method (Lesmes, Lu, Baek, & Albright, 2010), we developed and evaluated metrics for detecting CSF changes at both the individual and group levels. A 10-letter identification task was used to assess the systematic changes in the CSF measured in three luminance conditions in 112 naïve normal observers. The data from the large sample allowed us to estimate the test-retest reliability of the quick CSF procedure and evaluate its performance in detecting CSF changes at both the individual and group levels. The test-retest reliability reached 0.974 with 50 trials. In 50 trials, the quick CSF method can detect a medium 0.30 log unit area under log CSF change with 94.0% accuracy at the individual observer level. At the group level, a power analysis based on the empirical distribution of CSF changes from the large sample showed that a very small area under log CSF change (0.025 log unit) could be detected by the quick CSF method with 112 observers and 50 trials. These results make it plausible to apply the method to monitor the progression of visual diseases or treatment effects on individual patients and greatly reduce the time, sample size, and costs in clinical trials at the group level.

Discriminating anisometropic amblyopia from myopia based on interocular inhibition

Amblyopia screening during childhood is critical for early detection and successful treatment. In the current study, we develop and evaluate a screening method that exploits the imbalanced interocular inhibition between amblyopic and fellow eyes. In nineteen subjects with anisometropic amblyopia and twenty-two age-matched subjects with myopia, we measured the area under the contrast sensitivity functions (AUCSFs) in eight monocular conditions defined by the tested eye (left, right), patching of the untested eye (translucent, opaque), and refractive status (corrected, uncorrected). For each tested eye, we defined the inhibition index as the ratio between the AUCSF values obtained in the translucent and opaque patching conditions of the untested eye. To evaluate the screening potential of the inhibition index, we compared results from patients with amblyopia and myopia. With and without optical correction, the index was significantly lower in the amblyopic eye than in the fellow eye of the amblyopic subjects and both eyes of the myopic subjects. No significant difference was found among the two eyes of the myopic subjects and the fellow eyes of the amblyopic subjects. With the inhibition index as the predictor, a logistic regression model successfully discriminated amblyopic eyes from myopic eyes with 100% accuracy in the uncorrected condition. In the corrected condition, with the inhibition index and interocular visual acuity difference as predictors, amblyopic eyes were likewise discriminated from myopic eyes with 100% accuracy. This pattern of CSF changes, caused by the different patching modes of the untested eye, provides a potential CSF signature to discriminate anisometropic amblyopia from myopia.

Central Retinal Enrichment Supplementation Trials (CREST): design and methodology of the CREST randomized controlled trials

PURPOSE

The Central Retinal Enrichment Supplementation Trials (CREST) aim to investigate the potential impact of macular pigment (MP) enrichment, following supplementation with a formulation containing 10 mg lutein (L), 2 mg zeaxanthin (Z) and 10 mg meso-zeaxanthin (MZ), on visual function in normal subjects (Trial 1) and in subjects with early age-related macular degeneration (AMD; Trial 2).

METHODS

CREST is a single center, double-blind, randomized clinical trial. Trial 1 (12-month follow-up) subjects are randomly assigned to a formulation containing 10 mg L, 10 mg MZ and 2 mg Z (n = 60) or placebo (n = 60). Trial 2 (24-month follow-up) subjects are randomly assigned to a formulation containing 10 mg L, 10 mg MZ, 2 mg Z plus 500 mg vitamin C, 400 IU vitamin E, 25 mg zinc and 2 mg copper (Intervention A; n = 75) or 10 mg L and 2 mg Z plus 500 mg vitamin C, 400 IU vitamin E, 25 mg zinc and 2 mg copper (Intervention B; n = 75). Contrast sensitivity (CS) at 6 cycles per degree represents the primary outcome measure in each trial. Secondary outcomes include: CS at other spatial frequencies, MP, best-corrected visual acuity, glare disability, photostress recovery, light scatter, cognitive function, foveal architecture, serum carotenoid concentrations, and subjective visual function. For Trial 2, AMD morphology, reading speed and reading acuity are also being recorded.

CONCLUSIONS

CREST is the first study to investigate the impact of supplementation with all three macular carotenoids in the context of a large, double-blind, randomized clinical trial.

qCSF in clinical application: efficient characterization and classification of contrast sensitivity functions in amblyopia

PURPOSE

The qCSF method is a novel procedure for rapid measurement of spatial contrast sensitivity functions (CSFs). It combines Bayesian adaptive inference with a trial-to-trial information gain strategy, to directly estimate four parameters defining the observer's CSF. In the present study, the suitability of the qCSF method for clinical application was examined.

METHODS

The qCSF method was applied to rapidly assess spatial CSFs in 10 normal and 8 amblyopic participants. The qCSF was evaluated for accuracy, precision, test-retest reliability, suitability of CSF model assumptions, and accuracy of amblyopia screening.

RESULTS

qCSF estimates obtained with as few as 50 trials matched those obtained with 300 Ψ trials. The precision of qCSF estimates obtained with 120 and 130 trials, in normal subjects and amblyopes, matched the precision of 300 Ψ trials. For both groups and both methods, test-retest sensitivity estimates were well matched (all R > 0.94). The qCSF model assumptions were valid for 8 of 10 normal participants and all amblyopic participants. Measures of the area under log CSF (AULCSF) and the cutoff spatial frequency (cutSF) were lower in the amblyopia group; these differences were captured within 50 qCSF trials. Amblyopia was detected at an approximately 80% correct rate in 50 trials, when a logistic regression model was used with AULCSF and cutSF as predictors.

CONCLUSIONS

The qCSF method is sufficiently rapid, accurate, and precise in measuring CSFs in normal and amblyopic persons. It has great potential for clinical practice.

Bayesian adaptive estimation of the contrast sensitivity function: the quick CSF method

The contrast sensitivity function (CSF) predicts functional vision better than acuity, but long testing times prevent its psychophysical assessment in clinical and practical applications. This study presents the quick CSF (qCSF) method, a Bayesian adaptive procedure that applies a strategy developed to estimate multiple parameters of the psychometric function (A. B. Cobo-Lewis, 1996; L. L. Kontsevich & C. W. Tyler, 1999). Before each trial, a one-step-ahead search finds the grating stimulus (defined by frequency and contrast) that maximizes the expected information gain (J. V. Kujala & T. J. Lukka, 2006; L. A. Lesmes et al., 2006), about four CSF parameters. By directly estimating CSF parameters, data collected at one spatial frequency improves sensitivity estimates across all frequencies. A psychophysical study validated that CSFs obtained with 100 qCSF trials ( approximately 10 min) exhibited good precision across spatial frequencies (SD < 2-3 dB) and excellent agreement with CSFs obtained independently (mean RMSE = 0.86 dB). To estimate the broad sensitivity metric provided by the area under the log CSF (AULCSF), only 25 trials were needed to achieve a coefficient of variation of 15-20%. The current study demonstrates the method's value for basic and clinical investigations. Further studies, applying the qCSF to measure wider ranges of normal and abnormal vision, will determine how its efficiency translates to clinical assessment.