Ophthalmic Surgery, Lasers and Imaging Retina

Clinical Science 

Measuring Contrast Sensitivity Function With Active Learning in Retinal Vein Occlusion: A New Endpoint of Visual Function

Rebecca F. Silverman, MD; Megan Kasetty, MD; Filippos Vingopoulos, MD; Raviv Katz, MSc; June Cho, BS; Luis Andres Lesmes, PhD; David N. Zacks, MD, PhD; Leo A. Kim, MD, PhD; John B. Miller, MD

Abstract

BACKGROUND AND OBJECTIVE:

To characterize contrast sensitivity function (CSF) in patients with retinal vein occlusion (RVO) compared to age-matched controls using novel computerized contrast sensitivity (CS) testing with active learning algorithms.

PATIENTS AND METHODS:

CSF was prospectively measured in RVO patients with visual acuity (VA) greater than 20/200 and age-matched controls using the novel Manifold Contrast Vision Meter implementing quantitative CSF testing. Outcomes included area under the Log CSF (AULCSF), contrast acuity (CA), and CS thresholds at 1, 1.5, 3, 12, and 18 cycles per degree (cpd). A sub-analysis was performed on RVO eyes with good acuity (VA ≥ 20/30).

RESULTS:

Twenty-two eyes with RVO and 63 control eyes were included. Mean AULCSF (± standard deviation) in RVO eyes was 0.817 (0.28) compared to 1.217 (0.28) in controls (P < .0001). Mean contrast acuity in the RVO group was 1.054 (0.19) versus 1.286 ± 0.16 in controls (P < .0001). For individual spatial frequencies, CS loss at 6.0 cpd was most prominent in the RVO group. In 10 RVO eyes with VA of 20/30 or greater, mean AULCSF was 0.978 versus 1.217 in control eyes. (P = .008).

CONCLUSIONS:

CSF in eyes with RVO was found to be significantly reduced compared to age-matched controls. CSF seems to be a promising visual function endpoint with potential applications in clinical practice and future clinical trials.

[Ophthalmic Surg Lasers Imaging Retina. 2020;51:392–400.]

Abstract

BACKGROUND AND OBJECTIVE:

To characterize contrast sensitivity function (CSF) in patients with retinal vein occlusion (RVO) compared to age-matched controls using novel computerized contrast sensitivity (CS) testing with active learning algorithms.

PATIENTS AND METHODS:

CSF was prospectively measured in RVO patients with visual acuity (VA) greater than 20/200 and age-matched controls using the novel Manifold Contrast Vision Meter implementing quantitative CSF testing. Outcomes included area under the Log CSF (AULCSF), contrast acuity (CA), and CS thresholds at 1, 1.5, 3, 12, and 18 cycles per degree (cpd). A sub-analysis was performed on RVO eyes with good acuity (VA ≥ 20/30).

RESULTS:

Twenty-two eyes with RVO and 63 control eyes were included. Mean AULCSF (± standard deviation) in RVO eyes was 0.817 (0.28) compared to 1.217 (0.28) in controls (P < .0001). Mean contrast acuity in the RVO group was 1.054 (0.19) versus 1.286 ± 0.16 in controls (P < .0001). For individual spatial frequencies, CS loss at 6.0 cpd was most prominent in the RVO group. In 10 RVO eyes with VA of 20/30 or greater, mean AULCSF was 0.978 versus 1.217 in control eyes. (P = .008).

CONCLUSIONS:

CSF in eyes with RVO was found to be significantly reduced compared to age-matched controls. CSF seems to be a promising visual function endpoint with potential applications in clinical practice and future clinical trials.

[Ophthalmic Surg Lasers Imaging Retina. 2020;51:392–400.]

Introduction

Retinal vein occlusion (RVO) is the second most common retinal vascular disease after diabetic retinopathy and can lead to severe visual loss.1,2 The anatomic location of the occlusion and the affected regions of the retina divides RVO into central RVO (CRVO)3 and branch RVO (BRVO).4 RVOs can cause retinal ischemia, neovascularization, vitreous hemorrhage, retinal traction, and macular edema.5 In the presence of macular edema in RVO, intravitreal injections of anti-vascular endothelial growth factor (VEGF) have been shown to improve visual acuity (VA) and resolve the macular edema on optical coherence tomography (OCT).6,7 Yet, standard letter acuity alone is insensitive to early stages of eye diseases and progressive declines in functional vision8–10 and does not always accurately reflect the patient's self-assessment of their visual function. Even patients with 20/20 VA will still often have subjective visual complaints.11

The definition of clinically meaningful changes in vision is constrained by what is clinically measurable at baseline and after therapeutic intervention. Thus, employing better visual function metrics would aid in the detection of subtle changes in visual function that are noted by patient and evaluate our treatment regimes.

Contrast sensitivity (CS) quantifies the lightness or darkness needed to identify a target against its background.12 Compared to VA, CS function (CSF) seems to correlate better with real-world everyday activities including mobility,13 target and face identification,14 driving,15,16 walking,17 and reading,18,19 as well as subjectively perceived visual impairment.20–22 Further, CS has been shown to be impaired earlier in the course of neurodegenerative ocular pathologies when acuity is still unaffected,9,10 the latter often under-estimating the onset and/or severity of visual impairment.23–25

Despite its promising role in visual function assessment, the practical constraints limiting the sensitivity and/or precision of most CS testing methods have thus far prevented wider adoption of CSF in clinical practice and clinical trials so far. Conventional laboratory CSF testing with many possible combinations of spatial frequency and contrast is too time-consuming,26 whereas older CS tests like the Pelli-Robson chart27 use coarse sampling that operates only in one spatial frequency,28 thus limiting the test's sensitivity to detect subtle changes and identify frequency-specific deficits.29,30 Current clinically available CSF tests that evaluate both the spatial frequency and contrast are typically pre-printed letter charts, such as the Vistech CS chart or the Functional Acuity Contrast Test (Vision Sciences Research Corporation, San Ramon, CA), which exhibit poor range and resolution for sampling target contrast and frequency12,31,32 and poor test-retest reliability.31,33

Lesmes et al. introduced the qCSF method, which proposed a Bayesian active learning algorithm that maximizes information extraction over a very large set of possible stimuli, and reduced the number of trials to reliably estimate the CSF from several hundreds using traditional methods to several dozens and the respective time for test completion to 2 to 5 minutes.34 The qCSF estimates the CSF's global shape, using test stimuli that are spatially filtered optotypes that modulate both frequency and contrast, thus enabling the efficient testing of contrast sensitivity across multiple spatial frequencies in parallel.35

The qCSF has shown both great test-retest reliability and sensitivity in detecting changes of visual functions.36 After being applied to basic studies of vision,37,38 the qCSF computational approach was commercialized in a novel clinical device, the Manifold Contrast Vision Meter (Adaptive Sensory Technology [AST]; San Diego, CA)35 and used to measure CSF in several clinical populations including amblyopia,39,40 multiple sclerosis,22 dry age-related macular degeneration,41 central serous chorioretinopathy,42 glaucoma,43 retinal detachment, early diabetic retinopathy,44 and aging.45

The current study evaluates the potential of qCSF as a visual function endpoint that can provide the sensitive and precise signals required to initiate and track ocular diseases treatment over time in the clinical practice and provide a potential endpoint for future clinical trials. To our knowledge, there are currently no studies investigating CSF with the qCSF method in RVO. We herein present an initial prospective observational study employing the qCSF algorithm on the AST platform to compare CSF in RVO patients with age-matched controls.

Patients and Methods

This is a prospective, observational study approved by the Massachusetts Eye and Ear (MEE) Institutional Review Board. It was conducted in accordance with Health Insurance Portability and Accountability Act requirements and the tenets of the Declaration of Helsinki. Written informed consent was obtained from all participants.

Inclusion and Exclusion Criteria

We recruited patients from the retina service at two MEE locations. Patients were eligible for the study if they had at least one eye with nonischemic central or branch RVO and VA better than 20/200 in the affected eye at the time of CSF testing. Exclusion criteria included any other ocular disease originating in the retina, cornea, or optic nerve. Patients were excluded if they had prior surgery in the study eye or cataract status more significant than 1+ nuclear sclerosis as determined by an ophthalmologist.

Clinical Assessment

All patients underwent a complete ophthalmologic examination by a board-certified ophthalmologist, with measurement of intraocular pressure and Snellen VA by an ophthalmic technician. Following the work up, patients underwent CS testing, (see below for protocol). After CS testing, patients were dilated with phenylephrine/tropicamide and imaged with Spectralis spectral-domain optical coherence tomography (SD-OCT) (Heidelberg Engineering, Heidelberg, Germany).

CSF Testing Protocol

CS testing was performed at two MEE locations in standardized environments. Each eye was tested separately with the fellow eye occluded. In addition to a computer for qCSF computations, the Manifold Contrast device comprised an LED screen with a luminance of 95.4 cd/m2 and HD resolution of 1920 x 1080 pixels. CS testing used 10 filtered Sloan letters with 19 possible spatial frequencies (evenly distributed in log space from 1.19 to 30.95 cycles per degree [cpd]) and 128 possible contrasts (evenly distributed in log space from 0.002 to 1) to define the first of three filtered Sloan letters presented on each screen, with contrast decreasing from left to right. An adaptive Bayesian active learning algorithm used a one-step-ahead search to select contrast-spatial frequency combinations that maximized information gain. The active learning approach, which enables global estimation of the function's shape rather than local, piecemeal estimation at single frequencies, provides higher-resolution sampling and corresponding reduction in test-retest variability.36 Hence, only 25 stimuli trials needed to be presented for each eye in order to estimate the broad metric provided by the area under the logarithm of contrast sensitivity function (AULCSF). The duration for each test was approximately 5 to 10 minutes. Patients verbally reported the three letters presented on each screen to the examiner, who operated the test with a handheld tablet, recording “correct,” “incorrect,” or “no response.” The data from the 25 trials constructs a CSF curve along a spatial frequency range of 1 cpd to 18 cpd. This yielded the AULCSF, integrated from 1.5 to 18 cpd, which represents a fundamental measure of spatial vision.34 Outcomes measures included AULCSF, contrast acuity (CA), and CS thresholds at 1, 1.5, 3, 12, and 18 cpd. When patients were treated for macular edema with anti-VEGF injections, a repeat visit with CSF testing was used to evaluate the treatment effect. The patients in this cohort did not receive any treatment for macular edema aside from anti-VEGF injections.

Statistical Analysis

Data analysis was completed using SAS software, version 9.4 (SAS Institute, Cary, NC). The study population demographics were summarized with traditional descriptive methods such as mean and standard deviation. Comparisons between the RVO and control groups were assessed with Mann Whitney U test for age and VA, and chi-squared test for sex and lens status. Snellen VA was converted to logarithm of minimum angle of resolution (logMAR) for analysis. A mixed-effect linear model was used to account for correlation among eyes, as one participant had both eyes included in this study. When comparing RVO with VA better than or equal to 20/30 to controls, non-parametric analysis was used given the small sample size. A P value of less than .05 was considered statistically significant.

Results

Study Population

We included 85 eyes of 84 subjects, with 22 eyes (26%) belonging to patients with RVO and 63 controls (74%). Of the RVO eyes, 10 were BRVO (45%), 11 were CRVO (50%), and one was HRVO (5%). The overall demographics are reported in Table 1. The average age of RVO patients was 60 years ± 12 years, and the average age for controls was 55 years ± 12 years (P = .06). Eight RVO patients were female (38%), with a similar gender distribution in the control group of 27 female (43%). The mean log-MAR VA was 0.19 ± 0.14 for the RVO group compared to 0.03 ± 0.06 in controls (P < .0001). Four RVO eyes were pseudophakic (18%) compared to 13 control eyes (21%). In RVO eyes, the time from initial presentation to CSF testing ranged from 2 weeks to 2.5 years (average 42 weeks).

Patient Demographics

Table 1:

Patient Demographics

Mean Contrast Sensitivity Outcome Measures in RVO Eyes Versus Control

On average, eyes with RVO showed a statistically significant reduction in letter VA, AULCSF, and contrast acuity (Table 2). Contrast sensitivity reductions were seen at all spatial frequencies (Figure 1). Average AULCSF in the RVO group was 0.817 ± 0.28 compared to 1.217 ± 0.28 in controls (P < .0001). Average contrast acuity in the RVO group was 1.054 ± 0.19 and in controls was 1.286 ± 0.16 (P < .0001). The CS reduction in the RVO group was most significant at 6.0 cpd (Snellen equivalent of 20/100). At this spatial frequency, average CS was 0.726 ± 0.40 in RVO eyes and 1.222 ± 0.31 in control eyes (P < .0001).

Mean Contrast Sensitivity Outcome Measures in RVO and Control

Table 2:

Mean Contrast Sensitivity Outcome Measures in RVO and Control

Contrast sensitivity functions (CSFs) present contrast sensitivity (reciprocal of log contrast threshold) as a function of spatial frequency (optotype size). Average CSFs are presented for eyes with retinal vein occlusion (RVO) (square), eyes with RVO and good visual acuity (VA) (triangles), or eyes from age-matched controls (circle).

Figure 1.

Contrast sensitivity functions (CSFs) present contrast sensitivity (reciprocal of log contrast threshold) as a function of spatial frequency (optotype size). Average CSFs are presented for eyes with retinal vein occlusion (RVO) (square), eyes with RVO and good visual acuity (VA) (triangles), or eyes from age-matched controls (circle).

Additionally, we did a subgroup analysis of 10 RVO eyes with “good” letter acuity, which we defined as VA better than or equal to 20/30. Compared to controls, there was no statistically significant difference in lens status, sex, or age. Average logMAR VA was worse in the RVO group (0.059) compared to controls (0.024) (P = .0003). Similarly, there was a significant reduction in CS in RVO eyes compared to controls, including AULCSF, contrast acuity, and CS thresholds at 3 cpd, 6 cpd, 12 cpd, and 18 cpd (Table 3).

Mean Contrast Sensitivity Outcome Measures in RVO With VA ≤ 20/30 and Control

Table 3:

Mean Contrast Sensitivity Outcome Measures in RVO With VA ≤ 20/30 and Control

Contrast Sensitivity Outcomes in Patients Who Were Treated for Macular Edema With Anti-VEGF

Change in CS was assessed in relation to structural improvement of the retina, as seen on SD-OCT. All 21 patients, one with bilateral pathologies, in this subset received anti-VEGF injections and most underwent repeat qCSF testing at multiple clinic visits. Over the course of qCSF testing, five eyes showed significant improvement in macular structure due to resolution or near resolution of edema. Of these five eyes, four were patients who were treatment-naïve on first test. In this small group of treatment-naïve eyes, CSF was compared before and after improvement in retinal structure. All patients showed an improvement in VA, AULCSF, and CS at 1.5, 3, and 6 cpd (Figure 2). There was a significant improvement in AULCSF of 0.523 log units (P = .0001), compared to a 0.144 log unit increase in VA (P = .0053). The most significant improvement in CS was seen at 12 cpd, followed by 6 cpd (Figure 3). An example of one patient's improvement in retinal structure and CSF curves can be seen in Figure 4.

Comparing visual acuity (VA) and contrast sensitivity (CS) treatment effects. Visual gains, for acuity and contrast sensitivity, are presented for four patients showing retinal fluid resolution on optical coherence tomography following anti-vascular endothelial growth factor injections. Gains are presented for VA (left, dark bar), in addition to contrast sensitivity changes measured at six spatial frequencies that range from larger (1 cycle per degree [cpd]; approximately 20/600) to smaller optotype sizes (18 cpd; approximately 20/32). Note that the largest and most consistent visual gains are observed at intermediate frequencies (3 to 12 cpd), which correspond to optotype sizes of 20/50 to 20/200.

Figure 2.

Comparing visual acuity (VA) and contrast sensitivity (CS) treatment effects. Visual gains, for acuity and contrast sensitivity, are presented for four patients showing retinal fluid resolution on optical coherence tomography following anti-vascular endothelial growth factor injections. Gains are presented for VA (left, dark bar), in addition to contrast sensitivity changes measured at six spatial frequencies that range from larger (1 cycle per degree [cpd]; approximately 20/600) to smaller optotype sizes (18 cpd; approximately 20/32). Note that the largest and most consistent visual gains are observed at intermediate frequencies (3 to 12 cpd), which correspond to optotype sizes of 20/50 to 20/200.

Comparing visual acuity (VA) and contrast sensitivity (CS) treatment effects. To evaluate the concurrent treatment effects that follow anti-vascular endothelial growth factor injections, visual gains for VA (X-axis) are co-plotted against gains for contrast sensitivity (CS) measured at two low (open) and two intermediate (filled) spatial frequencies. Three concentric circles mark the visual gain regions of one, two, and three steps in acuity and contrast, defined in logMAR or logCS (0.10, 0.20, and 0.30 log10 units). The main diagonal represents treatment profile of equal gains in VA and CS; the gray-shaded region marks a treatment profile of large meaningful CS changes (> 0.30 logCS), which are greater than concurrent VA gains. Note how frequencies of 3 cycles per degree (cpd) and 6 cpd (ie, 20/200 and 20/100) provide an opportunity to observe large treatment effects that cannot be observed in VA testing alone.

Figure 3.

Comparing visual acuity (VA) and contrast sensitivity (CS) treatment effects. To evaluate the concurrent treatment effects that follow anti-vascular endothelial growth factor injections, visual gains for VA (X-axis) are co-plotted against gains for contrast sensitivity (CS) measured at two low (open) and two intermediate (filled) spatial frequencies. Three concentric circles mark the visual gain regions of one, two, and three steps in acuity and contrast, defined in logMAR or logCS (0.10, 0.20, and 0.30 log10 units). The main diagonal represents treatment profile of equal gains in VA and CS; the gray-shaded region marks a treatment profile of large meaningful CS changes (> 0.30 logCS), which are greater than concurrent VA gains. Note how frequencies of 3 cycles per degree (cpd) and 6 cpd (ie, 20/200 and 20/100) provide an opportunity to observe large treatment effects that cannot be observed in VA testing alone.

Correspondence of structural and functional improvements in one patient. Contrast sensitivity (CS) functions and optical coherence tomography images are presented for one eye showing substantial fluid resolution following an anti-vascular endothelial growth factor (VEGF) injection. Visual acuity (VA) testing demonstrated a treatment effect that was less than 2 lines: (from 20/30+2 to 20/20). Left: CS functions corresponding to before (A) and after (B) treatment injection. Relative to VA gains (< 0.20 logMAR), the CS gains are substantial and meaningful with > 0.60 logCS improvement for frequencies in the range of cycles per degree (cpd) to 18 cpd. Right: Significant macular edema present in treatment-naive eye of one patient (A) and near resolution of macular edema following anti-VEGF treatment (B).

Figure 4.

Correspondence of structural and functional improvements in one patient. Contrast sensitivity (CS) functions and optical coherence tomography images are presented for one eye showing substantial fluid resolution following an anti-vascular endothelial growth factor (VEGF) injection. Visual acuity (VA) testing demonstrated a treatment effect that was less than 2 lines: (from 20/30+2 to 20/20). Left: CS functions corresponding to before (A) and after (B) treatment injection. Relative to VA gains (< 0.20 logMAR), the CS gains are substantial and meaningful with > 0.60 logCS improvement for frequencies in the range of cycles per degree (cpd) to 18 cpd. Right: Significant macular edema present in treatment-naive eye of one patient (A) and near resolution of macular edema following anti-VEGF treatment (B).

Discussion

Active learning in the current study enabled CSF testing in RVO eyes in a sensitive and precise way with potential for clinical practice. In our cohort, we found eyes with RVO, relative to age-matched controls, demonstrated statistically significant CS reduction at all spatial frequencies, contrast acuity, and the broad measure provided by the AULCSF.

Unlike older CS tests like the Pelli-Robson chart27 that use coarse quantization and sampling operating only in one spatial frequency,28 the qCSF active learning method measures the CSF in many different spatial frequencies,35 allowing for identification of disproportionate reductions at specific spatial frequencies or global changes specific to the type of retinal disease. Current clinically available CSF tests that evaluate both the spatial frequency and contrast are typically pre-printed letter charts12,31,32 with poor range of sampling and poor test-retest reliability.32,33 In the presented RVO cohort employing the qCSF active learning method, reduction in CS was most significant at 6 cpd, and the most significant improvement in RVO eyes with resolved macular edema following anti-VEGF injections was observed at 12 cpd and 6 cpd. Of note, CS threshold at 6 cpd has been found to be the best predictor of road sign and object detection and identification, hence directly affecting patients' everyday life.34 This builds upon prior reports suggesting CS to be better correlated with real-world everyday activities and subjective perception of visual function.9,13–21

In clinical practice, a visual function metric more sensitive to subtle changes than VA would be particularly valuable in detecting subtle subjective visual impairment noted by the patient and subsequently better guide our clinical judgement on initiating and evaluating our therapeutic interventions. CS has been shown to be impaired earlier in the course of neurodegenerative ocular pathologies when acuity is still unaffected,9,10 whereas VA has been shown to often underestimate the onset and/or severity of visual impairment.23–25 In our subgroup analysis of the RVO eyes with VA 20/30 or better, CS was significantly reduced compared to controls, including AULCSF, contrast acuity, and CS thresholds at 3 cpd, 6 cpd, 12 cpd, and 18 cpd. Further, alhough we analyzed a very small sample of eyes with macular edema and improved retinal structure following anti-VEGF injections, we found a more marked improvement in AULCSF compared to VA (0.523 log units in CSF vs. 0.144 log units in the VA).

In the light of the above, VA, although consistently being the predominant visual function outcome in clinical trials, may not be the ideal functional endpoint. Current RVO trials for combination therapies or novel therapeutic agents face the challenge of proving noninferiority relative to monotherapies that demonstrate high levels of efficacy. An endpoint with reduced test-retest variability will allow for detection of smaller critical differences between treatment arms, and recruitment of smaller sample sizes. CSF measured with the active learning qCSF method demonstrates high sensitivity and at the same time precision, emerging as a promising visual function endpoint.

The qCSF active learning method has been already used to measure CSF in several clinical populations. Evaluating CSF in early diabetic retinopathy, Joltikov et al. reported AULCSF to be reduced across all spatial frequencies in diabetics with moderate compared to mild nonproliferative diabetic retinopathy and in diabetic patients with no diabetic retinopathy compared to controls.44 Further, CSF has been found to be reduced in amblyopia,39 central serous chorioretinopathy,42 glaucoma,43 retinal detachment, and retinitis pigmentosa24 and has been suggested as visual function endpoint to enable dry age-related macular degeneration (AMD) clinical trials.41 In multiple sclerosis, the CSF measured by the qCSF method has been proposed to be better correlated with self-reported visual function than letter charts.22 Lastly, aging has been associated with decreased CSF.24,45

There are several limitations to this study that should be noted. First, this is a relatively small cohort of nonischemic RVO, with no patients with neovascular complications, and therefore cannot be representative of all eyes with RVO. Second, there was a variable amount of time between the acute vein occlusion and the first CS test. Third, some patients were not treatment-naïve at the time of initial contrast testing. Fourth, four of our patients were pseudophakic. To address any changes advanced cataract status may impart of qCSF we have excluded patients with cataract status worse than 1+ nuclear sclerosis. However, the effect of cataract status on qCSF is still being examined. Future studies with longitudinal design and more consistent assessment, treatment schedule, and type are needed to verify our conclusions and provide information about long-term outcomes.

In conclusion, the CSF measured with the quick CSF active-learning method seems to be a promising visual function endpoint that can provide the sensitive and precise signals required to initiate and track RVO treatment over time in the clinical practice and emerges as a potential novel endpoint for future RVO clinical trials.

References

  1. Cugati S, Wang JJ, Rochtchina E, Mitchell P. Ten-Year Incidence of Retinal Vein Occlusion in an Older Population: The Blue Mountains Eye Study. Arch Ophthalmol. 2006;124(5):726–732. doi:10.1001/archopht.124.5.726 [CrossRef] PMID:16682596
  2. The Branch Vein Occlusion Study Group. Argon laser photo-coagulation for macular edema in branch vein occlusion. Am J Ophthalmol. 1984;98(3):271–282. doi:10.1016/0002-9394(84)90316-7 [CrossRef] PMID:6383055
  3. Mitchell P, Smith W, Chang A. Prevalence and associations of retinal vein occlusion in Australia. The Blue Mountains Eye Study. Arch Ophthalmol. 1996;114(10):1243–1247. doi:10.1001/archopht.1996.01100140443012 [CrossRef] PMID:8859084
  4. Jaulim A, Ahmed B, Khanam T, Chatziralli IP. Branch retinal vein occlusion: epidemiology, pathogenesis, risk factors, clinical features, diagnosis, and complications. An update of the literature. Retina. 2013;33(5):901–910. doi:10.1097/IAE.0b013e3182870c15 [CrossRef] PMID:23609064
  5. Cugati S, Wang JJ, Knudtson MD, et al. Retinal vein occlusion and vascular mortality: pooled data analysis of 2 population-based cohorts. Ophthalmology. 2007;114(3):520–524. doi:10.1016/j.ophtha.2006.06.061 [CrossRef] PMID:17141315
  6. Rosenfeld PJ, Fung AE, Puliafito CA. Optical coherence tomography findings after an intravitreal injection of bevacizumab (avastin) for macular edema from central retinal vein occlusion. Ophthalmic Surg Lasers Imaging. 2005;36(4):336–339. doi:10.3928/1542-8877-20050701-15 [CrossRef] PMID:16156153
  7. Prager F, Michels S, Kriechbaum K, et al. Intravitreal bevacizumab (Avastin) for macular oedema secondary to retinal vein occlusion: 12-month results of a prospective clinical trial. Br J Ophthalmol. 2009;93(4):452–456. doi:10.1136/bjo.2008.141085 [CrossRef] PMID:19074916
  8. Yenice O, Onal S, Incili B, Temel A, Afşar N, Tanridaş T. Assessment of spatial-contrast function and short-wavelength sensitivity deficits in patients with migraine. Eye (Lond). 2007;21(2):218–223. doi:10.1038/sj.eye.6702251 [CrossRef] PMID:16456594
  9. Jindra LF, Zemon V. Contrast sensitivity testing: a more complete assessment of vision. J Cataract Refract Surg. 1989;15(2):141–148. doi:10.1016/S0886-3350(89)80002-1 [CrossRef] PMID:2724114
  10. Woods RL, Wood JM. The role of contrast sensitivity charts and contrast letter charts in clinical practice. Clin Exp Optom. 1995;78(2):43–57. doi:10.1111/j.1444-0938.1995.tb00787.x [CrossRef]
  11. Arden GB. The importance of measuring contrast sensitivity in cases of visual disturbance. Br J Ophthalmol. 1978;62(4):198–209. doi:10.1136/bjo.62.4.198 [CrossRef] PMID:348230
  12. Richman J, Spaeth GL, Wirostko B. Contrast sensitivity basics and a critique of currently available tests. J Cataract Refract Surg. 2013;39(7):1100–1106. doi:10.1016/j.jcrs.2013.05.001 [CrossRef] PMID:23706926
  13. Marron JA, Bailey IL. Visual factors and orientation-mobility performance. Am J Optom Physiol Opt. 1982;59(5):413–426. doi:10.1097/00006324-198205000-00009 [CrossRef] PMID:7102800
  14. Owsley C, Sloane ME. Contrast sensitivity, acuity, and the perception of ‘real-world’ targets. Br J Ophthalmol. 1987;71(10):791–796. doi:10.1136/bjo.71.10.791 [CrossRef] PMID:3676151
  15. Freeman EE, Muñoz B, Turano KA, West SK. Measures of visual function and time to driving cessation in older adults. Optom Vis Sci. 2005;82(8):765–773. doi:10.1097/01.opx.0000175008.88427.05 [CrossRef] PMID:16127343
  16. Owsley C, McGwin G Jr, . Vision and driving. Vision Res. 2010;50(23):2348–2361. doi:10.1016/j.visres.2010.05.021 [CrossRef] PMID:20580907
  17. Geruschat DR, Turano KA, Stahl JW. Traditional measures of mobility performance and retinitis pigmentosa. Optom Vis Sci. 1998;75(7):525–537. doi:10.1097/00006324-199807000-00022 [CrossRef] PMID:9703042
  18. Owsley C. Contrast sensitivity. Ophthalmol Clin North Am. 2003;16(2):171–177. doi:10.1016/S0896-1549(03)00003-8 [CrossRef] PMID:12809156
  19. Brown B. Reading performance in low vision patients: relation to contrast and contrast sensitivity. Am J Optom Physiol Opt. 1981;58(3):218–226. doi:10.1097/00006324-198103000-00006 [CrossRef] PMID:7223854
  20. Lennerstrand G, Ahlström CO. Contrast sensitivity in macular degeneration and the relation to subjective visual impairment. Acta Ophthalmol (Copenh). 1989;67(3):225–233. doi:10.1111/j.1755-3768.1989.tb01863.x [CrossRef] PMID:2763808
  21. West SK, Rubin GS, Broman AT, Muñoz B, Bandeen-Roche K, Turano K. How does visual impairment affect performance on tasks of everyday life? The SEE Project. Salisbury Eye Evaluation. Arch Ophthalmol. 2002;120(6):774–780. doi:10.1001/archopht.120.6.774 [CrossRef] PMID:12049583
  22. Stellmann JP, Young KL, Pöttgen J, Dorr M, Heesen C. Introducing a New Method to Assess Vision: Computer-adaptive Contrast-Sensitivity Testing Predicts Visual Functioning Better Than Charts in Multiple Sclerosis Patients. Mult Scler J Exp Transl Clin. 2015;1:2055217315596184. doi:10.1177/2055217315596184 [CrossRef] PMID:28607699
  23. Preti RC, Ramirez LMV, Pimentel SLG, et al. Effect of a single intravitreal bevacizumab injection on contrast sensitivity and macular thickness in eyes with macular edema from central retinal vein occlusion: a prospective, nonrandomized, three-month follow-up study. Ophthalmic Res. 2014;51(3):140–145. doi:10.1159/000357737 [CrossRef] PMID:24525617
  24. Murugappan M, Vayalil J, Bade A, Bittner AK. Reliability of Quick Contrast Sensitivity Function Testing in Adults without Ocular Disease and Patients with Retinitis Pigmentosa. Invest Ophthalmol Vis Sci. 2016;57(12):616.
  25. Ramulu PY, Dave P, Friedman DS. Precision of contrast sensitivity testing in glaucoma. Invest Ophthalmol Vis Sci. 2015;56(7):2225–2225.
  26. Kelly DH, Savoie RE. A study of sine-wave contrast sensitivity by two psychophysical methods. Percept Psychophys. 1973;14(2):313–318. doi:10.3758/BF03212397 [CrossRef]
  27. Pelli DG, Robson JG, Wilkins AJ. The design of a new letter chart for measuring contrast sensitivity. Clin Vis Sci. 1988;2(3):187–199.
  28. Thayaparan K, Crossland MD, Rubin GS. Clinical assessment of two new contrast sensitivity charts. Br J Ophthalmol. 2007;91(6):749–752. doi:10.1136/bjo.2006.109280 [CrossRef] PMID:17166891
  29. Alexander KR, Barnes CS, Fishman GA. Characteristics of contrast processing deficits in X-linked retinoschisis. Vision Res. 2005;45(16):2095–2107. doi:10.1016/j.visres.2005.01.037 [CrossRef] PMID:15845241
  30. Ginsburg AP. Contrast sensitivity and functional vision. Int Ophthalmol Clin. 2003;43(2):5–15. doi:10.1097/00004397-200343020-00004 [CrossRef] PMID:12711899
  31. Pesudovs K, Hazel CA, Doran RML, Elliott DB. The usefulness of Vistech and FACT contrast sensitivity charts for cataract and refractive surgery outcomes research. Br J Ophthalmol. 2004;88(1):11–16. doi:10.1136/bjo.88.1.11 [CrossRef] PMID:14693761
  32. Bühren J, Terzi E, Bach M, Wesemann W, Kohnen T. Measuring contrast sensitivity under different lighting conditions: comparison of three tests. Optom Vis Sci. 2006;83(5):290–298. doi:10.1097/01.opx.0000216100.93302.2d [CrossRef] PMID:16699441
  33. Elliott DB, Bullimore MA. Assessing the reliability, discriminative ability, and validity of disability glare tests. Invest Ophthalmol Vis Sci. 1993;34(1):108–119. PMID:8425818
  34. Lesmes LA, Lu ZL, Baek J, Albright TD. Bayesian adaptive estimation of the contrast sensitivity function: The quick CSF method. Journal of Vision. 2010; 10(3):17.1–21.
  35. Dorr M, Wille M, Viulet T, et al. Next-generation vision testing: the quick CSF. Curr Dir Biomed Eng. 2015;1(1):131–134. doi:10.1515/cdbme-2015-0034 [CrossRef]
  36. Hou F, Lesmes LA, Kim W, et al. Evaluating the performance of the quick CSF method in detecting contrast sensitivity function changes. J Vis. 2016;16(6):18. doi:10.1167/16.6.18 [CrossRef] PMID:27120074
  37. Kalia A, Lesmes LA, Dorr M, et al. Development of pattern vision following early and extended blindness. Proc Natl Acad Sci USA. 2014;111(5):2035–2039. doi:10.1073/pnas.1311041111 [CrossRef] PMID:24449865
  38. Gepshtein S, Lesmes LA, Albright TD. Sensory adaptation as optimal resource allocation. Proc Natl Acad Sci USA. 2013;110(11):4368–4373. doi:10.1073/pnas.1204109110 [CrossRef] PMID:23431202
  39. Hou F, Huang CB, Lesmes L, et al. qCSF in clinical application: efficient characterization and classification of contrast sensitivity functions in amblyopia. Invest Ophthalmol Vis Sci. 2010;51(10):5365–5377. doi:10.1167/iovs.10-5468 [CrossRef] PMID:20484592
  40. Jia W, Zhou J, Lu ZL, Lesmes LA, Huang CB. Discriminating anisometropic amblyopia from myopia based on interocular inhibition. Vision Res. 2015;114:135–141. doi:10.1016/j.visres.2015.02.003 [CrossRef] PMID:25701741
  41. Lesmes LA, Jackson ML, Bex P. Visual function endpoints to enable dry AMD clinical trials. Drug Discov Today. 2013;10:e43–e50.
  42. Marmalidou A, Kim EL, Silverman R, et al. A Novel Contrast Sensitivity Test as a New Measure of Visual Function in Central Serous Chorioretinopathy. Invest Ophthalmol Vis Sci. 2018;59:3126.
  43. Lin S, Mihailovic A, West SK, et al. Predicting Visual Disability in Glaucoma With Combinations of Vision Measures. Transl Vis Sci Technol. 2018;7(2):22. doi:10.1167/tvst.7.2.22 [CrossRef]
  44. Joltikov KA, de Castro VM, Davila JR, et al. Multidimensional functional and structural evaluation reveals neuroretinal impairment in early diabetic retinopathy. Invest Ophthalmol Vis Sci. 2017;58(6):BIO277–BIO290. doi:10.1167/iovs.17-21863 [CrossRef] PMID:28973314
  45. Yan FF, Hou F, Lu ZL, Hu X, Huang CB. Efficient characterization and classification of contrast sensitivity functions in aging. Sci Rep. 2017;7(1):5045. doi:10.1038/s41598-017-05294-0 [CrossRef] PMID:28698553

Patient Demographics

CharacteristicRVO (N = 21 subjects, 22 eyes)Control (N = 63 subjects, 63 eyes)P Value
Age, mean (SD)60 (12)55 (12)P = .0557
Sex, female (%)8 (38)27 (43)P = .5942
LogMAR, mean (SD)0.204 (0.14)0.024 (0.05)P < .0001
Snellen, mean20/3220/21
Lens status, pseudophakic (%)4 (18)13 (21)P = .8044

Mean Contrast Sensitivity Outcome Measures in RVO and Control

RVO (N = 21)Control (N = 63)P Value
AULCSF mean (SD)0.817 (0.282)1.217 (0.280)P < .0001
CA mean (SD)1.054 (0.189)1.286 (0.156)P < .0001
1 cpd mean (SD)1.280 (0.232)1.400 (0.162)P = .0138
1.5 cpd mean (SD)1.288 (0.212)1.450 (0.170)P = .0027
3 cpd mean (SD)1.143 (0.270)1.458 (0.227)P < .0001
6 cpd mean (SD)0.726 (0.396)1.222 (0.306)P < .0001
12 cpd mean (SD)0.183 (0.255)0.627 (0.382)P < .0001
18 cpd mean (SD)0.022 (0.074)0.252 (0.283)P = .0002
LogMAR visual acuity (SD)0.204 (0.14)0.0239 (0.054)P < .0001

Mean Contrast Sensitivity Outcome Measures in RVO With VA ≤ 20/30 and Control

(N = 10)RVO VA ≤ 20/30Control (N = 63)P Value
AULCSF mean (SD)0.978 (0.322)1.217 (0.280)P = .0079
CA mean (SD)1.157 (0.181)1.286 (0.156)P = .0135
1 cpd mean (SD)1.359 (0.161)1.400 (0.162)P = .4460
1.5 cpd mean (SD)1.395 (0.161)1.450 (0.170)P = .2682
3 cpd mean (SD)1.290 (0.260)1.458 (0.227)P = .0213
6 cpd mean (SD)0.914 (0.410)1.222 (0.306)P = .0056
12 cpd mean (SD)0.356 (0.338)0.627 (0.382)P = .0115
18 cpd mean (SD)0.070 (0.124)0.252 (0.283)P = .0153
LogMAR visual acuity (SD)0.0586 (0.033)0.0239 (0.054)P = .0003
Authors

From Harvard Retinal Imaging Lab, Massachusetts Eye and Ear, Boston, Massachusetts (RFS, MK, FV, RK, JC, LAK, JBM); Retina Service, Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts (MK, FV, RK, JC, LAK, JBM); Adaptive Sensory Technology, San Diego, California (LAL); and Retina Service, Kellogg Eye Center, Department of Ophthalmology, University of Michigan Medical School, Ann Arbor, Michigan (DNZ).

Presented at the 2019 Macula Society Meeting, February 13–16, 2019, in Bonita Springs, Florida.

Supported in part by a grant from Lions International Fund. The supporting source had no involvement in study design, collection, analysis and interpretation of data, or writing the report.

Dr. Lesmes discloses financial, employment, and intellectual property interests in Adaptive Sensory Technology, which markets the vision-testing device used in this study. Dr. Miller is a consultan for Alcon, Allergan, Zeiss, Heidelberg, and Genentech. The remaining authors report no releveant financial disclosures.

Address correspondence to John B. Miller, MD, Retina Service, Massachusetts Eye and Ear Infirmary, Harvard Medical School, 243 Charles St, Boston, MA, 02114; email: john_miller@meei.harvard.edu.

Received: March 25, 2020
Accepted: June 04, 2020

10.3928/23258160-20200702-04

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