Active Learning of Contrast Sensitivity to Assess Visual Function in Macula-Off Retinal Detachment

Abstract

Purpose: This work characterizes the contrast sensitivity function (CSF) in patients with successful repair of macula-off rhegmatogenous retinal detachment (RD) using an adaptive computerized contrast testing device. Methods: CSF was prospectively measured in patients with macula-off RD following successful repair and age-matched controls at W.K. Kellogg Eye Center and Massachusetts Eye and Ear using Adaptive Sensory Technology’s Manifold Contrast Vision Meter. Outcome measures included average area under the CSF curve, contrast-sensitivity thresholds (1-18 cycles per degree), and best-corrected visual acuity (BCVA) in RD eyes, fellow eyes, and controls. A subanalysis was performed in eyes with BCVA of 20/30 or better. Results: Twenty-three macula-off RD eyes following repair, fellow healthy eyes, and 45 age-matched control eyes underwent CSF testing. Mean BCVA of the 23 RD eyes was 0.250 logMAR, which was, significantly reduced compared with fellow eyes 0.032 ( P < .001) and controls 0.026 ( P < .001). There was a statistically significant reduction in average area under the CSF curve in RD eyes compared with fellow eyes ( P < .0001) and age-matched controls ( z score –0.90, P < .0001) and CSF reduction across all spatial frequencies. In the 15 RD eyes with BCVA of 20/30 or better, the mean CSF was significantly reduced vs fellow eyes ( P = .02) and controls ( P = .045). Conclusions: CSF in macula-off RD eyes following repair was significantly reduced compared with fellow eyes and age-matched controls. CSF may be a promising visual function end point with applications in clinical practice and future clinical trials.

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

“…In our recently published work [79], our team has also examined a large cohort of 151 patients who retained good visual acuity and with different macular diseases including Our team has also previously reported on the qCSF method in eyes with maculaoff rhegmatogenous retinal detachment (RRD) after surgical repair. Eyes with a history of macula-off RRD had statistically significant reductions in AULCSF and in contrast sensitivity thresholds across all spatial frequencies compared to healthy age-matched control eyes [74]. Similarly, in the subgroup analysis of the macula-off RRD eyes with VA better than or equal to 20/30, contrast sensitivity function was still significantly reduced compared to fellow eyes and controls.…”

“…The qCSF method has been used in preliminary studies to measure CSF in several clinical populations including amblyopia [69,70] multiple sclerosis [71], dry age-related macular degeneration [72], glaucoma [73], retinal detachment [74], retinal vein occlusion [75,76], early diabetic retinopathy [77], and aging [78]. An initial clinical study showed that qCSF test results correlate better with subjective visual impairment and patient-reported outcomes than established VA measures both far and near [71].…”

“…Similarly, in the subgroup analysis of the macula-off RRD eyes with VA better than or equal to 20/30, contrast sensitivity function was still significantly reduced compared to fellow eyes and controls. This may explain why patients after RRD continue to have visual complaints, despite the great anatomic success in reattachment surgery [74].…”

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

“…A recent qCSF implementation with a 10-letter identification task enabled assessment of the CSF with a 0.10 log unit standard deviation in about 20 trials (approximately 2 minutes) and reduced the standard deviation of the estimates by 50% ( Hou, Lesmes, Bex, Dorr, & Lu, 2015 ). Accurate and precise qCSF estimates have been obtained in both normal ( Reynaud, Tang, Zhou, & Hess, 2014 ; Rosén, Lundström, Venkataraman, Winter, & Unsbo, 2014 ) and clinical populations ( Hou, Huang, Lesmes, Feng, Tao, Zhou, & Lu, 2010 ; Jia, Zhou, Lu, Lesmes, & Huang, 2015 ; Joltikov, de Castro, Davila, Anand, Khan, Farbman, Jackson, Johnson, & Gardner, 2017 ; Lesmes, Jackson & Bex, 2013 ; Lesmes, Wallis, Jackson, & Bex, 2013 ; Lesmes, Wallis, Lu, Jackson, & Bex, 2012 ; Lin, Mihailovic, West, Johnson, Friedman, Kong, & Ramulu, 2018 ; Ou, Lesmes, Christie, Denlar, & Csaky, 2021 ; Ramulu, Dave, & Friedman, 2015 ; Rosen, Jayaraj, Bharadwaj, Weeber, Van der Mooren, & Piers, 2015 ; Stellmann, Young, Pottgen, Dorr, & Heesen, 2015 ; Thomas, Silverman, Vingopoulos, Kasetty, Yu, Kim, Omari, Joltikov, Choi, Kim, Zacks, & Miller, 2021 ; Vingopoulos, Wai, Katz, Vavvas, Kim, & Miller, 2021 ; Wai, Vingopoulos, Garg, Kasetty, Silverman, Katz, Laíns, Miller, Husain, Vavvas, Kim, & Miller, 2021 ; Yan, Hou, Lu, Hu, & Huang, 2017 ).…”

Active Learning to Characterize the Full Contrast Sensitivity Function in Cataracts

“…[30][31][32] The quantitative contrast sensitivity function method (qCSF) leverages active-learning algorithms to test contrast sensitivity across multiple spatial frequencies, in a clinically feasible manner (2-5minutes per eye) 33,34 and with both high test-retest reliability and sensitivity in detecting subtle changes in visual function. 35 It has already been applied in retinal disorders, [36][37][38][39][40] amblyopia, 41 glaucoma 42 and aging. 43 Our group has previously employed the qCSF method and reported significant contrast sensitivity deficits in patients with macular disease and VA ≥20/30, that persisted even in eyes with VA ≥20/20 −1 .…”