June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Active Learning of Contrast Sensitivity Functions in Age-Related Macular Degeneration Across Luminance Levels
Author Affiliations & Notes
  • William C Ou
    Retina Foundation of the Southwest, Dallas, Texas, United States
  • Luis A Lesmes
    Adaptive Sensory Technology, San Diego, California, United States
  • Renee A Denlar
    Retina Foundation of the Southwest, Dallas, Texas, United States
  • Karl G Csaky
    Retina Foundation of the Southwest, Dallas, Texas, United States
  • Footnotes
    Commercial Relationships   William Ou, None; Luis Lesmes, Adaptive Sensory Technology (P), Adaptive Sensory Technology (I), Adaptive Sensory Technology (E); Renee Denlar, None; Karl Csaky, Allergan (C), Apellis (I), Astellas Pharma (C), Genentech (C), Gyroscope Therapeutics Limited (C), Heidelberg Engineering (C), Iveric Bio (C), Novartis (C), Ribomics (C), Roche (C)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 3011. doi:
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    • Get Citation

      William C Ou, Luis A Lesmes, Renee A Denlar, Karl G Csaky; Active Learning of Contrast Sensitivity Functions in Age-Related Macular Degeneration Across Luminance Levels. Invest. Ophthalmol. Vis. Sci. 2020;61(7):3011.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Age-related macular degeneration (AMD) is a leading cause of vision loss in developed countries. Patients with AMD often complain of visual dysfunction in early stages of disease while visual acuity (VA) is typically spared. Contrast sensitivity may be a more sensitive measure of early functional change in AMD, but has traditionally been difficult to measure. The aim of this study was to validate an active learning approach to measuring the contrast sensitivity function (CSF) in a cohort of patients with AMD under multiple luminance conditions.

Methods : In this cross sectional study, patients with AMD and age-matched controls were tested with the Manifold Contrast Vision Meter (Adaptive Sensory Technology, San Diego, CA) and the qCSF algorithm, which applies active learning to estimate a model of the CSF’s global shape. Patients were asked to identify 25 consecutive optotype triplets varying in size and contrast as determined by the algorithm. Testing was performed under conditions of standard and low luminance (2.0 log neutral density filter). AMD patients were divided into separate groups for analysis based on disease severity (intermediate AMD, subretinal drusenoid deposits [SDD], geographic atrophy [GA]). For each measure, the area under log CSF (AULCSF), in addition to contrast sensitivities at individual spatial frequencies, were calculated for analysis.

Results : 65 patients with AMD (26 intermediate AMD, 19 SDD, 20 GA) and 23 age-matched controls were included in this study. AULCSF declined progressively as disease severity increased. This was true for both standard luminance (mean AULCSF 1.26, 0.99, 0.78, and 0.69 for control, intermediate AMD, SDD, and GA) and low luminance (mean AULCSF 0.53, 0.35, 0.20, and 0.13 for control, intermediate AMD, SDD, and GA respectively) (Figures 1 and 2). Contrast sensitivity losses were most pronounced at low-intermediate spatial frequencies (3 and 6 cycles per degree-which are equivalent to Snellen sizes of 20/200 and 20/100).

Conclusions : Contrast sensitivity measured with the qCSF may be a sensitive functional correlate for progressive stages of AMD. Consistent with previous studies, patients with SDD appear to be phenotypically distinct from patients with soft drusen alone. The test, which takes 5-10 min/eye, can be readily incorporated into clinical practice and future clinical trials for AMD.

This is a 2020 ARVO Annual Meeting abstract.

 

 

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