July 2019
Volume 60, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2019
Active Learning of Contrast Sensitivity Function to Assess Visual Outcomes in Age-related macular degeneration
Author Affiliations & Notes
  • Ying Cui
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
    Department of Ophthalmology, Guangdong Eye Institute, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
  • Rebecca Silverman
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
    Tufts Medical School, Boston, Massachusetts, United States
  • Megan A Kasetty
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
    Tufts Medical School, Boston, Massachusetts, United States
  • June Cho
    Northeastern University, Boston, Massachusetts, United States
  • Luis Andres Lesmes
    Adaptive Sensory Technology, San Diego, California, United States
  • Ines Lains
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Raviv Katz
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Demetrios Vavvas
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Deeba Husain
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Joan W Miller
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • John B Miller
    Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Ying Cui, None; Rebecca Silverman, None; Megan Kasetty, None; June Cho, None; Luis Lesmes, Adaptive Sensory Technology (P), Adaptive Sensory Technology (I), Adaptive Sensory Technology (E); Ines Lains, None; Raviv Katz, None; Demetrios Vavvas, None; Deeba Husain, Alcon/Novartis (C), Genentech (C); Joan Miller, Bausch + Lomb (C), Genentech/Roche (C), Genentech/Roche (R), KalVista Pharmaceuticals (C), Lowy Medical Research Institute (F), ONL Therapeuticals (C), ONL Therapeuticals (P), ONL Therapeuticals (R), Valeant Pharmaceuticals/Mass. Eye and Ear (P), Valeant Pharmaceuticals/Mass. Eye and Ear (R); John Miller, Alcon (C), Allegan (C), Genentech/Roche (C), Heidelberg (R), Optovue (R), Zeiss (R)
  • Footnotes
    Support  none
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 1205. doi:https://doi.org/
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Ying Cui, Rebecca Silverman, Megan A Kasetty, June Cho, Luis Andres Lesmes, Ines Lains, Raviv Katz, Demetrios Vavvas, Deeba Husain, Joan W Miller, John B Miller; Active Learning of Contrast Sensitivity Function to Assess Visual Outcomes in Age-related macular degeneration. Invest. Ophthalmol. Vis. Sci. 2019;60(9):1205. doi: https://doi.org/.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : To evaluate the application of active learning to measure the contrast sensitivity function in age-related macular degeneration (AMD).

Methods : Prospective, observational study performed at Mass Eye and Ear. We included eyes with dry AMD and wet AMD and excluded other visually significant diseases or previous ocular surgeries (except anti-VEGF intravitreal injection and cataract surgery). Eyes were tested with quick contrast sensitivity function (qCSF) using the Manifold platform (Adaptive Sensory Technologies, San Diego, CA) and spectral domain optical coherence tomography (Heidelberg). The main outcome measure was the area under log contrast sensitivity function (AULCSF). Secondary outcomes were contrast sensitivity thresholds at six spatial frequencies (1, 1.5, 3, 6, 12, 18CPD), contrast acuity (CA) and best corrected visual acuity (BCVA, LogMAR). All measures were compared to previously collected data in control eyes. After adjusting for sex and age, general linear models were used to compare the means of continuous variables.

Results : We included 40 eyes from 30 AMD patients and 30 eyes from 30 controls, mean aged 71.4±8.4 and 65.1±5.9 years old respectively. Sixteen eyes presented dry AMD, while 24 had wet AMD. Among the last, 13 eyes had fluid under the fovea. AMD eyes differed significantly from control eyes in BCVA (LogMAR, 0.13 VS. 0.01, P=0.001), mean AULCSF (0.75 ± 0.34 VS. 1.17 ± 0.26, P<0.001) and CA (1.04 ± 0.23 VS. 1.22 ± 0.13, P=0.023), after adjusting for sex and age. Eyes with dry AMD had a statistically significant reduction in AULCSF (P<0.05) despite no difference in visual acuity when compared to controls (P>0.05). There was also a non-significant reduction in AULCSF and CA in eyes with wet AMD compared to dry AMD (P>0.05). However, when looking at intermediate spatial frequencies, eyes with wet AMD had significantly reduced contrast thresholds compared to dry AMD at 1.5CPD, 3CPD and 6CPD (P<0.05).We found no statistically significant differences (P>0.05) in BCVA, mean AULCSF and CA between wet AMD patients with and without fluid under fovea.

Conclusions : An active learning algorithm reveals patterns of contrast sensitivity loss in eyes with AMD, which can be correlated with structural changes in AMD. These contrast sensitivity outcomes exhibit potential as endpoints in clinical trials for the treatment of AMD.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×