June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Inter-Eye Symmetries of Visual Field Defects in Glaucoma
Author Affiliations & Notes
  • Bettina Teng
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Dian Li
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Lucy Shen
    Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Louis R Pasquale
    Department of Ophthalmology, Eye and Vision Research Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Michael V Boland
    Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
  • Pradeep Y Ramulu
    Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
  • Sara Wellik
    Bascom Palmer Eye Institute, University of Miami School of Medicine, Miami, Florida, United States
  • Carlos Gustavo De Moraes
    Edward S. Harkness Eye Institute, Columbia University Medical Center, New York, New York, United States
  • Jonathan S Myers
    Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania, United States
  • Siamak Yousefi
    Hamilton Eye Institute, University of Tennessee Health Science Center, Memphis, Tennessee, United States
  • Thao D Nguyen
    Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
  • Eun Young Choi
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Hui Wang
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
    Institute for Psychology and Behavior, Jilin University of Finance and Economics, Changchun, China
  • Peter J Bex
    Department of Psychology, Northeastern University, Boston, Massachusetts, United States
  • Tobias Elze
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Mengyu Wang
    Department of Opthalmomogy, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Bettina Teng, None; Dian Li, Adaptive Sensory Technology (R); Lucy Shen, Research Funding (F), Topcon (C); Louis Pasquale, Alcon-Speaker (S), Bausch+Lomb (C), Eyenovia-Advisory Board Member (S), Verily Life Sciences (F); Michael Boland, Heidelberg (C); Pradeep Ramulu, None; Sara Wellik, None; Carlos De Moraes, None; Jonathan Myers, None; Siamak Yousefi, None; Thao Nguyen, None; Eun Young Choi, None; Hui Wang, None; Peter Bex, United States PCT/US2014/052414 (P); Tobias Elze, Adaptive Sensory Technology (R), United States PCT/US2014/052414 (P); Mengyu Wang, Adaptive Sensory Technology (R)
  • Footnotes
    Support  NIH K99 EY028631, NIH R21 EY030142, NIH R21 EY030631, NIH R01 EY030575, NIH P30 EY003790, BrightFocus Foundation, Grimshaw-Gudewicz Foundation, Research to Prevent Blindness, Lions Foundation, Alice Adler Fellowship.
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 4047. doi:
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    • Get Citation

      Bettina Teng, Dian Li, Lucy Shen, Louis R Pasquale, Michael V Boland, Pradeep Y Ramulu, Sara Wellik, Carlos Gustavo De Moraes, Jonathan S Myers, Siamak Yousefi, Thao D Nguyen, Eun Young Choi, Hui Wang, Peter J Bex, Tobias Elze, Mengyu Wang; Inter-Eye Symmetries of Visual Field Defects in Glaucoma. Invest. Ophthalmol. Vis. Sci. 2020;61(7):4047.

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

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Abstract

Purpose : To study the inter-eye symmetries of visual field (VF) defects through artificial intelligence.

Methods : From a multi-centered dataset, we selected the most recent reliable 24-2 Humphrey VF pairs from both eyes tested on the same date with mean deviation (MD) ≥ -12 dB. VF defects were quantified by decomposing VFs into 16 archetype (AT) patterns consisting of 1 normal (AT 1) and 15 defect patterns (ATs 2 to 16), as detailed in our prior work (Fig. 1a). Coefficients describing the contribution of each VF AT to the overall VF pattern were correlated between worse and better eyes as defined by MD. The presence of VF defects (AT coefficients > 10%) in the better eye was modeled from the AT coefficients of the worse eye by logistic regression. The optimal models selected by stepwise regression were evaluated by the area under the receiver operating characteristic curve (AUC). We specifically provide model details for inter-eye prediction of the most common type of glaucomatous central vision loss: superior paracentral loss (AT14).

Results : 64,447 pairs of VFs from 64,447 patients (61.0 ± 16.6 years) were selected. The MDs for the worse and better eyes (r = 0.77, p < 0.001) were -3.4 ± 3.2 dB and -1.6 ± 2.3 dB, respectively. The inter-eye correlations of AT coefficients ranged from -0.34 to 0.70 (Fig. 1b), with strongest correlations either with the same or normal VF pattern. The AUCs predicting the presence of 15 VF defects in the better eye based on ATs of the worse eye ranged from 0.69 (AT 3, superonasal step) to 0.92 (AT 6, near total loss). Fig. 2a shows that AT 14’s presence in the better eye can be predicted by 9 AT features in the worse eye (AUC = 0.89): AT 7 (central scotoma), AT 8 (superior altitudinal defect), AT 14 (superior paracentral loss), AT 15 (nasal hemianopia) and AT 16 (inferior paracentral loss) from the worse eye were positively correlated with AT 14 in the better eye, while AT 1 (normal VF), AT 2 (superior peripheral defect), AT 4 (temporal wedge) and AT 11 (concentric peripheral defect) showed negative correlations. Fig. 2b shows an example of high likelihood of AT 14 in the better eye predicted by the worse eye for every reliable VF pair in a 3 VF series. While the first and last VFs of the better eye have 14.1% and 10.4% AT 14, the defect (1.0% AT 14) was missed in the second VF.

Conclusions : VF ATs from the patient’s worse eye can be used to predict and therefore confirm a VF defect in the better eye.

This is a 2020 ARVO Annual Meeting abstract.

 

 

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