Investigative Ophthalmology & Visual Science Cover Image for Volume 63, Issue 7
June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Preoperative OCT signal quality as a metric for measuring cataract visual burden
Author Affiliations & Notes
  • Joseph Colcombe
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Adanna Udeh
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Stephanie Choi
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Gadi Wollstein
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Joel S Schuman
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Scott E Brodie
    Department of Ophthalmology, NYU Langone Health, New York, New York, United States
  • Footnotes
    Commercial Relationships   Joseph Colcombe None; Adanna Udeh None; Stephanie Choi None; Gadi Wollstein None; Joel Schuman Carl Zeiss Meditec, Opticient , Code C (Consultant/Contractor), Opticient, Code I (Personal Financial Interest); Scott Brodie None
  • Footnotes
    Support  Research to Prevent Blindness; NIH Grant R01 EY013178
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 224 – F0071. doi:
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    • Get Citation

      Joseph Colcombe, Adanna Udeh, Stephanie Choi, Gadi Wollstein, Joel S Schuman, Scott E Brodie; Preoperative OCT signal quality as a metric for measuring cataract visual burden. Invest. Ophthalmol. Vis. Sci. 2022;63(7):224 – F0071.

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

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Abstract

Purpose : Objectively determining the effect of a cataract on visual performance has long been a problem for ophthalmologists. Many candidates for cataract extraction now routinely undergo optical coherence tomography (OCT) prior to surgery. We performed a single center, retrospective, observational study to evaluate the utility of using OCT image quality as an objective measure of the impact of a cataract on visual functioning.

Methods : A database was created of 1645 eyes that underwent cataract extraction and OCT prior to surgery. 1404 eyes met the inclusion criteria of a Best Corrected Visual Acuity (BCVA) of 20/25 or better within 60 days of surgery. This cutoff was chosen to reduce the likelihood of capturing concurrent non-lens pathologies. Pre- and postoperative BCVAs, cataract type and grade, preoperative OCT signal quality, and OCT model were recorded for each eye, and Snellen BCVAs were converted to Logarithm of the Minimal Angle of Resolution (LogMAR) values. The Q value, a standardized measure of signal quality, was created by scaling the proprietary image quality values from all machines to that of the most frequently used model (Zeiss). The data were stratified by postoperative BCVA, OCT model, and cataract type and grade. Simple linear regression was performed for each stratification.

Results : Linear regression of preoperative acuity among all included eyes versus Q returned an R-squared value of 0.1725. The same regression performed with eyes having a postoperative BCVA of 20/20 or better (n=1168) returned an R-squared of 0.2207. Regressing Q on preoperative acuity when stratifying by cataract type returned similar R-squared values for cortical, nuclear sclerotic, and posterior subcapsular cataracts (0.2098, 0.2219, and 0.2520 respectively). Likewise, regressing Q on preoperative acuity when stratifying by machine type returned similar R-squared values for Optovue, Topcon, and Zeiss models (0.2326, 0.2055, and 0.2641 respectively) and a lower value for Heidelberg (0.1502). The R-squared value was low when regressing either Q or preoperative acuity on summed cataract grade (0.0728 and 0.0912 respectively). P-values for all correlations were <0.0001.

Conclusions : These analyses suggest that preoperative acuity correlates better with OCT image quality than clinical cataract grade. Overall, there may be a modest correlation between vision loss caused by cataracts and OCT signal quality.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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