June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
cRORA progression and its baseline predicting factors
Author Affiliations & Notes
  • Or Shmueli
    Ophthalmology, Hadassah Medical Center Department of Ophthalmology, Jerusalem, Jerusalem, Israel
  • Roei Yehuda
    School of Computer Science and Engineering, Hebrew University of Jerusalem Faculty of Science, Jerusalem, Israel
  • Adi Szeskin
    School of Computer Science and Engineering, Hebrew University of Jerusalem Faculty of Science, Jerusalem, Israel
  • Leo Joskowicz
    School of Computer Science and Engineering, Hebrew University of Jerusalem Faculty of Science, Jerusalem, Israel
  • Jaime Levy
    Ophthalmology, Hadassah Medical Center Department of Ophthalmology, Jerusalem, Jerusalem, Israel
  • Footnotes
    Commercial Relationships   Or Shmueli, None; Roei Yehuda, None; Adi Szeskin, None; Leo Joskowicz, None; Jaime Levy, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 1888. doi:
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    • Get Citation

      Or Shmueli, Roei Yehuda, Adi Szeskin, Leo Joskowicz, Jaime Levy; cRORA progression and its baseline predicting factors. Invest. Ophthalmol. Vis. Sci. 2021;62(8):1888.

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

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Abstract

Purpose : To quantitatively evaluate progression rate and the baseline predictors of progression of complete retinal pigment epithelium and outer retinal atrophy (cRORA) in cases of dry age-related macular degeneration (AMD).

Methods : Two ophthalmologists retrospectively annotated cRORA. Two-thirds of the scans were annotated by one grader and validated by a second-grader. A third of the scans were independently annotated by both graders.
Primary outcomes: 1) cRORA area progression (mm2/year); 2) cRORA square root area progression (mm/year); and 3) radial progression towards the fovea (mm/year).
The effects of the different baseline predictors on the primary outcomes were analyzed, including 1) the total area; 2) area at a diameter of 1 mm around the center; 3) focality; 4) circularity; 5) total lesion perimeter; 6) minimal feret (Feretmin); 7) maximal Feret (Feretmax); 8) minimal distance from the center at baseline; 9) sex; 10) age; 11) hypertension and 12) lens status.

Results : cRORA was annotated on a dataset of 37 baseline and follow up pairs of OCT scans 16 patients with dry AMD. Inter-grader variability was tested on 1989 standalone OCT B-scans and resulted in a DICE coefficient of 0.75±0.16.
Mean area progression was 1.34±0.80 mm2/year (p<0.0001). Mean square root area progression was 0.32±0.18 mm/year (p<0.0001). Mean radial progression towards the fovea was 0.06±0.12 mm/year.
A multiple linear regression model (adjusted r2=0.665) showed baseline focality (estimated β=0.101; p=0.0008) and baseline circularity (estimated β=-1.789; p=0.0076) were significant factors associated with cRORA area progression.
The lesions' baseline minimal distance from the center correlated with radial growth rate towards the center on univariate linear regression analysis (p<0.0001;r=0.686).

Conclusions : This study quantitatively measured cRORA area progression rate in dry AMD patients, as compared to traditional fundus autofluorescence measurements. cRORA area progression varied with respect to baseline focality and circularity indices. Radial progression correlated with the lesion’s baseline minimal distance from the center. These results may be used in the research of treatments for retinal atrophy secondary to dry AMD.

This is a 2021 ARVO Annual Meeting abstract.

 

An example cRORA segment annotation on OCT B-scan (Fig. 1A). These atrophy segments are then projected on the Infra-red image at baseline (Fig. 1B) and follow-up (Fig. 1C), to calculate The difference (Fig. 1D).

An example cRORA segment annotation on OCT B-scan (Fig. 1A). These atrophy segments are then projected on the Infra-red image at baseline (Fig. 1B) and follow-up (Fig. 1C), to calculate The difference (Fig. 1D).

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