June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Automated and Manual Non Mydriatic Digital Retinal Imaging in Community-based Tele-Ocular Screening
Author Affiliations & Notes
  • Ann M John
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Sumana S Kommana
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Nicole Mendez
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Saysha Blazier
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Bernard C Szirth
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Albert S Khouri
    Ophthalmology, Rutgers New Jersey Medical School, Newark, NJ
  • Footnotes
    Commercial Relationships Ann John, None; Sumana Kommana, None; Nicole Mendez, None; Saysha Blazier, None; Bernard Szirth, None; Albert Khouri, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 5254. doi:
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      Ann M John, Sumana S Kommana, Nicole Mendez, Saysha Blazier, Bernard C Szirth, Albert S Khouri; Automated and Manual Non Mydriatic Digital Retinal Imaging in Community-based Tele-Ocular Screening. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5254.

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

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Abstract
 
Purpose
 

Tele-ocular screening relies on accurate interpretation of captured images. A newer automated fundus imaging system allows fast image acquisition with minimal training of screeners. Additional image enhancement assists in the ability to capture retinal pathology. The purpose of this study is to compare the quality of images captured by automated, enhanced automated, and traditionally used manual non mydriatic retinal camera systems.

 
Methods
 

We prospectively enrolled 44 subjects (88 eyes) during a community-based screening to be imaged with two fundus camera systems: 1. Manual imaging (Canon CR-DGi- Tokyo, Japan) and 2. A novel automated system (Canon CR-2AF- Tokyo, Japan). All subjects were imaged with ambient room light (250 Lux) without receiving mydriatic agents. Time to image both eyes included time to focus, capture in one eye, allow visual recovery of the second eye, and capture in the second eye. Image quality was assessed using a previously published validated quantitative grading scale (1-5, 5=best, 1=worse) (Table 1). An optometrist and ophthalmologist each evaluated 87 images from the manual, 88 images from the automated, and 88 images from the enhanced automated groups. Ratings were compared using t-tests. Inter-rater reliability was measured using Cohen’s Kappa (K).

 
Results
 

Subject characteristics were: 60.4% female, 39.6% male, 45.8% African-American, 50.0% Hispanic, 4.2% White. Mean quality scores were 4.26±0.9, 4.50±0.8, and 4.30±0.8 in the manual, automated, and enhanced automated groups, respectively. Time to image both eyes was lower with the automated system (Table 2). There was statistically significant higher grading in the automated imaging system when compared to both the manual system and enhanced automated system (p<0.05). The enhanced automated image grading was higher than the manual image grading but did not reach statistical significance (p=0.33). Overall inter-rater reliability was moderate (mean K=0.49, upper limit=0.59 and lower limit=0.40).

 
Conclusions
 

In this sample population, images captured with a new automated fundus imaging system had a faster acquisition and higher quality score than manual imaging. The auto-enhance feature did not increase image quality. In the future, automated imaging during community screening of a larger population with diverse pathology will be investigated.  

 
1: Grading Scale (Kolomeyer et al., 2014)
 
1: Grading Scale (Kolomeyer et al., 2014)
 
 
2: Comparison of Cameras
 
2: Comparison of Cameras

 
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