Allen O Eghrari1, Aisha A Mumtaz, Brian Garrett, Mahsa Rezaei, Mina S Akhavan, S Amer Riazuddin, John D Gottsch. 1. *Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD; †George Washington University School of Medicine & Health Sciences, Washington, DC; ‡Faculty of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; §Department of Medicine, University of California Irvine, Irvine, CA; and ¶University of Maryland, College Park, MD.
Abstract
PURPOSE: Retroillumination photography analysis is an objective tool for the assessment of the number and distribution of guttae in eyes affected with Fuchs corneal dystrophy (FCD). Current protocols include manual processing of images; here, we assess validity and interrater reliability of automated analysis across various levels of FCD severity. METHODS: Retroillumination photographs of 97 FCD-affected corneas were acquired, and total counts of guttae were previously summated manually. For each cornea, a single image was loaded into ImageJ software. We reduced color variability and subtracted background noise. Reflection of light from each gutta was identified as a local area of maximum intensity and counted automatically. Noise tolerance level was titrated for each cornea by examining a small region of each image with automated overlay to ensure appropriate coverage of individual guttae. We tested interrater reliability of automated counts of guttae across a spectrum of clinical and educational experience. RESULTS: A set of 97 retroillumination photographs was analyzed. Clinical severity as measured by a modified Krachmer scale ranged from a severity level of 1 to 5 in the set of analyzed corneas. Automated counts by an ophthalmologist correlated strongly with Krachmer grading (R = 0.79) and manual counts (R = 0.88). Intraclass correlation coefficients demonstrated strong correlation at 0.924 (95% CI, 0.870-0.958) among cases analyzed by 3 students, and 0.869 (95% CI, 0.797-0.918) among cases for which images were analyzed by an ophthalmologist and 2 students. CONCLUSIONS: Automated retroillumination photography analysis allows for grading of FCD severity with high resolution across a spectrum of disease severity.
PURPOSE: Retroillumination photography analysis is an objective tool for the assessment of the number and distribution of guttae in eyes affected with Fuchs corneal dystrophy (FCD). Current protocols include manual processing of images; here, we assess validity and interrater reliability of automated analysis across various levels of FCD severity. METHODS: Retroillumination photographs of 97 FCD-affected corneas were acquired, and total counts of guttae were previously summated manually. For each cornea, a single image was loaded into ImageJ software. We reduced color variability and subtracted background noise. Reflection of light from each gutta was identified as a local area of maximum intensity and counted automatically. Noise tolerance level was titrated for each cornea by examining a small region of each image with automated overlay to ensure appropriate coverage of individual guttae. We tested interrater reliability of automated counts of guttae across a spectrum of clinical and educational experience. RESULTS: A set of 97 retroillumination photographs was analyzed. Clinical severity as measured by a modified Krachmer scale ranged from a severity level of 1 to 5 in the set of analyzed corneas. Automated counts by an ophthalmologist correlated strongly with Krachmer grading (R = 0.79) and manual counts (R = 0.88). Intraclass correlation coefficients demonstrated strong correlation at 0.924 (95% CI, 0.870-0.958) among cases analyzed by 3 students, and 0.869 (95% CI, 0.797-0.918) among cases for which images were analyzed by an ophthalmologist and 2 students. CONCLUSIONS: Automated retroillumination photography analysis allows for grading of FCD severity with high resolution across a spectrum of disease severity.
Authors: Danielle N Meadows; Allen O Eghrari; S Amer Riazuddin; David G Emmert; Nicholas Katsanis; John D Gottsch Journal: Invest Ophthalmol Vis Sci Date: 2009-07-15 Impact factor: 4.799
Authors: Allen O Eghrari; Brian S Garrett; Aisha A Mumtaz; Armand E Edalati; Danielle N Meadows; Elyse J McGlumphy; Benjamin W Iliff; John D Gottsch Journal: Cornea Date: 2015-12 Impact factor: 2.651
Authors: Elyse J McGlumphy; William S Yeo; S Amer Riazuddin; Amr Al-Saif; Jiangxia Wang; Allen O Eghrari; Danielle N Meadows; David G Emmert; Nicholas Katsanis; John D Gottsch Journal: Invest Ophthalmol Vis Sci Date: 2010-09-01 Impact factor: 4.799
Authors: John D Gottsch; Olof H Sundin; Erik V Rencs; David G Emmert; Walter J Stark; Clement J Cheng; Gregory W Schmidt Journal: Cornea Date: 2006-05 Impact factor: 2.651
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