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Teleophthalmic Approach for Detection of Corneal Diseases: Accuracy and Reliability
Maria A Woodward1, David C Musch, Christopher T Hood
1*Department of Ophthalmology and Visual Sciences, W. K. Kellogg Eye Center, University of Michigan Medical School, Ann Arbor, MI; †Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; and ‡Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI.
Purpose:
Corneal and anterior segment diseases cause most of the urgent visits to eye care professionals. We evaluated the diagnostic accuracy of detecting corneal diseases using external photographs from 2 portable cameras for telemedicine purposes.
Methods:
This is a prospective study of adults with a clinical diagnosis of corneal pathology including corneal abrasions, ulcers, scars, and pterygia. A cornea specialist provided the gold standard diagnosis by slit-lamp examination. Images of both eyes were obtained using iTouch 5S and Nidek VersaCam cameras in multiple gazes and interpreted by 3 cornea specialists for the presence of pathology. Accuracy to detect disease was compared with gold standard diagnosis, stratified by the camera and grader. Reliability was evaluated with weighted kappa statistics. Graders assessed image quality on a Likert scale from 1 (poor) to 9 (optimal).
Results:
A total of 198 eyes (110 subjects) were photographed. By gold standard diagnosis, 59 eyes (30%) had corneal scars, 34 (17%) had ulcers, 13 (7%) had abrasions, 10 (5%) had pterygia, and 82 (41%) were normal. Sensitivity to detect AS pathology ranged from 54% to 71% for the iTouch and 66% to 75% for the Nidek, across graders; specificity ranged from 82% to 96% for the iTouch and 91% to 98% for the Nidek. The intergrader reliability was moderate to strong (kappa ranges: 0.54-0.71 for the iTouch; 0.75-0.76 for the Nidek). Quality ratings were variable between graders.
Conclusions:
External photographs taken by standard, nonenhanced portable cameras and interpreted remotely by ophthalmologist graders yielded sensitivity values that are not yet suitable for telemedicine applications. Additional work is needed to improve the ability to detect AS pathology remotely.