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Abstract #74720 Published in IGR 19-1
Optic Disc Image Subtraction as an Aid to Detect Glaucoma Progression
Amini N; Alizadeh R; Parivisutt N; Kim E; Nouri-Mahdavi K; Caprioli JTranslational vision science & technology 2017; 6: 14
PURPOSE: To present a digital image subtraction technique to alert clinicians to signs of glaucomatous optic disc progression. METHODS: Ninety-two glaucomatous eyes (65 patients) were included. Thirty-three eyes were identified as progressive and 59 as stable based on comparison of baseline and follow-up stereoscopic disc photographs by three masked glaucoma specialists. The disc images were aligned and converted to gray scale and underwent histogram matching to enhance contrast and account for illumination differences. The difference in image intensity between baseline and follow-up images was shown as a colormap superimposed on the grayscale follow-up image. A graded scale (1, no progression, to 5, definitive progression) was used by three masked glaucoma experts to score progression probability on the colormap images. Sensitivity, specificity, and accuracy of the classification were computed. Weighted κ statistics summarized agreement of categorical gradings. RESULTS: Median time interval between two visits was 4.4 years (range: 1.0-16.8). Clinicians detected glaucoma deterioration in 25 to 27 of the progressive group and 8 to 10 of stable eyes based on subtraction maps. Sensitivities/specificities of the clinicians were 0.76 to 0.82 and 0.86 to 0.89, respectively. Classification accuracy ranged from 81.5% to 84.8%. Agreement among clinicians was good (weighted κ = 0.68; 95% confidence interval [CI]: 0.60-0.77) for progression grades (1-5 scales) and was substantial (weighted κ = 0.81; 95% CI: 0.74-0.85) for binary scores. CONCLUSIONS: The proposed software provides a single static image that clinicians can use with other structural/functional tests to detect glaucoma progression. TRANSLATIONAL RELEVANCE: Provision of a subtraction colormap in the setting of electronic medical records can improve monitoring of glaucoma by alerting clinicians to possible signs of progression.
amini@jsei.ucla.edu.
Full articleClassification:
6.20 Progression (Part of: 6 Clinical examination methods)
6.8.2 Posterior segment (Part of: 6 Clinical examination methods > 6.8 Photography)
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
