An interinstitutional comparative study and validation of computer aided drusen quantification. Issue 5 (15th April 2005)

• Record Type: Journal Article
• Authors: Sivagnanavel, V; Smith, R T; Lau, G B; Chan, J; Donaldson, C; Chong, N V
• Is Part Of: British journal of ophthalmology. Volume 89:Issue 5(2005)
• Page Start: 554
• Page End: 557
• Publication Date: 2005-04-15
• Subjects: AMD, age related macular degeneration -- ARM, age related maculopathy -- ICC, intraclass correlation coefficient -- RPE, retinal pigment epithelium; drusen -- macula; Ophthalmology -- Periodicals; 617.7
• DOI: 10.1136/bjo.2004.046813
• Languages: English
• ISSNs: 0007-1161

Abstract

Abstract : Aims: To assess the portability and clinical applicability of a software program based on Photoshop (Adobe Systems Inc, San Jose, CA, USA) for digital drusen quantification. Methods: Independent graders from the Digital Fundus Photo Reading Center of Columbia University and King's College Hospital used macular background levelling software to quantify the percentage of drusen in the central and middle Wisconsin subfields. 100 images of consecutive patients with choroidal neovascularisation in one eye and significant drusen in the other eye were analysed to determine suitability, and 10 were chosen for assessment by this software. Results: Of the 10 images used in the interinstitutional validation, the random effects ANOVA for the central and middle subfields showed a high degree of interobserver agreement. The ICC for interobserver reliability was 0.83 (95% CI: 67 to 95) for the central subfield and 0.84 (95% CI: 69 to 99) for the middle subfield. Overall agreement with the manual grading results was good and the within patient coefficient of variation was about 20% for all the pairwise comparisons between observers and the manual stereo gradings. Of the 100 images used to assess practical applicability of the software, 79 were suitable for semiautomated analysis. 13 had extensive mixed retinal pigment epithelial (RPE) changes limiting drusen identification, five had a significant number of reticular drusen, which are poorly identified by the software, and three had multiple small areas of RPE atrophy, which are difficult to distinguish from drusen. Conclusions: The software was successfully used by two institutions demonstrating portability, with good correlation between graders and to the manual stereo grading. Digital drusen quantification was possible in 79% of the images analysed.