BACKGROUND/AIMS: To document the natural history and to assess the efficacy of interventional therapies in neovascular age related macular degeneration (AMD), an accurate and reproducible method is required for analysis of consecutive fluorescence angiograms. The development and evaluation of an image analysis software for this purpose is described here. It allows for the quantitative analysis of changes in CNV and/or leakage area over time. METHODS: In digitised angiograms, a mouse driven arrow was used to delineate the CNV border. The ratio of the CNV area to the square of the distance between two vessels was automatically calculated by pixel count to compensate for variation in image sizes at different examination times. These results were directly transferred and stored in a database. To assess reproducibility, CNV areas in 20 patients with occult and 20 patients with classic CNV were determined independently by two readers. RESULTS: There was only marginal variability between observers with this method: the mean deviation was 0.01 pixels for classic CNV (95% CI -0.17 to +0.15, SD 0.35) and 0.55 pixels for occult CNV (95% CI -1.06 to -0.04, SD 1.14). CONCLUSIONS: This practical PC based method allows for quantification of angiographic features such as CNV size in early frames and area of leakage in late frames. Limitations include non-readily defined borders in angiograms of poor image quality or indistinct borders of the hyperfluorescent areas of interest. The software is applicable to future clinical trials where the analysis of neovascular complex changes is required, for example, following therapeutic intervention.
BACKGROUND/AIMS: To document the natural history and to assess the efficacy of interventional therapies in neovascular age related macular degeneration (AMD), an accurate and reproducible method is required for analysis of consecutive fluorescence angiograms. The development and evaluation of an image analysis software for this purpose is described here. It allows for the quantitative analysis of changes in CNV and/or leakage area over time. METHODS: In digitised angiograms, a mouse driven arrow was used to delineate the CNV border. The ratio of the CNV area to the square of the distance between two vessels was automatically calculated by pixel count to compensate for variation in image sizes at different examination times. These results were directly transferred and stored in a database. To assess reproducibility, CNV areas in 20 patients with occult and 20 patients with classic CNV were determined independently by two readers. RESULTS: There was only marginal variability between observers with this method: the mean deviation was 0.01 pixels for classic CNV (95% CI -0.17 to +0.15, SD 0.35) and 0.55 pixels for occult CNV (95% CI -1.06 to -0.04, SD 1.14). CONCLUSIONS: This practical PC based method allows for quantification of angiographic features such as CNV size in early frames and area of leakage in late frames. Limitations include non-readily defined borders in angiograms of poor image quality or indistinct borders of the hyperfluorescent areas of interest. The software is applicable to future clinical trials where the analysis of neovascular complex changes is required, for example, following therapeutic intervention.
Authors: J A Chamberlin; N M Bressler; S B Bressler; M J Elman; R P Murphy; T P Flood; B S Hawkins; M G Maguire; S L Fine Journal: Ophthalmology Date: 1989-10 Impact factor: 12.079
Authors: H M Leibowitz; D E Krueger; L R Maunder; R C Milton; M M Kini; H A Kahn; R J Nickerson; J Pool; T L Colton; J P Ganley; J I Loewenstein; T R Dawber Journal: Surv Ophthalmol Date: 1980 May-Jun Impact factor: 6.048
Authors: J S Sunness; J Gonzalez-Baron; C A Applegate; N M Bressler; Y Tian; B Hawkins; Y Barron; A Bergman Journal: Ophthalmology Date: 1999-09 Impact factor: 12.079
Authors: M E J van Velthoven; M D de Smet; R O Schlingemann; M Magnani; F D Verbraak Journal: Graefes Arch Clin Exp Ophthalmol Date: 2006-03-08 Impact factor: 3.117