Accuracy and Reproducibility of Automated Drusen Segmentation in Eyes with Non-Neovascular Age-Related Macular Degeneration

Abstract

To evaluate the accuracy and reproducibility of drusen quantification by an automated drusen segmentation algorithm in spectral domain optical coherence tomography (SD-OCT) images of eyes with non-neovascular age-related macular degeneration (AMD). Drusen segmentation was performed using both a commercial automated algorithm (Cirrus OCT RPE analysis tool) and manual segmentation in 44 eyes of 30 subjects with dry AMD who underwent volume OCT scanning. The drusen (space between outer RPE layer and Bruch's membrane) was segmented automatically using an automated RPE tool and manually by 3D-OCTOR software. Drusen area and volume were calculated in all eyes. Age and visual acuity data were also collected. Reproducibility of manual and automated measurements was assessed by intraclass correlation (ICC). The mean age of subjects was 78.24 (± 9.4; range, 56-97 years). The mean logMAR (logarithm of the minimum angle of resolution) visual acuity was 0.4 (Snellen equivalent, ~20/50) (standard deviation, 0.40; range, 0-1.3). The mean (standard deviation) drusen area was 5.05 (3.67) mm(2) with manual segmentation and 4.66 (3.51) mm(2) with the automated RPE tool; the absolute difference was 2.63 (2.5) mm(2). The mean drusen volume was 1.49 (0.42) mm(3) with manual segmentation and 1.42 (0.43) mm(3) with the automated RPE tool; the absolute difference was 1.42 (0.43) mm(3). The agreement between manual and automated measurements of drusen volume (highest ICC = 0.95) was better than the agreement for drusen area (ICC = 0.65). The quantification of drusen area and volume using an automated RPE yielded better agreement for volume than for area when compared with human expert manual segmentation. Using this software, drusen volume measurements may be a useful tool for quantifying drusen burden in clinical trials and clinical practice.