Abstract
BACKGROUND: Trachomatous trichiasis (TT) will continue to develop among those people who have had repeated infections after active trachoma is controlled. Detecting and treating affected individuals will remain necessary for years; a long "tail" of incident cases is anticipated. As the prevalence of TT declines, there will be fewer cases available for training trachoma graders (TG), necessitating alternative methods. METHODOLOGY/PRINCIPAL FINDINGS: Prospective, diagnostic accuracy study assessing sensitivity and specificity of 3D and 2D photography as a tool for training TG to detect TT. Individuals with TT in Ethiopia were examined, and 2D and 3D clinical images taken. Images were independently graded by four graders for presence or absence of trichiasis and compared to field grading. We recruited 153 participants. Clinical assessments and images were available for 306 eyes. Trichiasis was identified in 204 eyes by field grading. Image grading was performed on a selection of 262 eyes (131 with trichiasis). Most eyes with trichiasis had minor trichiasis (94/131). Pooled sensitivity was 88.3% (3D) and 98.0% (2D); pooled specificity was 59.8% (3D) and 26.8% (2D). 3D photo grading was 33.0% more specific than the 2D photo grading (p = 0.0002). The overall Kappa scores were 0.48 (3D) and 0.25 (2D). We trained 26 novice TG in Ethiopia using 3D images. They were tested on a 3D images set and had 71.4% agreement (kappa 0.46), relative to an expert. They were then tested examining 50 people, and had 86.8% agreement (kappa 0.75). We also tested 27 experienced TG on the same cases (86.4% agreement, kappa 0.75). There was no difference in performance between groups (p = 0.76). All participants preferred 3D over 2D images for training. CONCLUSIONS/SIGNIFICANCE: The slightly higher sensitivity of 2D photos comes at considerable cost in specificity. Training with 3D images enabled novice TG to identify cases as well as experienced TG. 3D were preferred to conventional 2D photos for training. Standardized 3D images of TT could be a useful tool for training TG, in settings where there are now few TT cases.