To measure agreement of plus disease diagnosis among retinopathy of prematurity (ROP) experts. Methods: A set of 34 wide-angle retinal photographs from infants with ROP was compiled on a secure Web site and was interpreted independently by 22 recognized ROP experts. Diagnostic agreement was analyzed using 3-level (plus, pre-plus, or neither) and 2-level (plus or not plus) categorizations. Results: In the 3-level categorization, all experts agreed on the same diagnosis in 4 of 34 images (12%), and the mean weighted statistic for each expert compared with all others was between 0.21 and 0.40 (fair agreement) for 7 experts (32%) and between 0.41 and 0.60 (moderate agreement) for 15 experts (68%). In the 2-level categorization, all experts who provided a diagnosis agreed

Purpose-To measure accuracy of plus disease diagnosis by recognized experts in retinopathy of prematurity (ROP), and to conduct a pilot study examining performance of a computer-based image analysis system, Retinal Image multiScale Analysis (RISA).Methods-Twenty-two ROP experts independently interpreted a set of 34 wide-angle retinal images for presence of plus disease. A reference standard diagnosis based on expert consensus was defined for each image. Images were analyzed by the computer-based system using individual and linear combinations of system parameters for arterioles and venules: integrated curvature (IC), diameter, and tortuosity index (TI). Sensitivity, specificity, and receiver operating characteristic areas under the curve (AUC) for plus disease diagnosis compared to the reference standard were determined for each expert, as well as for the computer-based system.Results-Expert sensitivity ranged from 0.308-1.000, specificity ranged from 0.571-1.000, and AUC ranged from 0.784-1.000. Among individual computer system parameters, venular IC had highest AUC (0.853). Among all computer system parameters, the linear combination of arteriolar IC, arteriolar TI, venular IC, venular diameter, and venular TI had highest AUC (0.967), which was greater than that of 18 (81.8%) of 22 experts.Conclusions-Accuracy of ROP experts for plus disease diagnosis is imperfect. A computer-based image analysis system has potential to diagnose plus disease with high accuracy. Further research

No abstract

No abstract

No abstract