Agreement Analysis on Angle Characteristics With Automated Gonioscopy

Abstract

Précis: Automated gonioscopy is a recent method of recording angle pictures. Our study shows that agreement between observers is moderate in most categories used in clinical practice, underlying its clinical usefulness but also room for improvement.Introduction: Iridocorneal angle (ICA) imaging methods have been recently developed to record gonioscopic images. The purpose of this study was to perform an interrater agreement analysis of ICA photographs.Methods: Multicentric cross-sectional observational study. Consecutive patients in 2 ophthalmology departments underwent automated gonioscopy. One picture per quadrant from each eye was selected for randomization. Pictures were graded and analyzed by 4 masked glaucoma specialists regarding angle opening, width, Shaffer and Spaeth gradings and other findings. Fleiss' κ statistics was performed to assess interrater agreement.Results: A total of 50 patients were recruited, with the sample containing a variety of diagnosis including pseudoexfoliation (22%), angle-closure suspect (12%), and pigmentary glaucoma (4%). The sample included phakic (68%) and pseudophakic patients, as well as cases with gonio-implanted surgical devices (10%). There was moderate agreement on angle opening, angle width, presence of angle vessels, and peripheral anterior synechiae (κ = 0.435, 0.511, 0.558, 0.488, respectively; P < 0.01). Fair agreement was observed regarding Shaffer grading, site of iris root insertion, angle pigmentation features, and the presence of iris processes. Expectedly from a 2-dimensional picture, the configuration of peripheral iris was found to have a poor agreement. Subset analysis on higher quality pictures seemed to improve agreement on pigment but did not further improve on the overall good agreement on angle opening status.Conclusions: Our study shows that automated gonioscopy provides moderate agreement on most clinically relevant features. Binary characteristics such as angle opening or PAS seem to be more robust than more complex angle classification parameters.