Purpose: To describe a new image analysis method and software for anterior chamber images obtained by the anterior-segment optical coherence tomography (AS-OCT).and to assess its intraobserver and interobserver measurement reproducibility.
Methods: Twenty 8-bit grayscale 600 x 300 AS-OCT images with apparent wide angles and twenty images with apparent narrow angles were consecutively selected from a database. Two glaucoma fellowship-trained ophthalmologists used proprietary image analysis software to analyze the images twice. Algorithms defined the borders and curvatures of anterior chamber (AC) structures and measured AC parameters using scleral spur location as the only observer input. Intraobserver and interobserver reproducibility of scleral spur location and angle parameters was calculated in terms of limits of agreement (LOA; mean of differences ?1.96 x standard deviation (SD) of differences) and coefficient of variation (CV; SD of differences / overall mean).
Results: The analysis software successfully measured all parameters in all images. When the same image was assessed twice by the same grader, the mean differences were ranged from 0 to 0.010 mm in linear measurements and 0.001 to 0.006 mm2 in angle area measurements. LOA tended to be greater in the wider angles. The upper and lower limit values of LOAs were approximately 1/5 ~ 1/4 of the overall means. Measurements between two graders had higher variance. Reproducibility in terms of CV was better in wide angles when compared to narrow ones. The reproducibility of scleral spur placement between observers was poorer in narrow angles (p =0.001). About 50% of the inter-observer variance in angle area measurements was attributable to the variance of scleral spur placement while this proportion was only 10~20% in linear measurements.
Conclusions: Determination of angle parameters using semi-automated software leads to variability in measurement which is increased when more than one observer identifies the scleral spur. Variability differs in narrow and open angles, and therefore including both types is essential when evaluating angle assessment software. Fully automated analysis and higher image resolution would likely improve quantification of Visante?AS-OCT images.