Purpose: To assess the repeatability and reliability of semi-automated EyeMark Python program measurements compared to manual ImageJ image processing of anterior segment-optical coherence tomography (AS-OCT) structures in healthy and keratoconus eyes.
Methods: Heidelberg AS-OCT was used to image 25 eyes from 14 healthy subjects and 25 eyes from 15 subjects with keratoconus between the ages of 20 and 80 years, collected prospectively, in this observational case-control study. Visual axis scan containing vertical fixation light beam was selected from the 15-line AS-OCT scan raster. Central corneal thickness (CCT), anterior corneal radius of curvature (ACRC), posterior corneal radius of curvature (PCRC), and truncated anterior vault (TAV) were measured using ImageJ software and the EyeMark Python program. MedCalc and R were used to calculate the intraclass correlation coefficient (ICC) and generate Bland-Altman plots (BAP).
Results: When comparing the measurements of CCT, ACRC, PCRC, and TAV between manual ImageJ analysis and the EyeMark Python program, ICC values were consistently greater than 0.9, indicating excellent agreement. BAPs comparing the ImageJ and Python measurements of anterior segment structures show no systematic proportional bias and the average differences were near zero and within 95% of the limits of agreement.
Conclusions: Semi-automated tools may provide the necessary efficiency for point-of-care quantitative corneal analysis of raw AS-OCT images. The semi-automated EyeMark Python program offers a repeatable and reliable tool compared to manual ImageJ analysis for measuring anterior segment structures from AS-OCT images among individuals with keratoconus.
Keywords: Anterior segment optical coherence tomography; Corneal image analysis; EyeMark Python; ImageJ; Keratoconus.
© 2023. The Author(s), under exclusive licence to Springer Nature B.V.