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Reliability, repeatability, and accordance between three different corneal diagnostic imaging devices for evaluating
Abril L Garcia-Terraza1,2, David Jimenez-Collado1,3, Francisco Sanchez-Sanoja1,4
1Department of Cornea and Refractive Surgery, Conde de Valenciana Institute of Ophthalmology, Mexico City, Mexico.
Frontiers in Medicine
|August 15, 2022
Summary
Ocular surface measurements vary significantly between imaging devices, impacting repeatability and reproducibility. This highlights differences in image processing and device performance for tear meniscus height and non-invasive tear break-up time.
Area of Science:
- Ophthalmology
- Optometry
- Biomedical Imaging
Background:
- Ocular surface assessment is crucial for diagnosing and managing dry eye disease.
- Standardization of measurements across different imaging devices remains a challenge.
Purpose of the Study:
- To evaluate the repeatability, reproducibility, and agreement of ocular surface measurements obtained from three distinct corneal imaging devices.
- To compare tear meniscus height, non-invasive tear break-up time (NITBUT), and meibography data across devices.
Main Methods:
- An observational study was conducted on 66 healthy eyes.
- Measurements included tear meniscus height, NITBUT, and meibography using Keratograph 5M, Antares, and LacryDiag devices.
- Statistical analyses included ANOVA, post-hoc tests, coefficients of variation, intraclass correlation coefficients (ICC), and Fleiss' Kappa Index.
Main Results:
- High coefficients of variation and moderate ICCs indicated variable reliability for tear meniscus height and NITBUT measurements.
- Significant discordance was observed in tear meniscus height and NITBUT measurements between the devices.
- Meibography classification showed discrete to poor agreement between devices (Fleiss' Kappa: -0.00487 upper lid, 0.128 lower lid).
Conclusions:
- Ocular surface measurements demonstrate significant variability depending on the imaging device and parameter analyzed.
- Differences in image processing algorithms contribute to the observed discrepancies between devices.
- Clinical interpretation of ocular surface data requires careful consideration of the device used.
