The proposed automated approach for estimating the quality of the tear film closes the gap between the manual and automated assessment, translating the high-speed videokeratoscopy technology from scientific laboratories to a clinical practice.
To develop and test a new method for characterizing Tear Film Surface Quality with high-speed videokeratoscopy utilizing a fractal dimension approach.
The regularity of the reflected pattern in high-speed videokeratoscopy (E300; Medmont) depends on tear film stability. Thus, determining tear film stability can be addressed by estimating the fractal dimension of the reflected pattern. The method is tested on 39 normal subjects. The results of the fractal dimension approach are compared with those obtained using previously proposed automated method, based on a gray-level co-occurrence matrix approach, and with subjective results obtained by two operators that were assessing the video recordings in ideal conditions.
Fractal dimension method was less affected by eye movements and changes in the videokeratoscopic image background than gray-level co-occurrence matrix method. Median difference of the noninvasive break-up time between manual and automated methods was 0.03 s (IQR = 4.47 s) and 0.0 s (IQR = 2.22 s) for gray-level co-occurrence matrix and fractal dimension approaches, respectively. Correlation coefficient with manual noninvasive break-up time was r 2 = 0.86 (P < 0.001) for gray-level co-occurrence matrix approach, and r 2 = 0.82 (P < 0.001) for fractal dimension approach. Significant statistical difference was found between noninvasive break-up measurements of manual and gray-level co-occurrence matrix method (P = 0.008).
The proposed method has the potential to characterize tear film dynamics in more detail compared to previous methods based on high-speed videokeratoscopy. It showed good correlation with manual assessment of tear film.
Department of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland (both authors) *email@example.com
Submitted: February 13, 2017
Accepted: September 17, 2017
Funding/Support: This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 642760.
Conflict of Interest Disclosure: None of the authors have reported a conflict of interest.
Author Contributions and Acknowledgments: Clara Llorens-Quintana, MSc (conceptualization; data curation; formal analysis; investigation; methodology; project administration; resources; software; validation; visualization; writing—original draft; writing—review and editing). D. Robert Iskander, PhD, DSc (conceptualization; formal analysis; funding acquisition; investigation; methodology; project administration; resources; software; supervision; validation; visualization; writing—original draft; writing—review and editing).
The authors thank Dr. Dorota H. Szczesna-Iskander and Maryam Mousavi for performing clinical assessment of patients and high-speed videokeratoscopy images and Dr. David Alonso-Caneiro for providing the custom-written graphic user interface used for manual analysis of high-speed videokeratoscopy recorded images.