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Published on: May 25, 2020
Objective grading of the anterior eye
Rachael C Peterson1, James S Wolffsohn
1Centre for Contact Lens Research, University of Waterloo, Waterloo, Canada. rpeterso@uwaterloo.ca
Summary
Objective image analysis of the anterior eye can reliably predict clinical grades for ocular surface conditions. This digital grading method offers a more sensitive and dependable alternative to subjective assessments, improving detection and monitoring.
Area of Science:
- Ophthalmology
- Medical Imaging
- Biomedical Engineering
Background:
- Current subjective grading of anterior ocular surface conditions lacks sensitivity and reliability.
- Objective image analysis offers a potential for more accurate and consistent assessment.
Purpose of the Study:
- To develop objective image analysis methods for grading anterior ocular surface conditions.
- To create a more sensitive and reliable grading system compared to subjective methods.
Main Methods:
- Correlated clinical grading (CCLRU and Efron scales) with digital image analysis of ocular surface images.
- Utilized objective measures including edge-detection and relative-coloration.
- Employed stepwise regression analysis to determine correlations between subjective and objective grades.
Main Results:
- Objective image analysis components accurately predicted average subjective grades.
- Digital grades accounted for 69% to 98% of the subjective variance in grading palpebral redness and bulbar hyperaemia.
- Vessel area and hue were key objective measures correlating with clinical severity.
Conclusions:
- Objective grading of the anterior eye, using vessel areas and hue, can predict clinical severity.
- This digital approach provides a more sensitive and reliable method for detecting and monitoring ocular surface changes.
- Objective grading can be integrated into clinical practice and research, using familiar terminology.
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