ArticleGraefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie2022
Automated vs. human evaluation of corneal staining.
Article in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Diagnostic methods for managing dry eyes.World journal of methodology · 2025Article
- A Comprehensive Review Comparing Artificial Intelligence and Clinical Diagnostic Approaches for Dry Eye Disease.Diagnostics (Basel, Switzerland) · 2025Review
- Advanced and interpretable corneal staining assessment through fine grained knowledge distillation.NPJ digital medicine · 2025Article
- The repeatability of tests for dry eye signs and symptoms in the dry eye assessment and management (DREAM) study.Contact lens & anterior eye : the journal of the British Contact Lens Association · 2025Article
- Impact of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Treatment on Dry Eye Disease: A Systematic Review and Meta-Analysis.Nature and science of sleep · 2024Review
- Impact of Clinician Subjectivity on the Assessment of Dry Eye Disease Prevalence in a UK Public Health Care Patient Population.Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- An Automated Grading System Based on Topological Features for the Evaluation of Corneal Fluorescein Staining in Dry Eye Disease.Diagnostics (Basel, Switzerland) · 2023Article
- [Application of Deep Learning Algorithm in the Grading Assessment of Corneal Fluorescein Staining].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023Article
- AES-CSFS: an automatic evaluation system for corneal sodium fluorescein staining based on deep learning.Therapeutic advances in chronic disease · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeCorneal fluorescein staining is one of the most important diagnostic tests in dry eye disease (DED). Nevertheless, the result of this examination is depending on the grader. So far, there is no method for an automated quantification of corneal staining commercially available. Aim of this study was to develop a software-assisted grading algorithm and to compare it with a group of human graders with variable clinical experience in patients with DED.
methodsFifty images of eyes stained with 2 µl of 2% fluorescein presenting different severity of superficial punctate keratopathy in patients with DED were taken under standardized conditions. An algorithm for detecting and counting superficial punctate keratitis was developed using ImageJ with a training dataset of 20 randomly picked images. Then, the test dataset of 30 images was analyzed (1) by the ImageJ algorithm and (2) by 22 graders, all ophthalmologists with different levels of experience. All graders evaluated the images using the Oxford grading scheme for corneal staining at baseline and after 6-8 weeks. Intrarater agreement was also evaluated by adding a mirrored version of all original images into the set of images during the 2nd grading.
resultsThe count of particles detected by the algorithm correlated significantly (n = 30; p < 0.01) with the estimated true Oxford grade (Sr = 0,91). Overall human graders showed only moderate intrarater agreement (K = 0,426), while software-assisted grading was always the same (K = 1,0). Little difference was found between specialists and non-specialists in terms of intrarater agreement (K = 0,436 specialists; K = 0,417 non-specialists). The highest interrater agreement was seen with 75,6% in the most experienced grader, a cornea specialist with 29 years of experience, and the lowest was seen in a resident with 25,6% who had only 2 years of experience.
conclusionThe variance in human grading of corneal staining - if only small - is likely to have only little impact on clinical management and thus seems to be acceptable. While human graders give results sufficient for clinical application, software-assisted grading of corneal staining ensures higher consistency and thus is preferrable for re-evaluating patients, e.g., in clinical trials.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.