Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
- Author:
Hyoju JANG
1
;
Sang Min LEE
;
Jaehong AHN
;
Seungsoo RHO
Author Information
- Publication Type:Original Article
- Keywords: Axial length; Database; Glaucoma; Major retinal artery position; Optical coherence tomography
- MeSH: Glaucoma; Nerve Fibers; Prospective Studies; Retinal Artery; Retinaldehyde; Sensitivity and Specificity; Tomography, Optical Coherence; Treatment Outcome
- From:Korean Journal of Ophthalmology 2019;33(2):103-112
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: To assess the clinical efficacy for early detection of glaucoma using custom-built image software visualizing translucent retinal nerve fiber layer thickness (RNFLT) that is graphed based on a normative database. METHODS: This prospective study was conducted using a normative database constructed with RNFLT data of 151 healthy Korean eyes. The reference lines of the mean, the lower 5%, and the lower 1% limit were visualized as a translucent RNFLT graph produced by our software after inputting each subject's major retinal artery position and overlaying the results onto the RNFLT measurements. Fifty-eight additional healthy control and 79 early-glaucoma eyes were collected for the validation group. If a subject's RNFLT graph was outside the reference line of the lower 1% limit, the graph was defined as abnormal. The lower 1% limit, which was generated by three criteria (criterion 1, built-in software; criterion 2, axial-length data; criterion 3, major retinal artery data), was used to address the difference of agreement with a standard answer. RESULTS: For criteria 1, 2, and 3, the accuracy of our custom-built software was significantly higher than that of the manufacturer's database (kappa of 0.475 vs. 0.852 vs. 0.940; sensitivity of 62.0% vs. 91.1% vs. 97.5%, respectively) maintaining high specificity (87.9% vs. 94.8% vs. 96.6%, respectively). CONCLUSIONS: The custom-built imaging software with the constructed RNFLT normative database showed high clinical efficiency for early detection of glaucoma with negligible user-related variability.
