Clinical Efficacy of Custom-built Software for the Early Detection of Glaucoma: A Comparison of Axial-length and Major Retinal Artery Location Data
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Purpose: To assess the clinical efficacy for early detection of glaucoma using custom-built image softwarevisualizing 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 of151 healthy Korean eyes. The reference lines of the mean, the lower 5%, and the lower 1% limit were visualizedas a translucent RNFLT graph produced by our software after inputting each subject’s major retinal arteryposition and overlaying the results onto the RNFLT measurements. Fifty-eight additional healthy controland 79 early-glaucoma eyes were collected for the validation group. If a subject’s RNFLT graph was outsidethe reference line of the lower 1% limit, the graph was defined as abnormal. The lower 1% limit, which wasgenerated by three criteria (criterion 1, built-in software; criterion 2, axial-length data; criterion 3, major retinalartery 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 thatof 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 showedhigh clinical efficiency for early detection of glaucoma with negligible user-related variability.
Abstract
Purpose: To assess the clinical efficacy for early detection of glaucoma using custom-built image softwarevisualizing 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 of151 healthy Korean eyes. The reference lines of the mean, the lower 5%, and the lower 1% limit were visualizedas a translucent RNFLT graph produced by our software after inputting each subject’s major retinal arteryposition and overlaying the results onto the RNFLT measurements. Fifty-eight additional healthy controland 79 early-glaucoma eyes were collected for the validation group. If a subject’s RNFLT graph was outsidethe reference line of the lower 1% limit, the graph was defined as abnormal. The lower 1% limit, which wasgenerated by three criteria (criterion 1, built-in software; criterion 2, axial-length data; criterion 3, major retinalartery 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 thatof 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 showedhigh clinical efficiency for early detection of glaucoma with negligible user-related variability.
참고문헌 (14)
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