Research Repository

Improving Glaucoma Diagnosis by the Combination of Perimetry and HRT Measurements

Mardin, CY and Peters, A and Horn, F and Jünemann, AG and Lausen, B (2006) 'Improving Glaucoma Diagnosis by the Combination of Perimetry and HRT Measurements.' Journal of Glaucoma, 15 (4). pp. 299-305. ISSN 1057-0829

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Purpose: The aim of this study was to determine, whether the combination of morphologic data of the optic nerve head and visual field (VF) data would improve diagnosis of glaucoma, on the basis of the measurements alone. Patients and Methods: Eighty-eight perimetric glaucomatous and 88 normal optic discs from the Erlangen Glaucoma Registry were matched for age. All normals and patients were examined in a standardized manner (Slitlamp biomicroscopy, gonioscopy, 24 h-applanation tonometry, automated VF testing, 15-degree optic disc stereographs, and Heidelberg Retina Tomograph (HRT)-scanning of the optic disc). The HRT variables were calculated in 4 optic disc sectors. All variables were calculated with the software's standard reference plane. To gain the same allocation of sectors as provided by the HRT software, the VF responses were averaged within 4 sectors. Classification results of these VF responses were compared with the summarized results within 4 sectors. Six different combinations of morphologic and VF data were used to assess their suitability to diagnose the disease. HRT measurements, and the standard output of the Octopus (HRT/PERI1), HRT measurements and the summarized sectors and their standard deviations (HRT/PERI2), HRT measurements, standard output of the octopus and the summarized sectors and their standard deviations (HRT/PERI1/PERI2), standard output of the Octopus (PERI1), summarized sectors of the Octopus and their standard deviations (PERI2) and HRT measurements. To assess the diagnostic value of the different data sets machine learning classifiers, stabilized linear discriminant analysis, classification trees, bagging, and double-bagging were applied. Results: Combination of morphologic and VF data improved the automated classification rules. The accuracy to diagnose glaucoma just by VF and HRT indices was maximized for double-bagging using both diagnostic tools. An estimated misclassification probability of less than 0.07 could be achieved for the primary open angle glaucoma patients combining HRT and VF sectors by double bagging. So highest sensitivity was 95% and specificity 91%, achieved by double-bagging and combination of HRT, PERI1, and PERI2. Conclusions: The combination of optic disc measurements and VF data could not only improve glaucoma diagnosis in future, but could also help to find an objective way to diagnose glaucomatous optic atrophy. The limitation of the topographic relationship between structure and function is the individual variability of the optic disc morphology and the subjective variability of VF testing.

Item Type: Article
Uncontrolled Keywords: HRT; glaucoma; perimetry; automated diagnosis
Subjects: R Medicine > RE Ophthalmology
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 13 Jun 2012 10:19
Last Modified: 06 Jan 2022 13:24

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