Purpose: To compare the diagnostic accuracy of minimum rim width (MRW), peripapillary retinal nerve fibre layer (pRNFL) and multilayered macular analysis by Spectralis SD-OCT (Heidelberg Engineering, Germany) in discriminating perimetric glaucoma at different stages of the disease from healthy eyes. Methods: In this multicentre, prospective, evaluation of diagnostic tests study, multilayered macular analysis and MRW and pRNFL were obtained from one eye of 197 glaucoma (76 early, 68 moderate and 53 advanced) and of 83 healthy controls from the Multicenter Italian Glaucoma Imaging Study (MIGIS). The reference standard for classifying eyes as glaucomatous and for staging the disease was the visual field. The main outcome measures were area under the ROC curve (AUC) and sensitivity at fixed specificity (95%). Results: Average MRW and average pRNFL showed the highest and similar diagnostic accuracy in both the whole study population (AUC 0.968 and 0.939) and early glaucoma (AUC 0.956 and 0.929). Among the macular parameters, the three innermost retinal layers combined as the Ganglion Cell Complex provided the highest diagnostic accuracy (AUC 0.931) in the whole population, which was statistically similar to that of average pRNFL but inferior to that of average MRW. Compared to both average MRW and pRNFL, all macular parameters showed statistically significant lower accuracy in early glaucoma, but accuracy in moderate and advanced glaucoma showed no statistically significant differences among three protocols. Conclusion: The diagnostic accuracy of MRW, pRNFL and macular analysis by Spectralis SD-OCT is overall good. MRW and pRNFL analysis performs statistically and clinically better than macular analysis to discriminate early glaucoma from healthy eyes.
Michelessi, M., Riva, I., Martini, E., Figus, M., Frezzotti, P., Agnifili, L., et al. (2019). Macular versus nerve fibre layer versus optic nerve head imaging for diagnosing glaucoma at different stages of the disease: Multicenter Italian Glaucoma Imaging Study. ACTA OPHTHALMOLOGICA, 97(2), e207-e215 [10.1111/aos.13930].
Macular versus nerve fibre layer versus optic nerve head imaging for diagnosing glaucoma at different stages of the disease: Multicenter Italian Glaucoma Imaging Study
Miglior S.;
2019
Abstract
Purpose: To compare the diagnostic accuracy of minimum rim width (MRW), peripapillary retinal nerve fibre layer (pRNFL) and multilayered macular analysis by Spectralis SD-OCT (Heidelberg Engineering, Germany) in discriminating perimetric glaucoma at different stages of the disease from healthy eyes. Methods: In this multicentre, prospective, evaluation of diagnostic tests study, multilayered macular analysis and MRW and pRNFL were obtained from one eye of 197 glaucoma (76 early, 68 moderate and 53 advanced) and of 83 healthy controls from the Multicenter Italian Glaucoma Imaging Study (MIGIS). The reference standard for classifying eyes as glaucomatous and for staging the disease was the visual field. The main outcome measures were area under the ROC curve (AUC) and sensitivity at fixed specificity (95%). Results: Average MRW and average pRNFL showed the highest and similar diagnostic accuracy in both the whole study population (AUC 0.968 and 0.939) and early glaucoma (AUC 0.956 and 0.929). Among the macular parameters, the three innermost retinal layers combined as the Ganglion Cell Complex provided the highest diagnostic accuracy (AUC 0.931) in the whole population, which was statistically similar to that of average pRNFL but inferior to that of average MRW. Compared to both average MRW and pRNFL, all macular parameters showed statistically significant lower accuracy in early glaucoma, but accuracy in moderate and advanced glaucoma showed no statistically significant differences among three protocols. Conclusion: The diagnostic accuracy of MRW, pRNFL and macular analysis by Spectralis SD-OCT is overall good. MRW and pRNFL analysis performs statistically and clinically better than macular analysis to discriminate early glaucoma from healthy eyes.File | Dimensione | Formato | |
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