Discrimination of glaucomatous from non-glaucomatous optic neuropathy with swept-source optical coherence tomography.
Atrophie optique
Couche de cellules ganglionnaires
Couche de fibres nerveuses rétiniennes
Ganglion cell layer
Glaucoma
Neuropathie optique
Optic atrophy
Optic neuropathy
Optical coherence tomography
Retinal nerve fiber layer
Tomographie par cohérence optique
Journal
Journal francais d'ophtalmologie
ISSN: 1773-0597
Titre abrégé: J Fr Ophtalmol
Pays: France
ID NLM: 7804128
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
01
11
2022
revised:
27
12
2022
accepted:
02
01
2023
medline:
9
10
2023
pubmed:
21
5
2023
entrez:
20
5
2023
Statut:
ppublish
Résumé
To assess the ability of optic nerve head (ONH) parameters, peripapillary retinal nerve fiber layer (pRNFL), and macular ganglion cell layer (GCL) thickness measurements with swept-source optical coherence tomography (SS-OCT), to discriminate between glaucomatous and non-glaucomatous optic neuropathy (GON and NGON). This retrospective cross-sectional study involved 189 eyes of 189 patients, 133 with GON and 56 with NGON. The NGON group included ischemic optic neuropathy, previous optic neuritis, and compressive, toxic-nutritional, and traumatic optic neuropathy. Bivariate analyses of SS-OCT pRNFL and GCL thickness and ONH parameters were performed. Multivariable logistic regression analysis was employed to obtain predictor variables from OCT values, and the area under the receiver operating characteristic curve (AUROC) was calculated to differentiate between NGON and GON. Bivariate analyses showed that the overall and inferior quadrant of the pNRFL was thinner in the GON group (P=0.044 and P<0.01), while patients with NGON had thinner temporal quadrants (P=0.044). Significant differences between the GON and NGON groups were identified in almost all the ONH topographic parameters. Patients with NGON had thinner superior GCL (P=0.015), but there were no significant differences in GCL overall and inferior thickness. Multivariate logistic regression analysis demonstrated that vertical cup-to-disc ratio (CDR), cup volume, and superior GCL provided independent predictive value for differentiating GON from NGON. The predictive model of these variables along with disc area and age achieved an AUROC=0.944 (95% CI 0.898-0.991). SS-OCT is useful in discriminating GON from NGON. Vertical CDR, cup volume, and superior GCL thickness show the highest predictive value.
Identifiants
pubmed: 37210297
pii: S0181-5512(23)00184-5
doi: 10.1016/j.jfo.2023.01.008
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
941-948Informations de copyright
Copyright © 2023 Elsevier Masson SAS. All rights reserved.