Cargando…

Combined Multi-Modal Assessment of Glaucomatous Damage With Electroretinography and Optical Coherence Tomography/Angiography

PURPOSE: To compare the diagnostic performance and to evaluate the interrelationship of electroretinographical and structural and vascular measures in glaucoma. METHODS: For 14 eyes of 14 healthy controls and 15 eyes of 12 patients with glaucoma ranging from preperimetric to advanced stages optical...

Descripción completa

Detalles Bibliográficos
Autores principales: Al-Nosairy, Khaldoon O., Prabhakaran, Gokulraj T., Pappelis, Konstantinos, Thieme, Hagen, Hoffmann, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7645242/
https://www.ncbi.nlm.nih.gov/pubmed/33200048
http://dx.doi.org/10.1167/tvst.9.12.7
Descripción
Sumario:PURPOSE: To compare the diagnostic performance and to evaluate the interrelationship of electroretinographical and structural and vascular measures in glaucoma. METHODS: For 14 eyes of 14 healthy controls and 15 eyes of 12 patients with glaucoma ranging from preperimetric to advanced stages optical coherence tomography (OCT), OCT-angiography (OCT-A), and electrophysiological measures (multifocal photopic negative response ratio [mfPhNR] and steady-state pattern electroretinography [ssPERG]) were applied to assess changes in retinal structure, microvasculature, and function, respectively. The diagnostic performance was assessed via area-under-curve (AUC) measures obtained from receiver operating characteristics analyses. The interrelation of the different measures was assessed with correlation analyses. RESULTS: The mfPhNR, ssPERG amplitude, parafoveal (pfVD) and peripapillary vessel density (pVD), macular ganglion cell inner plexiform layer thickness (mGCIPL) and peripapillary retinal nerve fiber layer thickness (pRNFL) were significantly reduced in glaucoma. The AUC for mfPhNR was highest among diagnostic modalities (AUC: 0.88, 95% confidence interval: 0.75–1.0, P < 0.001), albeit not statistically different from that for macular (mGCIPL: 0.76, 0.58–0.94, P < 0.05; pfVD: 0.81, 0.65–0.97, P < 0.01) or peripapillary imaging (pRNFL: 0.85, 0.70–1.0, P < 0.01; pVD: 0.82, 0.68–0.97, P < 0.01). Combined functional/vascular measures yielded the highest AUC (mfPhNR-pfVD: 0.94, 0.85–1.0, P < 0.001). The functional/structural measure correlation (mfPhNR-mGCIPL correlation coefficient [r(s)]: 0.58, P = 0.001; mfPhNR-pRNFL r(s): 0.66, P < 0.001) was stronger than the functional-vascular correlation (mfPhNR-pfVD r(s): 0.29, P = 0.13; mfPhNR-pVD r(s): 0.54, P = 0.003). CONCLUSIONS: The combination of ERG measures and OCT-A improved diagnostic performance and enhanced understanding of pathophysiology in glaucoma. TRANSLATIONAL RELEVANCE: Multimodal assessment of glaucoma damage improves diagnostics and monitoring of disease progression.