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Correlation of vascular and fluid‐related parameters in neovascular age‐related macular degeneration using deep learning

PURPOSE: To identify correlations between the vascular characteristics of macular neovascularization (MNV) obtained by optical coherence tomography angiography (OCTA) and distinct retinal fluid volumes in neovascular age‐related macular degeneration (nAMD). METHODS: In this prospective interventiona...

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Detalles Bibliográficos
Autores principales: Schranz, Markus, Told, Reinhard, Hacker, Valentin, Reiter, Gregor S., Reumueller, Adrian, Vogl, Wolf‐Dieter, Bogunovic, Hrvoje, Sacu, Stefan, Schmidt‐Erfurth, Ursula, Roberts, Philipp K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10087766/
https://www.ncbi.nlm.nih.gov/pubmed/35912717
http://dx.doi.org/10.1111/aos.15219
Descripción
Sumario:PURPOSE: To identify correlations between the vascular characteristics of macular neovascularization (MNV) obtained by optical coherence tomography angiography (OCTA) and distinct retinal fluid volumes in neovascular age‐related macular degeneration (nAMD). METHODS: In this prospective interventional study, 54 patients with treatment‐naïve type 1 or 2 nAMD were included and treated with intravitreal aflibercept. At baseline and month 1, each patient underwent a SD‐OCT volume scan and volumetric flow scan using a swept‐source OCTA. A deep learning algorithm was used to automatically detect and quantify fluid in OCT scans. Angio Tool, a National Cancer Institute algorithm, was used to skeletonize MNV properties and quantify lesion size (LS), vessel area (VA), vessel density (VD), total number of endpoints (TNE), total number of junctions (TNJ), junction density (JD), total vessel length (TVL), average vessel length (AVL) and mean‐e‐lacunarity (MEL). Subsequently, linear regression models were used to investigate a correlation between OCTA parameters and fluid quantifications. RESULTS: The median amount of fluid within the central 6‐mm EDTRS ring was 173.7 nl at baseline, consisting of 156.6 nl of subretinal fluid (SRF) and 2.3 nl of intraretinal fluid (IRF). Fluid decreased significantly in all compartments to 1.76 nl (SRF) and 0.64 nl (IRF). The investigated MNV parameters did not change significantly after the first treatment. There was no significant correlation between MNV parameters and relative fluid decrease after anti‐VEGF treatment. Baseline fluid correlated statistically significant but weakly with TNE (p = 0.002, R (2) = 0.17), SRF with TVL (p = 0.04, R (2) = 0.08), VD (p = 0.046, R (2) = 0.08), TNE (p = 0.001, R (2) = 0.20) and LS (p = 0.033, R (2) = 0.09). IRF correlated with VA (p = 0.042, R (2) = 0.08).The amount of IRF at month 1 correlated significantly but weakly with VD (p = 0.036, R (2) = 0.08), JD (p = 0.019, R (2) = 0.10) and MEL (p = 0.005, R (2) = 0.14). CONCLUSION: Macular neovascularization parameters at baseline and month 1 played only a minor role in the exudation process in nAMD. None of the MNV parameters were correlated with the treatment response.