Vascular changes precede tomographic changes in diabetic eyes without retinopathy and improve artificial intelligence diagnostics.
angiography
artificial intelligence
diabetic retinopathy
optical coherence tomography
Journal
Journal of biophotonics
ISSN: 1864-0648
Titre abrégé: J Biophotonics
Pays: Germany
ID NLM: 101318567
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
24
03
2020
revised:
30
04
2020
accepted:
06
05
2020
pubmed:
12
5
2020
medline:
24
6
2021
entrez:
12
5
2020
Statut:
ppublish
Résumé
The purpose of this study was to evaluate early vascular and tomographic changes in the retina of diabetic patients using artificial intelligence (AI). The study included 74 age-matched normal eyes, 171 diabetic eyes without retinopathy (DWR) eyes and 69 mild non-proliferative diabetic retinopathy (NPDR) eyes. All patients underwent optical coherence tomography angiography (OCTA) imaging. Tomographic features (thickness and volume) were derived from the OCTA B-scans. These features were used in AI models. Both OCT and OCTA features showed significant differences between the groups (P < .05). However, the OCTA features indicated early retinal changes in DWR eyes better than OCT (P < .05). In the AI model using both OCT and OCTA features simultaneously, the best area under the curve of 0.91 ± 0.02 was obtained (P < .05). Thus, the combined use of AI, OCT and OCTA significantly improved the early diagnosis of diabetic changes in the retina.
Identifiants
pubmed: 32392370
doi: 10.1002/jbio.202000107
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e202000107Informations de copyright
© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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