Facilitating diabetic retinopathy screening using automated retinal image analysis in underresourced settings.
Indigenous Australians
automated retinal image analysis
diabetic retinopathy
Journal
Diabetic medicine : a journal of the British Diabetic Association
ISSN: 1464-5491
Titre abrégé: Diabet Med
Pays: England
ID NLM: 8500858
Informations de publication
Date de publication:
09 2021
09 2021
Historique:
revised:
17
03
2021
received:
06
12
2020
accepted:
30
03
2021
pubmed:
8
4
2021
medline:
31
3
2022
entrez:
7
4
2021
Statut:
ppublish
Résumé
To evaluate an automated retinal image analysis (ARIA) of indigenous retinal fundus images against a human grading comparator for the classification of diabetic retinopathy (DR) status. Indigenous Australian adults with type 2 diabetes (n = 410) from three remote and very remote primary-care services in the Northern Territory, Australia, underwent teleretinal DR screening. A single, central retinal fundus photograph (opportunistic mydriasis) for each eye was later regraded using a single ARIA and a UK human grader and national DR classification system. The sensitivity and specificity of ARIA were assessed relative to the comparator. Proportionate agreement and a Kappa statistic were also computed. Retinal images from 391 and 393 participants were gradable for 'Any DR' by the human grader and ARIA grader, respectively. 'Any DR' was detected by the human grader in 185 (47.3%) participants and by ARIA in 202 (48.6%) participants (agreement =88.0%, Kappa = 0.76,), whereas proliferative DR was detected in 31 (7.9%) and 37 (9.4%) participants (agreement = 98.2%, Kappa = 0.89,), respectively. The ARIA software had 91.4 (95% CI, 86.3-95.0) sensitivity and 85.0 (95% CI, 79.3-89.5) specificity for detecting 'Any DR' and 96.8 (95% CI, 83.3-99.9) sensitivity and 98.3 (95% CI, 96.4-99.4) specificity for detecting proliferative DR. This ARIA software has high sensitivity for detecting 'Any DR', hence could be used as a triage tool for human graders. High sensitivity was also found for detection of proliferative DR by ARIA. Future versions of this ARIA should include maculopathy and referable DR (CSME and/or PDR). Such ARIA software may benefit diabetes care in less-resourced regions.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e14582Informations de copyright
© 2021 Diabetes UK.
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