Estimating biological age from retinal imaging: a scoping review.
eye (globe)
imaging
public health
retina
Journal
BMJ open ophthalmology
ISSN: 2397-3269
Titre abrégé: BMJ Open Ophthalmol
Pays: England
ID NLM: 101714806
Informations de publication
Date de publication:
24 Aug 2024
24 Aug 2024
Historique:
received:
24
05
2024
accepted:
25
07
2024
medline:
26
8
2024
pubmed:
26
8
2024
entrez:
24
8
2024
Statut:
epublish
Résumé
The emerging concept of retinal age, a biomarker derived from retinal images, holds promise in estimating biological age. The retinal age gap (RAG) represents the difference between retinal age and chronological age, which serves as an indicator of deviations from normal ageing. This scoping review aims to collate studies on retinal age to determine its potential clinical utility and to identify knowledge gaps for future research. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist, eligible non-review, human studies were identified, selected and appraised. PubMed, Scopus, SciELO, PsycINFO, Google Scholar, Cochrane, CINAHL, Africa Wide EBSCO, MedRxiv and BioRxiv databases were searched to identify literature pertaining to retinal age, the RAG and their associations. No restrictions were imposed on publication date. Thirteen articles published between 2022 and 2023 were analysed, revealing four models capable of determining biological age from retinal images. Three models, 'Retinal Age', 'EyeAge' and a 'convolutional network-based model', achieved comparable mean absolute errors: 3.55, 3.30 and 3.97, respectively. A fourth model, 'RetiAGE', predicting the probability of being older than 65 years, also demonstrated strong predictive ability with respect to clinical outcomes. In the models identified, a higher predicted RAG demonstrated an association with negative occurrences, notably mortality and cardiovascular health outcomes. This review highlights the potential clinical application of retinal age and RAG, emphasising the need for further research to establish their generalisability for clinical use, particularly in neuropsychiatry. The identified models showcase promising accuracy in estimating biological age, suggesting its viability for evaluating health status.
Sections du résumé
BACKGROUND/AIMS
OBJECTIVE
The emerging concept of retinal age, a biomarker derived from retinal images, holds promise in estimating biological age. The retinal age gap (RAG) represents the difference between retinal age and chronological age, which serves as an indicator of deviations from normal ageing. This scoping review aims to collate studies on retinal age to determine its potential clinical utility and to identify knowledge gaps for future research.
METHODS
METHODS
Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist, eligible non-review, human studies were identified, selected and appraised. PubMed, Scopus, SciELO, PsycINFO, Google Scholar, Cochrane, CINAHL, Africa Wide EBSCO, MedRxiv and BioRxiv databases were searched to identify literature pertaining to retinal age, the RAG and their associations. No restrictions were imposed on publication date.
RESULTS
RESULTS
Thirteen articles published between 2022 and 2023 were analysed, revealing four models capable of determining biological age from retinal images. Three models, 'Retinal Age', 'EyeAge' and a 'convolutional network-based model', achieved comparable mean absolute errors: 3.55, 3.30 and 3.97, respectively. A fourth model, 'RetiAGE', predicting the probability of being older than 65 years, also demonstrated strong predictive ability with respect to clinical outcomes. In the models identified, a higher predicted RAG demonstrated an association with negative occurrences, notably mortality and cardiovascular health outcomes.
CONCLUSION
CONCLUSIONS
This review highlights the potential clinical application of retinal age and RAG, emphasising the need for further research to establish their generalisability for clinical use, particularly in neuropsychiatry. The identified models showcase promising accuracy in estimating biological age, suggesting its viability for evaluating health status.
Identifiants
pubmed: 39181547
pii: bmjophth-2024-001794
doi: 10.1136/bmjophth-2024-001794
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: None declared.