Grimbly, Michaela Joan;
Koopowitz, Sheri-Michelle;
Chen, Ruiye;
Sun, Zihan;
Foster, Paul J;
He, Mingguang;
Stein, Dan J;
... Zhu, Zhuoting; + view all
(2024)
Estimating biological age from retinal imaging: a scoping review.
BMJ Open Ophthalmol
, 9
(1)
, Article e001794. 10.1136/bmjophth-2024-001794.
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Abstract
BACKGROUND/AIMS: 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: 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: 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: 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.
| Type: | Article |
|---|---|
| Title: | Estimating biological age from retinal imaging: a scoping review |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1136/bmjophth-2024-001794 |
| Publisher version: | http://dx.doi.org/10.1136/bmjophth-2024-001794 |
| Language: | English |
| Additional information: | This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
| Keywords: | eye (globe), imaging, public health, retina, Humans, Retina, Aging |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10196421 |
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