Retinal microvascular changes are strongly linked to prevalent and incident cardiovascular disease. These changes can now be mapped with unparalleled accuracy using retinal optical coherence tomography. Novel retinal imaging, combined with the power of deep learning, might soon equip clinicians with unique and precise risk-assessment tools that enable truly individualized patient management.
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References
Seidelmann, S. B. et al. Retinal vessel calibers in predicting long-term cardiovascular outcomes: the Atherosclerosis Risk In Communities study. Circulation 134, 1328–1338 (2016).
Balmforth, C. et al. Chorioretinal thinning in chronic kidney disease links to inflammation and endothelial dysfunction. JCI Insight 1, e89173 (2016).
Arnould, L. et al. The EYE-MI pilot study: a prospective acute coronary syndrome cohort evaluated with retinal optical coherence tomography angiography. Invest. Ophthalmol. Vis. Sci. 59, 4299–4306 (2018).
Poplin, R. et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat. Biomed. Eng. 2, 158–164 (2018).
De Fauw, J. et al. Clinically applicable deep learning for diagnosis and referral in retinal disease. Nat. Med. 24, 1342–1350 (2018).
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Farrah, T.E., Webb, D.J. & Dhaun, N. Retinal fingerprints for precision profiling of cardiovascular risk. Nat Rev Cardiol 16, 379–381 (2019). https://doi.org/10.1038/s41569-019-0205-2
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DOI: https://doi.org/10.1038/s41569-019-0205-2