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PLoS One. 2019 May 2;14(5):e0215916. doi: 10.1371/journal.pone.0215916. eCollection 2019.

Age-related changes of the retinal microvasculature.

Author information

1
Laboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
2
Division of Epidemiology and Clinical Applications, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
3
Neurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
4
Laboratory of Cardiovascular Science, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
5
Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.
6
Department of Clinical and Experimental Medicine, Azienda Ospedaliero Universitaria di Sassari, Sassari, Italy.

Abstract

PURPOSE:

Blood vessels of the retina provide an easily-accessible, representative window into the condition of microvasculature. We investigated how retinal vessel structure captured in fundus photographs changes with age, and how this may reflect features related to patient health, including blood pressure.

RESULTS:

We used two approaches. In the first approach, we segmented the retinal vasculature from fundus photographs and then we correlated 25 parameterized aspects ("traits")-comprising 15 measures of tortuosity, 7 fractal ranges of self-similarity, and 3 measures of junction numbers-with participant age and blood pressure. In the second approach, we examined entire fundus photographs with a set of algorithmic CHARM features. We studied 2,280 Sardinians, ages 20-28, and an U.S. based population from the AREDS study in 1,178 participants, ages 59-84. Three traits (relating to tortuosity, vessel bifurcation number, and vessel endpoint number) showed significant changes with age in both cohorts, and one additional trait (relating to fractal number) showed a correlation in the Sardinian cohort only. When using second approach, we found significant correlations of particular CHARM features with age and blood pressure, which were stronger than those detected when using parameterized traits, reflecting a greater signal from the entire photographs than was captured in the segmented microvasculature.

CONCLUSIONS:

These findings demonstrate that automated quantitative image analysis of fundus images can reveal general measures of patient health status.

Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: Ilya G. Goldberg is employed by Mindshare Medical, Inc. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

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