Age-related changes of the retinal microvasculature

• Published in: PloS one 2019-05, Vol.14 (5), p.e0215916-e0215916
• Main Authors: Orlov, Nikita V, Coletta, Cristopher, van Asten, Freekje, Qian, Yong, Ding, Jun, AlGhatrif, Majd, Lakatta, Edward, Chew, Emily, Wong, Wai, Swaroop, Anand, Fiorillo, Edoardo, Delitala, Alessandro, Marongiu, Michele, Goldberg, Ilya G, Schlessinger, David
• Format: Article
• Language: English
• Subjects: Adult; Age; Aged; Aged, 80 and over; Aging; Aging - physiology; Algorithms; Artificial intelligence; Atherosclerosis; Bifurcations; Biology and Life Sciences; Blood Pressure; Blood vessels; Cardiovascular disease; Cardiovascular diseases; Care and treatment; Cohort Studies; Correlation; Diabetic retinopathy; Echocardiography; Epidemiology; Female; Fractals; Fundus Oculi; Genomics; Health; Humans; Image analysis; Image processing; Laboratories; Macular degeneration; Male; Medical personnel; Medicine and Health Sciences; Microvasculature; Microvessels - anatomy & histology; Microvessels - physiology; Middle Aged; Neurobiology; Neurodegeneration; Neurosciences; Parameterization; Patient outcomes; Pattern recognition; Photography; Physical Sciences; Population studies; Research and Analysis Methods; Retina; Retinal Vessels - anatomy & histology; Retinal Vessels - physiology; Self-similarity; Studies; Tortuosity; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0215916

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