» Articles » PMID: 29614075

Association Between the Retinal Vascular Network with Singapore "I" Vessel Assessment (SIVA) Software, Cardiovascular History and Risk Factors in the Elderly: The Montrachet Study, Population-based Study

Overview
Journal PLoS One
Date 2018 Apr 4
PMID 29614075
Citations 27
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: To identify patterns summarizing the retinal vascular network in the elderly and to investigate the relationship of these vascular patterns with cardiovascular history.

Methods: We conducted a population-based study, the Montrachet study (Maculopathy Optic Nerve nuTRition neurovAsCular and HEarT diseases), in participants older than 75 years. The history of cardiovascular disease and a score-based estimation of their 10-year risk of cardiovascular mortality (Heart SCORE) were collected. Retinal vascular network analysis was performed by means of Singapore "I" Vessel Assessment (SIVA) software. Principal component analysis was used to condense the information contained in the high number of variables provided and to identify independent retinal vascular patterns.

Results: Overall, 1069 photographs (1069 participants) were reviewed with SIVA software. The mean age was 80.0 ± 3.8 years. We extracted three vascular patterns summarizing 41.3% of the vascular information. The most clinically relevant pattern, Sparse vascular network, accounted for 17.4% of the total variance. It corresponded to a lower density in the vascular network and higher variability in vessel width. Diabetic participants with hypoglycemic treatment had a sparser vascular network pattern than subjects without such treatment (odds ratio, [OR], 1.68; 95% CI, 1.04-2.72; P = 0.04). Participants with no history of cardiovascular disease who had a sparser vascular network were associated with a higher Heart SCORE (OR, 1.76; 95% CI, 1.08-2.25; P = 0.02).

Conclusions: Three vascular patterns were identified. The Sparse vascular network pattern was associated with having a higher risk profile for cardiovascular mortality risk at 10 years.

Citing Articles

Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases.

Muthukumar K, Nandi D, Ranjan P, Ramachandran K, Pj S, Ghosh A Sci Rep. 2025; 15(1):4390.

PMID: 39910082 PMC: 11799439. DOI: 10.1038/s41598-025-87634-z.


The Use of Retinal Imaging Including Fundoscopy, OCT, and OCTA for Cardiovascular Risk Stratification and the Detection of Subclinical Atherosclerosis.

Colcombe J, Solli E, Kaiser A, Ranadive I, Bolneni S, Berger J Curr Atheroscler Rep. 2025; 27(1):23.

PMID: 39775159 DOI: 10.1007/s11883-024-01268-6.


Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.

Syed M, Trucco E, Mookiah M, Lang C, McCrimmon R, Palmer C Cardiovasc Diabetol. 2025; 24(1):3.

PMID: 39748380 PMC: 11697721. DOI: 10.1186/s12933-024-02564-w.


Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease.

Iorga R, Costin D, Munteanu-Danulescu R, Rezus E, Moraru A J Pers Med. 2024; 14(5).

PMID: 38793083 PMC: 11122007. DOI: 10.3390/jpm14050501.


A Multi-Stage Approach for Cardiovascular Risk Assessment from Retinal Images Using an Amalgamation of Deep Learning and Computer Vision Techniques.

Prasad D, Manjunath M, Kulkarni M, Kullambettu S, Srinivasan V, Chakravarthi M Diagnostics (Basel). 2024; 14(9).

PMID: 38732342 PMC: 11083022. DOI: 10.3390/diagnostics14090928.


References
1.
Sharrett A, Hubbard L, Cooper L, Sorlie P, Brothers R, Nieto F . Retinal arteriolar diameters and elevated blood pressure: the Atherosclerosis Risk in Communities Study. Am J Epidemiol. 1999; 150(3):263-70. DOI: 10.1093/oxfordjournals.aje.a009997. View

2.
Liew G, Mitchell P, Rochtchina E, Wong T, Hsu W, Lee M . Fractal analysis of retinal microvasculature and coronary heart disease mortality. Eur Heart J. 2010; 32(4):422-9. DOI: 10.1093/eurheartj/ehq431. View

3.
Lim L, Yim-Lui Cheung C, Lin X, Mitchell P, Wong T, Mei-Saw S . Influence of refractive error and axial length on retinal vessel geometric characteristics. Invest Ophthalmol Vis Sci. 2010; 52(2):669-78. DOI: 10.1167/iovs.10-6184. View

4.
Sasongko M, Hodgson L, Wong T, Kawasaki R, Cheung C, Hsu W . Correlation and reproducibility of retinal vascular geometric measurements for stereoscopic retinal images of the same eyes. Ophthalmic Epidemiol. 2012; 19(5):322-7. DOI: 10.3109/09286586.2012.702258. View

5.
Knudtson M, Klein B, Klein R, Wong T, Hubbard L, Lee K . Variation associated with measurement of retinal vessel diameters at different points in the pulse cycle. Br J Ophthalmol. 2003; 88(1):57-61. PMC: 1771926. DOI: 10.1136/bjo.88.1.57. View