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

PLoS One. 2018 Apr 3;13(4):e0194694. doi: 10.1371/journal.pone.0194694. eCollection 2018.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cardiovascular Diseases / epidemiology*
  • Cardiovascular Diseases / etiology*
  • Computer Simulation
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Male
  • Middle Aged
  • Odds Ratio
  • Population Surveillance
  • Retina / diagnostic imaging
  • Retina / pathology
  • Retinal Vessels* / diagnostic imaging
  • Retinal Vessels* / pathology
  • Risk Factors
  • Singapore / epidemiology
  • Software*

Grants and funding

This work was supported by Regional Council of Burgundy (Pr Catherine Creuzot-Garcher) and Agence Nationale de la Recherche (FR) (Pr Catherine Creuzot-Garcher). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.