Artificial intelligence-enabled retinal vasculometry for prediction of circulatory mortality, myocardial infarction and stroke

• Published in: British journal of ophthalmology Vol. 106; no. 12; pp. 1722 - 1729
• Main Authors: Rudnicka, Alicja Regina, Welikala, Roshan, Barman, Sarah, Foster, Paul J, Luben, Robert, Hayat, Shabina, Khaw, Kay-Tee, Whincup, Peter, Strachan, David, Owen, Christopher G
• Format: Journal Article
• Language: English
• Published: BMA House, Tavistock Square, London, WC1H 9JR BMJ Publishing Group Ltd 01.12.2022; BMJ Publishing Group LTD; BMJ Publishing Group
• Subjects: Accuracy; Artificial Intelligence; Cardiovascular disease; Clinical Science; Diagnostic tests/Investigation; Epidemiology; Female; Health risks; Heart attacks; Humans; Imaging; Incidence; Male; Medical diagnosis; Middle Aged; Mortality; Myocardial Infarction - diagnosis; Ophthalmology; Proportional Hazards Models; Prospective Studies; Public health; Retina; Risk Factors; Stroke; Stroke - diagnosis; Stroke - epidemiology; Veins & arteries; Retina; Epidemiology; Imaging; Public health; Diagnostic tests/Investigation
• ISSN: 0007-1161; 1468-2079; 1468-2079
• DOI: 10.1136/bjo-2022-321842

AimsWe examine whether inclusion of artificial intelligence (AI)-enabled retinal vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction (MI) and circulatory mortality.MethodsAI-enabled retinal vessel image analysis processed images from 88 052 UK Biobank (UKB) participants (aged 40–69 years at image capture) and 7411 European Prospective Investigation into Cancer (EPIC)-Norfolk participants (aged 48–92). Retinal arteriolar and venular width, tortuosity and area were extracted. Prediction models were developed in UKB using multivariable Cox proportional hazards regression for circulatory mortality, incident stroke and MI, and externally validated in EPIC-Norfolk. Model performance was assessed using optimism adjusted calibration, C-statistics and R2 statistics. Performance of Framingham risk scores (FRS) for incident stroke and incident MI, with addition of RV to FRS, were compared with a simpler model based on RV, age, smoking status and medical history (antihypertensive/cholesterol lowering medication, diabetes, prevalent stroke/MI).ResultsUKB prognostic models were developed on 65 144 participants (mean age 56.8; median follow-up 7.7 years) and validated in 5862 EPIC-Norfolk participants (67.6, 9.1 years, respectively). Prediction models for circulatory mortality in men and women had optimism adjusted C-statistics and R2 statistics between 0.75–0.77 and 0.33–0.44, respectively. For incident stroke and MI, addition of RV to FRS did not improve model performance in either cohort. However, the simpler RV model performed equally or better than FRS.ConclusionRV offers an alternative predictive biomarker to traditional risk-scores for vascular health, without the need for blood sampling or blood pressure measurement. Further work is needed to examine RV in population screening to triage individuals at high-risk.