Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank.

Background Automated analysis of cardiovascular magnetic resonance images provides the potential to assess aortic distensibility in large populations. The aim of this study was to compare the prediction of cardiovascular events by automated cardiovascular magnetic resonance with those of other simple measures of aortic stiffness suitable for population screening. Methods and Results Aortic distensibility was measured from automated segmentation of aortic cine cardiovascular magnetic resonance using artificial intelligence in 8435 participants. The associations of distensibility, brachial pulse pressure, and stiffness index (obtained by finger photoplethysmography) with conventional risk factors was examined by multivariable regression and incident cardiovascular events by Cox proportional-hazards regression. Mean (±SD) distensibility values for men and women were 1.77±1.15 and 2.10±1.45 (<0.0001) 10 mm Hg, respectively. There was a good correlation between automatically and manually obtained systolic and diastolic aortic areas (=0.980 and =0.985, respectively). In regression analysis, distensibility associated with age, mean arterial pressure, heart rate, weight, and plasma glucose but not male sex, cholesterol or current smoking. During an average follow-up of 2.8±1.3 years, 86 participants experienced cardiovascular events 6 of whom died. Higher distensibility was associated with reduced risk of cardiovascular events (adjusted hazard ratio [HR], 0.61 per log unit of distensibility; =0.016). There was no evidence of an association between pulse pressure (adjusted HR 1.00; =0.715) or stiffness index (adjusted HR, 1.02; =0.535) and risk of cardiovascular events. Conclusions Automated cardiovascular magnetic resonance-derived aortic distensibility may be incorporated into routine clinical imaging. It shows a similar association to cardiovascular risk factors as other measures of arterial stiffness and predicts new-onset cardiovascular events, making it a useful tool for the measurement of vascular aging and associated cardiovascular risk.