TY - JOUR
T1 - Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank
AU - Cecelja, Marina
AU - Ruijsink, Bram
AU - Puyol-Antón, Esther
AU - Li, Ye
AU - Godwin, Harriet
AU - King, Andrew P.
AU - Razavi, Reza
AU - Chowienczyk, Phil
N1 - Funding Information:
The authors acknowledge financial support the National Institute for Health Research (NIHR) Cardiovascular MedTech Co-operative (previously existing as the Cardiovascular Healthcare Technology Co-operative 2012–2017) award to the Guy’s and St Thomas’ National Health Service (NHS) Foundation Trust, in partnership with King’s College London and the NIHR comprehensive Biomedical Research Centre of the Guy’s & St Thomas’ NHS Foundation Trust. This work was also supported by the Wellcome/EPSRC Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Wellcome Trust, EPSRC, or the Department of Health. This research was funded in part by the Wellcome Trust for the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.
Publisher Copyright:
© 2022 The Authors.
PY - 2022
Y1 - 2022
N2 - BACKGROUND: Automated analysis of cardiovascular magnetic resonance images provides the potential to assess aortic dis-tensibility 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 (P<0.0001) 10−3 mm Hg−1, respectively. There was a good correlation between automatically and manually obtained systolic and diastolic aortic areas (r=0.980 and r=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; P=0.016). There was no evidence of an association between pulse pressure (adjusted HR 1.00; P=0.715) or stiffness index (adjusted HR, 1.02; P=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.
AB - BACKGROUND: Automated analysis of cardiovascular magnetic resonance images provides the potential to assess aortic dis-tensibility 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 (P<0.0001) 10−3 mm Hg−1, respectively. There was a good correlation between automatically and manually obtained systolic and diastolic aortic areas (r=0.980 and r=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; P=0.016). There was no evidence of an association between pulse pressure (adjusted HR 1.00; P=0.715) or stiffness index (adjusted HR, 1.02; P=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.
KW - aortic stiffness
KW - distensibility
KW - outcome
UR - http://www.scopus.com/inward/record.url?scp=85143611061&partnerID=8YFLogxK
U2 - 10.1161/JAHA.122.026361
DO - 10.1161/JAHA.122.026361
M3 - Article
C2 - 36444831
AN - SCOPUS:85143611061
SN - 2047-9980
VL - 11
JO - Journal of the American Heart Association
JF - Journal of the American Heart Association
IS - 23
M1 - e026361
ER -