OBJECTIVE: Understanding the determinants of subclinical atherosclerosis may aid in elucidating the pathogenesis of atherosclerosis and guide prevention strategies. In this pilot study, we investigated the role of aortic wall thickness as a measure of subclinical atherosclerosis, assessed a method by which to measure aortic wall thickness using MRI, and attempted to define differences in aortic wall thickness by patient race, sex, and age. SUBJECTS AND METHODS. In this prospective study, 196 participants (99 black, 97 white; 98 men, 98 women) were selected from the Multiethnic Study of Atherosclerosis, which consists of participants 45-84 years old without clinical cardiovascular disease, who were recruited from six study centers in the United States. We performed fast spin-echo double inversion recovery MRI to measure thoracic aortic wall thickness. We tested interobserver agreement using the intraclass correlation coefficient, for sex and race differences in wall thickness using the Mann-Whitney test, and for associations between age and wall thickness using linear regression. RESULTS: Reproducibility was excellent for measurements of average and maximal wall thickness on MRI. Average and maximal wall thickness increased with age (p < 0.001 and p = 0.002, respectively). Men had greater mean average wall thickness (2.32 vs 2.11 mm, p = 0.028) and mean maximal wall thickness (3.85 vs 3.31 mm, p = 0.010) than women. Blacks had greater mean maximal wall thickness than whites (3.74 vs 3.42 mm, p = 0.023). CONCLUSION: MRI is a feasible method to measure aortic wall thickness with high interobserver agreement. Aortic wall thickness increases with age and also varies by race and sex.
OBJECTIVE: Understanding the determinants of subclinical atherosclerosis may aid in elucidating the pathogenesis of atherosclerosis and guide prevention strategies. In this pilot study, we investigated the role of aortic wall thickness as a measure of subclinical atherosclerosis, assessed a method by which to measure aortic wall thickness using MRI, and attempted to define differences in aortic wall thickness by patient race, sex, and age. SUBJECTS AND METHODS. In this prospective study, 196 participants (99 black, 97 white; 98 men, 98 women) were selected from the Multiethnic Study of Atherosclerosis, which consists of participants 45-84 years old without clinical cardiovascular disease, who were recruited from six study centers in the United States. We performed fast spin-echo double inversion recovery MRI to measure thoracic aortic wall thickness. We tested interobserver agreement using the intraclass correlation coefficient, for sex and race differences in wall thickness using the Mann-Whitney test, and for associations between age and wall thickness using linear regression. RESULTS: Reproducibility was excellent for measurements of average and maximal wall thickness on MRI. Average and maximal wall thickness increased with age (p < 0.001 and p = 0.002, respectively). Men had greater mean average wall thickness (2.32 vs 2.11 mm, p = 0.028) and mean maximal wall thickness (3.85 vs 3.31 mm, p = 0.010) than women. Blacks had greater mean maximal wall thickness than whites (3.74 vs 3.42 mm, p = 0.023). CONCLUSION: MRI is a feasible method to measure aortic wall thickness with high interobserver agreement. Aortic wall thickness increases with age and also varies by race and sex.
Authors: Andreas J Schriefl; Georg Zeindlinger; David M Pierce; Peter Regitnig; Gerhard A Holzapfel Journal: J R Soc Interface Date: 2011-12-14 Impact factor: 4.118
Authors: Ashkan A Malayeri; Shunsuke Natori; Hossein Bahrami; Alain G Bertoni; Richard Kronmal; João A C Lima; David A Bluemke Journal: Am J Cardiol Date: 2008-05-24 Impact factor: 2.778
Authors: Li Dong; Jinnan Wang; Vasily L Yarnykh; Hunter R Underhill; Moni B Neradilek; Nayak Polissar; Thomas S Hatsukami; Chun Yuan Journal: J Magn Reson Imaging Date: 2010-08 Impact factor: 4.813
Authors: Simon Veldhoen; Cyrus Behzadi; Thorsten Derlin; Meike Rybczinsky; Yskert von Kodolitsch; Sara Sheikhzadeh; Frank Oliver Henes; Thorsten Alexander Bley; Gerhard Adam; Peter Bannas Journal: Eur Radiol Date: 2014-10-15 Impact factor: 5.315
Authors: Andreas Hessenthaler; Maximilian Balmus; Oliver Röhrle; David Nordsletten Journal: Comput Methods Appl Mech Eng Date: 2020-04-15 Impact factor: 6.756
Authors: Stijntje D Roes; Jos J M Westenberg; Joost Doornbos; Rob J van der Geest; Emmanuelle Angelié; Albert de Roos; Matthias Stuber Journal: Magn Reson Med Date: 2009-01 Impact factor: 4.668