Arterial stiffness predicts cardiovascular events beyond traditional risk factors. However, the relationship with aging of novel noninvasive measures of aortic function by MRI and their interrelationship with established markers of vascular stiffness remain unclear and currently limit their potential impact. Our aim was to compare age-related changes of central measures of aortic function with carotid distensibility, global carotid–femoral pulse wave velocity, and wave reflections. We determined aortic strain, distensibility, and aortic arch pulse wave velocity by MRI, carotid distensibility by ultrasound, and carotid–femoral pulse wave velocity by tonometry in 111 asymptomatic subjects (54 men, age range: 20 to 84 years). Central pressures were used to calculate aortic distensibility. Peripheral and central pulse pressure, augmentation index, and carotid–femoral pulse wave velocity increased with age, but aortic strain and aortic arch PWV were most closely and specifically related to aging. Ascending aortic (AA) strain and distensibility decreased, respectively, by 5.3±0.5% ( R ² =0.54, P <0.0001) and 13.6±1 kPa ⁻¹ ×10 ⁻³ ( R ² =0.62, P <0.0001), and aortic arch pulse wave velocity increased by 1.6±0.13 m/sec ( R ² =0.60, P <0.0001) for each decade of age after adjustment for gender, body size, and heart rate. We demonstrate in this study a dramatic decrease in AA distensibility before the fifth decade of life in individuals with diverse prevalence of risk factors free of overt cardiovascular disease. In particular, compared with other measures of aortic function, the best markers of subclinical large artery stiffening, were AA distensibility in younger and aortic arch pulse wave velocity in older individuals.

Purpose: To assess if segmentation of the aorta can be accurately achieved using the modulus image of phase contrast (PC) magnetic resonance (MR) acquisitions.Materials and Methods: PC image sequences containing both the ascending and descending aorta of 52 subjects were acquired using three different MR scanners. An automated segmentation technique, based on a 2D+t deformable surface that takes into account the features of PC aortic images, such as flow‐related effects, was developed. The study was designed to: 1) assess the variability of our approach and its robustness to the type of MR scanner, and 2) determine its sensitivity to aortic dilation and its accuracy against an expert manual tracing.Results: Interobserver variability in the lumen area was 0.59 ± 0.92% for the automated approach versus 10.09 ± 8.29% for manual segmentation. The mean Dice overlap measure was 0.945 ± 0.014. The method was robust to the aortic size and highly correlated (r = 0.99) with the manual tracing in terms of aortic area and diameter.Conclusion: A fast and robust automated segmentation of the aortic lumen was developed and successfully tested on images provided by various MR scanners and acquired on healthy volunteers as well as on patients with a dilated aorta. J. Magn. Reson. Imaging 2010;31:881–888. ©2010 Wiley‐Liss, Inc.

Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance (CMR) data.

Early detection of diastolic dysfunction is crucial for patients with incipient heart failure. Although this evaluation could be performed from phase-contrast (PC) cardiovascular magnetic resonance (CMR) data, its usefulness in clinical routine is not yet established, mainly because the interpretation of such data remains mostly based on manual post-processing. Accordingly, our goal was to develop a robust process to automatically estimate velocity and flow rate-related diastolic parameters from PC-CMR data and to test the consistency of these parameters against echocardiography as well as their ability to characterize left ventricular (LV) diastolic dysfunction.