Alain De Cesare

Reduced Ascending Aortic Strain and Distensibility Earliest Manifestations of Vascular Aging in Humans

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% (R2=0.54, P<0.0001) and 13.6±1 kPa−1×10−3 (R2=0.62, P<0.0001), and aortic arch pulse wave velocity increased by 1.6±0.13 m/sec (R2=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.

Automated segmentation of the aorta from phase contrast MR images: Validation against expert tracing in healthy volunteers and in patients with a dilated aorta

To assess if segmentation of the aorta can be accurately achieved using the modulus image of phase contrast (PC) magnetic resonance (MR) acquisitions.

Consistency of aortic distensibility and pulse wave velocity estimates with respect to the Bramwell-Hill theoretical model: a cardiovascular magnetic resonance study

BackgroundArterial 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.ResultsForty-six healthy subjects underwent carotid-femoral pulse wave velocity measurements (CF_PWV) by applanation tonometry and CMR with steady-state free-precession and phase contrast acquisitions at the level of the aortic arch. These data were used for the automated evaluation of the aortic arch pulse wave velocity (Arch_PWV), and the ascending aorta distensibility (AA_Distc, AA_Distb), which were estimated from ascending aorta strain (AA_Strain) combined with either carotid or brachial pulse pressure. The local ascending aorta pulse wave velocity AA_PWVc and AA_PWVb were estimated respectively from these carotid and brachial derived distensibility indices according to the Bramwell-Hill theoretical model, and were compared with the Arch_PWV. In addition, a reproducibility analysis of AA_PWV measurement and its comparison with the standard CF_PWV was performed. Characterization according to the Bramwell-Hill equation resulted in good correlations between Arch_PWV and both local distensibility indices AA_Distc (r = 0.71, p < 0.001) and AA_Distb (r = 0.60, p < 0.001); and between Arch_PWV and both theoretical local indices AA_PWVc (r = 0.78, p < 0.001) and AA_PWVb (r = 0.78, p < 0.001). Furthermore, the Arch_PWV was well related to CF_PWV (r = 0.69, p < 0.001) and its estimation was highly reproducible (inter-operator variability: 7.1%).ConclusionsThe present work confirmed the consistency and robustness of the regional index Arch_PWV and the local indices AA_Distc and AA_Distb according to the theoretical model, as well as to the well established measurement of CF_PWV, demonstrating the relevance of the regional and local CMR indices.

Automated left ventricular diastolic function evaluation from phase-contrast cardiovascular magnetic resonance and comparison with Doppler echocardiography

BackgroundEarly 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.ResultsWe studied 35 controls and 18 patients with severe aortic valve stenosis and preserved LV ejection fraction who had PC-CMR and Doppler echocardiography exams on the same day. PC-CMR mitral flow and myocardial velocity data were analyzed using custom software for semi-automated extraction of diastolic parameters. Inter-operator reproducibility of flow pattern segmentation and functional parameters was assessed on a sub-group of 30 subjects. The mean percentage of overlap between the transmitral flow segmentations performed by two independent operators was 99.7 ± 1.6%, resulting in a small variability (<1.96 ± 2.95%) in functional parameter measurement. For maximal myocardial longitudinal velocities, the inter-operator variability was 4.25 ± 5.89%. The MR diastolic parameters varied significantly in patients as opposed to controls (p < 0.0002). Both velocity and flow rate diastolic parameters were consistent with echocardiographic values (r > 0.71) and receiver operating characteristic (ROC) analysis revealed their ability to separate patients from controls, with sensitivity > 0.80, specificity > 0.80 and accuracy > 0.85. Slight superiority in terms of correlation with echocardiography (r = 0.81) and accuracy to detect LV abnormalities (sensitivity > 0.83, specificity > 0.91 and accuracy > 0.89) was found for the PC-CMR flow-rate related parameters.ConclusionsA fast and reproducible technique for flow and myocardial PC-CMR data analysis was successfully used on controls and patients to extract consistent velocity-related diastolic parameters, as well as flow rate-related parameters. This technique provides a valuable addition to established CMR tools in the evaluation and the management of patients with diastolic dysfunction.

Geometry is a major determinant of flow reversal in proximal aorta

The aim of this study is to quantify aortic backward flow (BF) using phase-contrast cardiovascular magnetic resonance (PC-CMR) and to study its associations with age, indexes of arterial stiffness, and geometry. Although PC-CMR blood flow studies showed a simultaneous presence of BF and forward flow (FF) in the ascending aorta (AA), the relationship between aortic flows and aging as well as arterial stiffness and geometry in healthy volunteers has never been reported. We studied 96 healthy subjects [47 women, 39 ± 15 yr old (19-79 yr)]. Aortic stiffness [arch pulse wave velocity (PWVAO), AA distensibility], geometry (AA diameter and arch length), and parameters related to AA BF and FF (volumes, peaks, and onset times) were estimated from CMR. Applanation tonometry carotid-femoral pulse-wave velocity (PWVCF), carotid augmentation index, and time to return of the reflected pressure wave were assessed. Whereas FF parameters remained unchanged, BF onset time shortened significantly (R(2) = 0.18, P < 0.0001) and BF volume and BF-to-FF peaks ratio increased significantly (R(2) = 0.38 and R(2) = 0.44, respectively, P < 0.0001) with aging. These two latter BF indexes were also related to stiffness indexes (PWVCF, R(2) > 0.30; PWVAO, R(2) > 0.24; and distensibility, R(2) > 0.20, P < 0.001), augmentation index (R(2) > 0.20, P < 0.001), and aortic geometry (AA diameter, R(2) > 0.58; and arch length, R(2) > 0.31, P < 0.001). In multivariate analysis, aortic diameter was the strongest independent correlate of BF beyond age effect. In conclusion, AA BF estimated using PC-CMR increased significantly in terms of magnitude and volume and appeared earlier with aging and was mostly determined by aortic geometry. Thus BF indexes could be relevant markers of subclinical arterial wall alterations.

Automated estimation of aortic strain from steady-state free-precession and phase contrast MR images

The strain values extracted from steady‐state free‐precession (SSFP) and phase contrast (PC) images acquired with a 1.5T scanner on a compliant flow phantom and within the thoracic aorta of 52 healthy subjects were compared. Aortic data were acquired perpendicular to the aorta at the level of the pulmonary artery bifurcation. Cross sectional areas were obtained by using an automatic and robust segmentation method. While a good correlation (r = 0.99) was found between the aortic areas extracted from SSFP and PC sequences, a lower correlation (r = 0.71) was found between the corresponding aortic strain values. Strain values estimated using SSFP and PC sequences were equally correlated with age. Interobserver reproducibility was better for SSFP than for PC. Strain values in the ascending and descending aorta were better correlated for SSFP (r = 0.8) than for PC (r = 0.65) and fitted with the expectation of a larger strain in the ascending aorta when using SSFP. The spatial and temporal resolutions of the acquisitions had a minor influence upon the estimated strain values. Thus, if PC acquisitions can be used to estimate both pulse wave velocity and aortic strain, an additional SSFP sequence may be useful to improve the accuracy in estimating the aortic strain. Magn Reson Med, 2010.

REGULARIZED ESTIMATION OF CONTRAST AGENT ATTENUATION TO IMPROVE THE IMAGING OF MICROBUBBLES IN SMALL ANIMAL STUDIES

Quantitative analysis of tissue perfusion using contrast-enhanced ultrasound is still limited by shadowing, which is caused by inadequate compensation for microbubble contrast agent attenuation. Many previous methods have been developed for attenuation correction in soft tissues. However, no method has been proposed to correct for microbubble attenuation in vivo. In this article, a model to estimate microbubble attenuation is presented, using the time-intensity variation in a highly echogenic distal area without contrast uptake. This model is based on the assumption that a linear relationship holds between local microbubble attenuation and local backscatter. The model was applied to 12 murine renal perfusion studies. Parametric images of microbubble attenuation were generated, corresponding to dynamic contrast agent-specific sequences without shadowing. Contrast uptake kinetics consistent with the physiology were retrieved in all perfused areas. This method therefore proved to be of potential interest in the quantification of tissue perfusion in small animal studies.

Using an adaptive semiautomated self-evaluated registration technique to analyze MRI data for myocardial perfusion assessment.

To validate the adaptive semiautomated self‐evaluated registration technique (ASSERT) followed by factor analysis of medical image sequence (FAMIS) for analyzing myocardial perfusion using magnetic resonance imaging (MRI) images.

Calculation of left ventricle relative pressure distribution in MRI using acceleration data.

Measurements of pressure variations within the cardiac chambers could provide important information for clinical assessments of cardiovascular function. In this work an MRI method for evaluating spatial distributions of intracardiac relative pressure is presented. We first calculated pressure gradients from MR maps of blood acceleration by applying the NS equation. We then used an original algorithm to compute pressure distribution in a region of interest (ROI) by minimizing the pressure gradient curl so that the result in a given pixel is independent of the integration path. The method was assessed in five healthy volunteers by means of MR 2D maps of the blood acceleration in the left ventricle (LV) during ejection and filling phases. The pressure variations calculated from acceleration mapping fit the known physiological variations better than those based on velocity maps acquired in the same volunteers. Furthermore, the optimization algorithm presented here produced the same results as iterative algorithms proposed by other authors, but in much less time and without requiring adjustable parameters or boundary conditions. Magn Reson Med 53:877–884, 2005.

How to estimate aortic characteristic impedance from magnetic resonance and applanation tonometry data

Objectives: Compare seven previous methods for the estimation of aortic characteristic impedance, which contributes to left ventricle pulsatile load, from phase-contrast cardiovascular magnetic resonance (CMR) and applanation tonometry data. Methods: We studied 77 healthy (43 ± 16 years) individuals and 16 hypertensive (61 ± 9 years) patients, who consecutively underwent ascending aorta CMR and carotid tonometry, resulting in flow and pressure waveforms, respectively. Characteristic impedance was semi-automatically estimated in time domain from these latter waveforms, using seven methods. The methods were based on the following: methods 1–4, magnitudes at specific times; method 5, early-systolic up-slope; method 6, time-derivatives peak; and method 7, pressure-flow loop early-systolic slope. Results: Aortic characteristic impedance was significantly increased in hypertensive patients when compared to elderly controls (n = 32) with a similar mean age of (59 ± 8 years) when using methods based on 95% of peak flow, up-slopes, and derivatives peaks (P < 0.05). When considering healthy individuals, impedance indices were significantly correlated to central pulse pressure for all methods (P < 0.005). Finally, characteristic impedance was correlated to the frequency-domain reference values (r > 0.65, P < 0.0001), with a slight superiority for the same three methods as above (r > 0.82, P < 0.0001). Conclusions: This is the first study demonstrating phase-contrast CMR and tonometry usefulness in aortic characteristic impedance temporal estimation. Methods based on 95% of peak flow, as well as those based on derivative peaks and up-slopes, which are fast and independent of curve preprocessing, were slightly superior. They can be easily integrated in a clinical workflow and may help to understand the complementarity of this pulsatile index with other CMR aortic geometry and stiffness measures in the setting of left ventricle-aortic coupling.