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Background: Quantification of aortic morphology plays an important role in the evaluation and follow-up assessment of patients with aortic diseases, but often requires labor-intensive and operator-dependent measurements. Automatic solutions would help enhance their quality and reproducibility., Purpose: To design a deep learning (DL)-based automated approach for aortic landmarks and lumen detection derived from three-dimensional (3D) MRI., Study Type: Retrospective., Population: Three hundred ninety-one individuals (female: 47%, age = 51.9 ± 18.4) from three sites, including healthy subjects and patients (hypertension, aortic dilation, Turner syndrome), randomly divided into training/validation/test datasets (N = 236/77/78). Twenty-five subjects were randomly selected and analyzed by three operators with different levels of expertise., Field Strength/sequence: 1.5-T and 3-T, 3D spoiled gradient-recalled or steady-state free precession sequences., Assessment: Reinforcement learning and a two-stage network trained using reference landmarks and segmentation from an existing semi-automatic software were used for aortic landmark detection and segmentation from sinotubular junction to coeliac trunk. Aortic segments were defined using the detected landmarks while the aortic centerline was extracted from the segmentation and morphological indices (length, aortic diameter, and volume) were computed for both the reference and the proposed segmentations., Statistical Tests: Segmentation: Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetrical surface distance (ASSD); landmark detection: Euclidian distance (ED); model robustness: Spearman correlation, Bland-Altman analysis, Kruskal-Wallis test for comparisons between reference and DL-derived aortic indices; inter-observer study: Williams index (WI). A WI 95% confidence interval (CI) lower bound >1 indicates that the method is within the inter-observer variability. A P-value <0.05 was considered statistically significant., Results: DSC was 0.90 ± 0.05, HD was 12.11 ± 7.79 mm, and ASSD was 1.07 ± 0.63 mm. ED was 5.0 ± 6.1 mm. A good agreement was found between all DL-derived and reference aortic indices (r >0.95, mean bias <7%). Our segmentation and landmark detection performances were within the inter-observer variability except the sinotubular junction landmark (CI = 0.96;1.04)., Data Conclusion: A DL-based aortic segmentation and anatomical landmark detection approach was developed and applied to 3D MRI data for achieve aortic morphology evaluation., Evidence Level: 3 TECHNICAL EFFICACY: Stage 2., (© 2024 International Society for Magnetic Resonance in Medicine.)

Objectives. In cardiovascular magnetic resonance, the 3D time-resolved phase-contrast technique, also known as 4D flow, is gaining increasing attention due to applications that exploit three-directional velocity encoding throughout the cardiac cycle. Blood flow volume assessment usually requires an expert to draw regions of interest (ROI) around the vessel cross section, whereas the errors involved in this estimation have not been thoroughly investigated. Our objective is to quantify the influence of ROI sizing, angulation and spatial resolution of the reconstructed plane employed in blood flow measurements using 4D flow. Approach. Three circular ROIs were drawn around the ascending, arch and descending aorta of healthy volunteers ( n = 27) and patients with a dilated ascending aorta or bicuspid valve ( n = 37). We applied systematic changes of ROI diameter (up to ±10%), tilt angle (up to ±25°) and spatial resolution (from 0.25 to 2 mm) of the reconstructed oblique planes, calculating the effects on net, forward and backward blood flow volumes. Main results. Patients had a larger ascending aorta than healthy volunteers with similar ages and male sex proportion (60 ± 15 y.o. vs 58 ± 16 y.o. and 84% vs 70%, respectively). Higher forward and backward flow volumes were observed in the ascending aorta and the aortic arch of the patients with respect to controls ( p < 0.001), whereas net volumes were similar: 74.0 ± 20.8 ml versus 75.7 ± 21.8 ml ( p = 0.37), respectively. The ascending aorta was the most sensitive to ROI modifications. Changes of ±10% in the ROI diameter and ±25° in tilt angles produced flow volume differences of up to 9 ml (10%) and 18 ml (15%) in controls and patients, respectively. Modifying the reconstructed planes spatial resolution produced flow volume changes below 2 ml. Significance. Since the setting of the ROI size and plane angle could produce errors that represent up to 20% of the forward and/or backward aortic flow volume, a good standardization for vessel segmentation and plane positioning is desirable., (© 2021 Institute of Physics and Engineering in Medicine.)

Background: Arterial pulse wave velocity (PWV) is associated with increased mortality in aging and disease. Several studies have shown the accuracy of applanation tonometry carotid-femoral PWV (Cf-PWV) and the relevance of evaluating central aorta stiffness using 2D cardiovascular magnetic resonance (CMR) to estimate PWV, and aortic distensibility-derived PWV through the theoretical Bramwell-Hill model (BH-PWV). Our aim was to compare various methods of aortic PWV (aoPWV) estimation from 4D flow CMR, in terms of associations with age, Cf-PWV, BH-PWV and left ventricular (LV) mass-to-volume ratio while evaluating inter-observer reproducibility and robustness to temporal resolution., Methods: We studied 47 healthy subjects (49.5 ± 18 years) who underwent Cf-PWV and CMR including aortic 4D flow CMR as well as 2D cine SSFP for BH-PWV and LV mass-to-volume ratio estimation. The aorta was semi-automatically segmented from 4D flow data, and mean velocity waveforms were estimated in 25 planes perpendicular to the aortic centerline. 4D flow CMR aoPWV was calculated: using velocity curves at two locations, namely ascending aorta (AAo) and distal descending aorta (DAo) aorta (S1, 2D-like strategy), or using all velocity curves along the entire aortic centreline (3D-like strategies) with iterative transit time (TT) estimates (S2) or a plane fitting of velocity curves systolic upslope (S3). For S1 and S2, TT was calculated using three approaches: cross-correlation (TTc), wavelets (TTw) and Fourier transforms (TTf). Intra-class correlation coefficients (ICC) and Bland-Altman biases (BA) were used to evaluate inter-observer reproducibility and effect of lower temporal resolution., Results: 4D flow CMR aoPWV estimates were significantly (p < 0.05) correlated to the CMR-independent Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with the strongest correlations for the 3D-like strategy using wavelets TT (S2-TTw) (R = 0.62, 0.65, 0.77 and 0.52, respectively, all p < 0.001). S2-TTw was also highly reproducible (ICC = 0.99, BA = 0.09 m/s) and robust to lower temporal resolution (ICC = 0.97, BA = 0.15 m/s)., Conclusions: Reproducible 4D flow CMR aoPWV estimates can be obtained using full 3D aortic coverage. Such 4D flow CMR stiffness measures were significantly associated with Cf-PWV, BH-PWV, age and LV mass-to-volume ratio, with a slight superiority of the 3D strategy using wavelets transit time (S2-TTw).

Background: Aging-related arterial stiffness is associated with substantial changes in global and local arterial pressures. The subsequent early return of reflected pressure waves leads to an elevated left ventricular (LV) afterload and ultimately to a deleterious concentric LV remodeling., Purpose: To compute aortic time-resolved pressure fields of healthy subjects from 4D flow MRI and to define relevant pressure-based markers while investigating their relationship with age, LV remodeling, as well as tonometric augmentation index (AIx) and pulse wave velocity (PWV)., Study Type: Retrospective., Population: Forty-seven healthy subjects (age: 49.5 ± 18 years, 24 women)., Field Strength/sequence: 3 T/4D flow MRI., Assessment: Spatiotemporal pressure fields were computed by integrating velocity-derived pressure gradients using Navier-Stokes equations, while assuming zero pressure at the sino-tubular junction. To quantify aortic pressure spatiotemporal variations, we defined the following markers: 1) volumetric aortic pressure propagation rates ΔP E1 /ΔV and ΔP E2 /ΔV, representing variations of early and late systolic relative pressure peaks along the aorta, respectively, according to the cumulated aortic volume; 2) ΔA PE1-PE2 defined in four aortic regions as the absolute difference between early and late systolic relative pressure peaks amplitude., Statistical Tests: Linear regression, Wilcoxon rank sum test, Bland-Altman analysis, and intraclass correlation coefficients (ICC)., Results: Spatiotemporal variations of aortic pressure peaks were moderately to highly reproducible (ICC ≥0.50) and decreased significantly with age, in terms of absolute magnitude: ΔP E1 /ΔV (r = 0.70, P < 0.005), ΔP E2 /ΔV (r = -0.45, P < 0.005) and ΔA PE1-PE2 (|r| > 0.39, P < 0.005). ΔP E1 /ΔV was associated with LV remodeling (r = 0.53, P < 0.001) and ascending aorta ΔA PE1-PE2 was associated with AIx (r = -0.59, P < 0.001). Both associations were independent of age and systolic blood pressures. Only weak associations were found between pressure indices and PWV (r ≤ 0.40)., Data Conclusion: 4D flow MRI relative aortic pressures were consistent with physiological knowledge as demonstrated by their significant volumetric and temporal variations with age and their independent association with LV remodeling and augmentation index. Level of Evidence 2 Technical Efficacy Stage 3 J. Magn. Reson. Imaging 2019;50:982-993., (© 2019 International Society for Magnetic Resonance in Medicine.)

Objectives: Aortic distensibility estimation of local aortic stiffness is based on local aortic strains and central pulse pressure (cPP) measurements. Most MRI studies used either brachial PP (bPP) despite differences with cPP, or direct cPP estimates obtained after MRI examination, assuming no major pressure variations. We evaluated the feasibility of assessment of cPP with a specific device fitted with a 6 m long hose (study1) and looked at the influence of using such cPP within the magnet instead of bPP on aortic distensibility in a control population (study 2)., Methods: Brachial and central pressures values were recorded with the SphygmoCor XCEL system fitted with 2 and 6 m long tubing randomly assigned on arms. A 6 m long tubing was used in the second study to measure aortic distensibility with MRI. Aortic distensibility was calculated using either bPP (bAD) or cPP (cAD)., Results: Study1, performed on 38 patients (mean age: 43 ± 17 years), showed no statistical difference between bPP and cPP measured with 2 or 6 m long tubing (0.41 ± 4.45 and 0.78 ± 3.18 mmHg, respectively, both P = ns). In study 2, cAD provided statistically higher values than bAD (1.87 ± 1.43 10 · mmHg, P < 0.001) especially in younger individuals (3.28 ± 0.86 10 · mmHg). The correlation between age and aortic distensibility was stronger with cAD (r = -0.92; P < 0,001) than with bAD (r = -0.88; P < 0.001)., Conclusion: cPP can be estimated with reasonable accuracy during MRI acquisition using a 6 m long tube. Using either cPP or bPP greatly influences aortic distensibility values, especially in young individuals in whom an accurate detection of early or accelerated vascular aging can be of major importance.

Background: Left ventricular (LV) remodeling and aortic stiffness have independent predictive value for all causes and cardiovascular mortality. Because elastic properties of the arterial wall vary along the aortic pathway, we hypothesized that local and regional aortic stiffness could differently impact on LV remodeling., Methods and Results: Regional aortic stiffness was determined from carotid-femoral pulse wave velocity (cfPWV) measured by aplanation tonometry. Aortic arch pulse wave velocity was measured by phase contrast cardiovascular magnetic resonance (CMR). Local stiffness was calculated in the ascending aorta pulse wave velocity (aaPWV) and descending aorta pulse wave velocity using central pulse pressure measurement, cine CMR acquisition, and surface change estimation. CMR LV remodeling was expressed as LV mass to end-diastolic volume ratio.We evaluated 146 study participants (41 ± 15 years) free of overt cardiovascular disease. In stepwise multivariate regression analysis, cfPWV and aaPWV were significantly and independently correlated to mass to end-diastolic volume ratio (partial R = 0.07 and R = 0.10, respectively, all P < 0.005) after adjustment for age, sex, BMI, brachial mean blood pressure, and central pulse pressure. Descending aorta pulse wave velocity was correlated with mass to end-diastolic volume ratio to a lower extent (R = 0.04, P = 0.0115) and aortic arch pulse wave velocity was not independently associated with mass to end-diastolic volume ratio. CfPWV and aaPWV were both independently associated with mass to end-diastolic volume ratio, explaining 5 and 8% of mass to end-diastolic volume ratio variance, respectively., Conclusion: In study participants free of overt cardiovascular disease, stiffness of the ascending aorta representing the local proximal aortic function face to the LV and of the downstream aortic pathway assessed by cfPWV reflecting more advanced alterations of material properties involving the entire aorta, are independent determinants of LV remodeling after adjustment to age, BMI, mean blood pressure, and sex.

Pulse waveform analyses have become established components of cardiovascular research. Recently several methods have been proposed as tools to measure aortic pulse wave velocity (aPWV). The carotid-femoral pulse wave velocity (cf-PWV), the current clinical gold standard method for the noninvasive assessment of aPWV, uses the carotid-to-femoral pulse transit time difference (cf-PTT) and an estimated path length to derive cf-PWV., Objective: The heart-ankle PWV (ha-PWV), brachial-ankle PWV (ba-PWV) and finger-toe (ft-PWV) are also methods presuming to approximate aPWV based on time delays between physiological cardiovascular signals at two locations (~heart-ankle PTT, ha-PTT; ~brachial-ankle PTT, ba-PTT; ~finger-toe PTT, ft-PTT) and a path length typically derived from the subject's height. To test the validity of these methods, we used a detailed 1D arterial network model (143 arterial segments) including the foot and hand circulation., Approach: The arterial tree dimensions and properties were taken from the literature and completed with data from patient scans. We calculated PTTs with all the methods mentioned above. The calculated PTTs were compared with the aortic PTT (aPTT), which is considered as the absolute reference method in this study., Main Results: The correlation between methods and aPTT was good and significant, cf-PTT (R 2   =  0.97; P  <  0.001; mean difference 5  ±  2 ms), ha-PTT (R 2   =  0.96; P  <  0.001; 150  ±  23 ms), ba-PTT (R 2   =  0.96; P  <  0.001; 70  ±  13 ms) and ft-PTT (R 2   =  0.95; P  <  0.001; 14  ±  10 ms). Consequently, good correlation was also observed for the PWV values derived with the tested methods, but absolute values differed because of the different path lengths used., Significance: In conclusion, our computer model-based analyses demonstrate that for PWV methods based on peripheral signals, pulse transit time differences closely correlate with the aortic transit time, supporting the use of these methods in clinical practice.

Purpose: Valvuloarterial impedance (Z VA ), estimating left ventricle (LV) afterload, has been proposed in transthoracic echocardiography (TTE) as a predictor of mortality in aortic valve stenosis (AVS). However, its calculation differs from arterial characteristic impedance (Z C ). Our aim was to apply the concept of Z C calculation to estimate Z VA from MR with carotid tonometry and to evaluate these indices through their associations with symptoms, LV diastolic function and aortic stiffness., Materials and Methods: In 40 patients with AVS (76 ± 13 years), Z VA-TI derived from velocity time integral and E/Ea were estimated by TTE. Z VA-INS , based on Z C formula, calculated as the instantaneous pressure gradient to peak flow ratio and aortic compliance were estimated by using MRI at 1.5 Tesla., Results: Both Z VA estimates were higher in symptomatic than asymptomatic patients (707 ± 22 versus 579 ± 53 dyne.s/cm 5 , P = 0.031 for Z VA-INS and 4.35 ± 0.16 versus 3.33 ± 0.38 mmHg.m 2 /mL, P = 0.018 for Z VA-TI ). Although they were both associated with aortic compliance (r = -0.45; P = 0.006 for Z VA-INS and r = -0.43; P = 0.008 for Z VA-TI ) only Z VA-INS was associated with E/Ea (r = 0.50; P < 0.001). In multivariate analysis to identify determinants of E/Ea, a model including age, mean blood pressure, LV ejection fraction, LV mass, and aortic valve area was performed (R 2  = 0.41; P < 0.01). When Z VA-INS was added to the model, its overall significance was higher R 2  = 0.56 (P < 0.01) and Z VA-INS and LV mass were the only significant determinants., Conclusion: Z VA-INS was more strongly associated with diastolic dysfunction than usual parameters quantifying AVS severity. This new Z VA estimate could improve LV afterload evaluation., Level of Evidence: 1 J. Magn. Reson. Imaging 2017;45:795-803., (© 2016 International Society for Magnetic Resonance in Medicine.)