Four-dimensional flow cardiovascular magnetic resonance aortic cross-sectional pressure changes and their associations with flow patterns in health and ascending thoracic aortic aneurysm.

BACKGROUND: Ascending thoracic aortic aneurysm (ATAA) is a silent and threatening dilation of the ascending aorta (AscAo). Maximal aortic diameter which is currently used for ATAA patients management and surgery planning has been shown to inadequately characterize risk of dissection in a large proportion of patients. Our aim was to propose a comprehensive quantitative evaluation of aortic morphology and pressure-flow-wall associations from four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) data in healthy aging and in patients with ATAA. METHODS: We studied 17 ATAA patients (64.7 ± 14.3 years, 5 females) along with 17 age- and sex-matched healthy controls (59.7 ± 13.3 years, 5 females) and 13 younger healthy subjects (33.5 ± 11.1 years, 4 females). All subjects underwent a CMR exam, including 4D flow and three-dimensional anatomical images of the aorta. This latter dataset was used for aortic morphology measurements, including AscAo maximal diameter (iDMAX) and volume, indexed to body surface area. 4D flow MRI data were used to estimate 1) cross-sectional local AscAo spatial (∆PS) and temporal (∆PT) pressure changes as well as the distance (∆DPS) and time duration (∆TPT) between local pressure peaks, 2) AscAo maximal wall shear stress (WSSMAX) at peak systole, and 3) AscAo flow vorticity amplitude (VMAX), duration (VFWHM), and eccentricity (VECC). RESULTS: Consistency of flow and pressure indices was demonstrated through their significant associations with AscAo iDMAX (WSSMAX:r = -0.49, p < 0.001; VECC:r = -0.29, p = 0.045; VFWHM:r = 0.48, p < 0.001; ∆DPS:r = 0.37, p = 0.010; ∆TPT:r = -0.52, p < 0.001) and indexed volume (WSSMAX:r = -0.63, VECC:r = -0.51, VFWHM:r = 0.53, ∆DPS:r = 0.54, ∆TPT:r = -0.63, p < 0.001 for all). Intra-AscAo cross-sectional pressure difference, ∆PS, was significantly and positively associated with both VMAX (r = 0.55, p = 0.002) and WSSMAX (r = 0.59, p < 0.001) in the 30 healthy subjects (48.3 ± 18.0 years). Associations remained significant after adjustment for iDMAX, age, and systolic blood pressure. Superimposition of ATAA patients to normal aging trends between ∆PS and WSSMAX as well as VMAX allowed identifying patients with substantially high pressure differences concomitant with AscAo dilation. CONCLUSION: Local variations in pressures within ascending aortic cross-sections derived from 4D flow MRI were associated with flow changes, as quantified by vorticity, and with stress exerted by blood on the aortic wall, as quantified by wall shear stress. Such flow-wall and pressure interactions might help for the identification of at-risk patients.

Aortic Stiffness Measured from Either 2D/4D Flow and Cine MRI or Applanation Tonometry in Coronary Artery Disease: A Case-Control Study.

BACKGROUND AND OBJECTIVE: Aortic stiffness can be evaluated by aortic distensibility or pulse wave velocity (PWV) using applanation tonometry, 2D phase contrast (PC) MRI and the emerging 4D flow MRI. However, such MRI tools may reach their technical limitations in populations with cardiovascular disease. Accordingly, this work focuses on the diagnostic value of aortic stiffness evaluated either by applanation tonometry or MRI in high-risk coronary artery disease (CAD) patients. METHODS: 35 patients with a multivessel CAD and a myocardial infarction treated 1 year before were prospectively recruited and compared with 18 controls with equivalent age and sex distribution. Ascending aorta distensibility and aortic arch 2D PWV were estimated along with 4D PWV. Furthermore, applanation tonometry carotid-to-femoral PWV (cf PWV) was recorded immediately after MRI. RESULTS: While no significant changes were found for aortic distensibility; cf PWV, 2D PWV and 4D PWV were significantly higher in CAD patients than controls (12.7 ± 2.9 vs. 9.6 ± 1.1; 11.0 ± 3.4 vs. 8.0 ± 2.05 and 17.3 ± 4.0 vs. 8.7 ± 2.5 m·s-1 respectively, p < 0.001). The receiver operating characteristic (ROC) analysis performed to assess the ability of stiffness indices to separate CAD subjects from controls revealed the highest area under the curve (AUC) for 4D PWV (0.97) with an optimal threshold of 12.9 m·s-1 (sensitivity of 88.6% and specificity of 94.4%). CONCLUSIONS: PWV estimated from 4D flow MRI showed the best diagnostic performances in identifying severe stable CAD patients from age and sex-matched controls, as compared to 2D flow MRI PWV, cf PWV and aortic distensibility.

Value of aortic volumes assessed by automated segmentation of 3D MRI data in patients with thoracic aortic dilatation: A case-control study.

PURPOSE: The purpose of this study was to investigate the benefit of aortic volumes compared to diameters or cross-sectional areas on three-dimensional (3D) magnetic resonance imaging (MRI) in discriminating between patients with dilated aorta and matched controls. MATERIALS AND METHODS: Sixty-two patients (47 men and 15 women; median age, 66 years; age range: 33-86 years) with tricuspid aortic valve and ascending thoracic aorta aneurysm (TAV-ATAA) and 43 patients (35 men and 8 women; median age, 51 years; age range: 17-76 years) with bicuspid aortic valve and dilated ascending aorta (BAV) were studied. One group of 54 controls matched for age and sex to patients with TAV-ATAA (39 men and 15 women; median age, 68 years; age range: 33-81 years) and one group of 42 controls matched for age and sex to patients with BAV (34 men and 8 women; median age, 50 years; age range: 17-77 years) were identified. All participants underwent 3D MRI, used for 3D-segmentation for measuring aortic length, maximal diameter, maximal cross-sectional area (CSA) and volume for the ascending aorta. RESULTS: An increase in ascending aorta volume (TAV-ATAA: +107%; BAV: +171% vs. controls; P < 0.001) was found, which was three times greater than the increase in diameter (TAV-ATAA: +29%; BAV: +40% vs. controls; P < 0.001). In differentiating patients with TAV-ATAA from their controls, the indexed ascending aorta volume showed better performances (AUC, 0.935 [95% confidence interval (CI): 0.882-0.989]; accuracy, 88.7% [95% CI: 82.9-94.5]) than indexed ascending aorta length (P < 0.001), indexed ascending aorta maximal diameter (P = 0.003) and indexed ascending aorta maximal CSA (P = 0.03). In differentiating patients with BAV from matched controls, indexed ascending aorta volume showed significantly better performances performance (AUC, 0.908 [95% CI: 0.829-0.987]; accuracy, 88.0% [95% CI: 80.9-95.0]) than indexed ascending aorta length (P = 0.02) and not different from indexed ascending aorta maximal diameter (P = 0.07) or from indexed ascending aorta maximal CSA (P = 0.27) CONCLUSION: Aortic volume measured by 3D-MRI integrates both elongation and luminal dilatation, resulting in greater classification performance than maximal diameter and length in differentiating patients with dilated ascending aorta or aneurysm from controls.

Deep Learning-based Automated Aortic Area and Distensibility Assessment: the Multi-Ethnic Study of Atherosclerosis (MESA).

This study details application of deep learning for automatic segmentation of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging for automatic aortic analysis on the large MESA cohort with assessment on an external cohort of thoracic aortic aneurysm (TAA) patients. This study includes images and corresponding analysis of the ascending and descending aorta at the pulmonary artery bifurcation from the MESA study. Train, validation, and internal test sets consisted of 1123 studies (24,282 images), 374 studies (8067 images), and 375 studies (8069 images), respectively. The external test set of TAAs consisted of 37 studies (3224 images). CNN performance was evaluated utilizing a dice coefficient and concordance correlation coefficients (CCC) of geometric parameters. Dice coefficients were as high as 97.55% (CI: 97.47-97.62%) and 93.56% (CI: 84.63-96.68%) on the internal and external test of TAAs, respectively. CCC for maximum and minimum and ascending aortic area were 0.969 and 0.950, respectively, on the internal test set and 0.997 and 0.995, respectively, for the external test. The absolute differences between manual and deep learning segmentations for ascending and descending aortic distensibility were 0.0194 × 10-4 ± 9.67 × 10-4 and 0.002 ± 0.001 mmHg-1, respectively, on the internal test set and 0.44 × 10-4 ± 20.4 × 10-4 and 0.002 ± 0.001 mmHg-1, respectively, on the external test set. We successfully developed a U-Net-based aortic segmentation and analysis algorithm in both MESA and in external cases of TAA.

Comparison of different methods for the estimation of aortic pulse wave velocity from 4D flow cardiovascular magnetic resonance.

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).

Comparison of MR T1 and T2 mapping parameters to characterize myocardial and skeletal muscle involvement in systemic idiopathic inflammatory myopathy (IIM).

OBJECTIVES: To compare the performance of magnetic resonance (MR) relaxometry parameters to discriminate myocardial and skeletal muscle inflammation in idiopathic inflammatory myopathy (IIM) patients from healthy controls. MATERIALS AND METHODS: For this retrospective case-control study, 20 consecutive IIM patients (54 ± 18 years, 11 females) with cardiac involvement (troponin level > 50 ng/l) and 20 healthy controls (47 ± 12 years, 9 females) were included. All patients without cardiac MR imaging < 2 weeks prior to the laboratory testings were excluded. T1/T2 relaxation times, as well as T1-derived extracellular volume (ECV), relative tissue T1 shortening ΔT1 = (native T1tissue-post contrast T1tissue)/native T1tissue), and enhancement fraction EHF = (native T1tissue-post contrast T1tissue)/(native T1blood-post contrast T1blood), were compared using Mann-Whitney U test and ROC analysis. RESULTS: All measured MR relaxometry parameters significantly discriminated IIM patients and healthy controls, except T2 in skeletal muscles and ECV in the myocardium. In skeletal muscles, post contrast T1 and T1-derived parameters showed the best performance to discriminate IIM patients from healthy controls (AUC = 0.98 for post contrast T1 and AUC 0.94-0.97 for T1-derived parameters). Inversely, in the myocardium, native T1 and T2 showed better diagnostic performance (AUC = 0.89) than post contrast T1 (AUC = 0.76), ECV (AUC = 0.58), ΔT1 (AUC = 0.80) and EHF (0.82). CONCLUSIONS: MR relaxometry parameters applied to the myocardium and skeletal muscles might be useful to separate IIM patients from healthy controls. However, different tissue composition and vascularization should be taken into account for their interpretation. ΔT1 and EHF may be simple alternatives to ECV in highly vascularized tissues such as the myocardium. KEY POINTS: • MR relaxometry parameters applied to the myocardium and skeletal muscles are highly useful to separate IIM patients from healthy controls. • Different tissue composition and vascularization should be taken into account for T1 and T2 mapping parameter interpretation. • ΔT1 and EHF may be simple alternatives to ECV in highly vascularized tissues such as the myocardium.

Analysis of aortic pressure fields from 4D flow MRI in healthy volunteers: Associations with age and left ventricular remodeling.

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.

3D aortic morphology and stiffness in MRI using semi-automated cylindrical active surface provides optimized description of the vascular effects of aging and hypertension.

BACKGROUND: Clinically, aortic geometry assessment is mainly based on the measurement of maximal diameters at different anatomic locations, which are subsequently used to indicate prophylactic aortic surgery. However, 3D evaluation of aortic morphology could provide volumetric quantification, which integrates both aortic dilatation and elongation and might thus be more sensitive to early geometric changes than diameters. Precise aortic morphology is also required for the calculation of pulse wave velocity (PWVMRI), an established marker of aortic stiffness. Accordingly, we proposed a 3D semi-automated analysis of thoracic aorta MRI data optimizing morphological and subsequent stiffness assessment. METHODS: We studied 74 individuals (40 males, 50 ± 12years): 21 healthy volunteers and 53 patients with hypertension in whom aortic 3D MRI angiography and 2D + t phase-contrast and cine imaging were performed. A semi-automated method was proposed for volumetric aortic segmentation and was evaluated by studying resulting measurements (length, diameters, volumes and PWVMRI) in terms of: 1) reproducibility, 2) correlations with well-established 2D aortic length and diameters, 3) associations with age, carotid-femoral PWV (cf-PWV) and presence of hypertension. RESULTS: The measurements obtained with the proposed method were reproducible (coefficients of variation ≤ 5.1%) and were highly correlated with 2D measurements (arch length: r = 0.80, Bland-Altman mean bias [limits]: 2.7 mm [-25; 30]; PWVMRI: r = 0.95, 0.22 m/s [-1.9; 2.4]). Higher or similar correlations with age were found for the proposed 3D method compared to the 2D approach (arch length: r = 0.47 (2D), r = 0.60 (3D); PWVMRI: r = 0.63 (2D), r = 0.64 (3D)). Moreover, a significant association was found between PWVMRI and cf-PWV (r = 0.49, p < 0.001). All aortic measurements increased with hypertension (p < 0.05) and with age: arch length (+9mm/decade); diameters: ascending (+1.2mm/decade) and descending aorta (+1.0mm/decade); volumes: ascending (+2.6mL/decade) and descending aorta (+4.0mL/decade); PWVMRI (+1.7  m s-1/decade). CONCLUSIONS: A semi-automated method based on cylindrical active surfaces was proposed for the 3D segmentation of the aorta using a single MRI dataset, providing aortic diameters at anatomical landmarks, aortic volumes and the aortic centerline length used for PWV estimation. Such measurements were reproducible and comparable to expert measurements, which required time-consuming centerline delineation. Furthermore, expected relationships with age and hypertension were found indicating the consistency of our measurements.

Non-invasive differentiation of idiopathic inflammatory myopathy with cardiac involvement from acute viral myocarditis using cardiovascular magnetic resonance imaging T1 and T2 mapping.

BACKGROUND: Idiopathic inflammatory myopathy (IIM) is a group of autoimmune diseases with systemic myositis which may involve the myocardium. Cardiac involvement in IIM, although often subclinical, may mimic clinical manifestations of acute viral myocarditis (AVM). Our aim was to investigate the usefulness of the combined analysis of cardiovascular magnetic resonance (CMR) T1 and T2 mapping parameters measured both in the myocardium and in the thoracic skeletal muscles to differentiate AVM from IIM cardiac involvement. METHODS: Sixty subjects were included in this retrospective study (36 male, age 45 ± 16 years): twenty patients with AVM, twenty patients with IIM and cardiac involvement and twenty healthy controls. Study participants underwent CMR imaging with modified Look-Locker inversion-recovery (MOLLI) T1 mapping and 3-point balanced steady-state-free precession T2 mapping. Relaxation times were quantified after endocardial and epicardial delineation on basal and medial short-axis slices, as well as in different thoracic skeletal muscle groups present in the CMR field-of-view. ROC-Analysis was performed to assess the ability of mapping indices to discriminate the study groups. RESULTS: Mapping parameters in the thoracic skeletal muscles were able to discriminate between AVM and IIM patients. Best skeletal muscle parameters to identify IIM from AVM patients were reduced post-contrast T1 and increased extracellular volume (ECV), resulting in an area under the ROC curve (AUC) of 0.95 for post-contrast T1 and 0.96 for ECV. Conversely, myocardial mapping parameters did not discriminate IIM from AVM patients but increased native T1 (AUC 0.89 for AVM; 0.84 for IIM) and increased T2 (AUC 0.82 for AVM; 0.88 for IIM) could differentiate both patient groups from healthy controls. CONCLUSION: CMR myocardial mapping detects cardiac inflammation in AVM and IIM compared to normal myocardium in healthy controls but does not differentiate IIM from AVM. However, thoracic skeletal muscle mapping was able to accurately discern IIM from AVM.

Scan-rescan reproducibility of ventricular and atrial MRI feature tracking strain.

BACKGROUND: A feature tracking (FT) was designed to simultaneously extract myocardial strains in main cardiac chambers from cine MRI images. Its inter-observer and scan-rescan reproducibility was assessed and sample sizes required to detect predefined longitudinal changes in strain values were provided. METHOD: FT was applied on left (LV) and right (RV) ventricles as well as left atrium (LA) of 21 individuals (66 ± 10 years) who underwent 2 MRIs 2 weeks apart. Global peaks for radial, circumferential, longitudinal strains, radial motion fraction (Mr), fractional area change (FAC) and tricuspid annular plane excursion (TAPSE) were estimated. Inter-operator and inter-exam reproducibility were evaluated using coefficients of variations (CV) and intra-class correlation coefficients (ICC). RESULTS: Reproducibility of all measurements were good to excellent for inter-operator (LV:CV<6.5%, ICC>0.91; RV:CV<12%, ICC>0.86; LA:CV<14%, ICC>0.85) and inter-study (LV:CV<15%, ICC>0.65; RV:CV<20%, ICC>0.71; LA:CV<20.5%, ICC>0.83) evaluations. Reasonable sample sizes are required to detect a longitudinal difference of 10-15% in strain values (LV:5 to 33 individuals, RV:14 to 62 individuals, LA:4 to 65 individuals). CONCLUSIONS: FT-based functional evaluation of main heart chamber deformation from cine MRI is repeatable and thus suitable for follow-up. Strain measurements may help for the joint clinical evaluation of LV, RV or LA implication in various cardiomyopathies.

Quantification of tumor perfusion using dynamic contrast-enhanced ultrasound: impact of mathematical modeling.

Dynamic contrast-enhanced ultrasound has been proposed to monitor tumor therapy, as a complement to volume measurements. To assess the variability of perfusion parameters in ideal conditions, four consecutive test-retest studies were acquired in a mouse tumor model, using controlled injections. The impact of mathematical modeling on parameter variability was then investigated. Coefficients of variation (CV) of tissue blood volume (BV) and tissue blood flow (BF) based-parameters were estimated inside 32 sub-regions of the tumors, comparing the log-normal (LN) model with a one-compartment model fed by an arterial input function (AIF) and improved by the introduction of a time delay parameter. Relative perfusion parameters were also estimated by normalization of the LN parameters and normalization of the one-compartment parameters estimated with the AIF, using a reference tissue (RT) region. A direct estimation (rRTd) of relative parameters, based on the one-compartment model without using the AIF, was also obtained by using the kinetics inside the RT region. Results of test-retest studies show that absolute regional parameters have high CV, whatever the approach, with median values of about 30% for BV, and 40% for BF. The positive impact of normalization was established, showing a coherent estimation of relative parameters, with reduced CV (about 20% for BV and 30% for BF using the rRTd approach). These values were significantly lower (p < 0.05) than the CV of absolute parameters. The rRTd approach provided the smallest CV and should be preferred for estimating relative perfusion parameters.

Pulmonary Artery Stiffness Is Independently Associated with Right Ventricular Mass and Function: A Cardiac MR Imaging Study.

Purpose To determine the relationship between pulmonary artery (PA) stiffness and both right ventricular (RV) mass and function with cardiac magnetic resonance (MR) imaging. Materials and Methods The study was approved by the local research ethics committee, and all participants gave written informed consent. Cardiac MR imaging was performed at 1.5 T in 156 healthy volunteers (63% women; age range, 19-61 years; mean age, 36.1 years). High-temporal-resolution phase-contrast imaging was performed in the main and right PAs. Pulmonary pulse wave velocity (PWV) was determined by the interval between arterial systolic upslopes. RV function was assessed with feature tracking to derive peak systolic strain and strain rate, as well as peak early-diastolic strain rate. RV volumes, ejection fraction (RVEF), and mass were measured from the cine images. The association of pulmonary PWV with RV function and mass was quantified with univariate linear regression. Interstudy repeatability was assessed with intraclass correlation. Results The repeatability coefficient for pulmonary PWV was 0.96. Increases in pulmonary PWV and RVEF were associated with increases in age (r = 0.32, P < .001 and r = 0.18, P = .025, respectively). After adjusting for age (P = .090), body surface area (P = .073), and sex (P = .005), pulmonary PWV demonstrated an independent positive association with RVEF (r = 0.34, P = .026). Significant associations were also seen with RV mass (r = 0.41, P = .004), RV radial strain (r = 0.38, P = .022), and strain rate (r = 0.35, P = .002), and independent negative associations were seen with radial (r = 0.27, P = .003), longitudinal (r = 0.40, P = .007), and circumferential (r = 0.31, P = .005) peak early-diastolic strain rate with the same covariates. Conclusion Pulmonary PWV is reliably assessed with cardiac MR imaging. In subjects with no known cardiovascular disease, increasing PA stiffness is associated with increasing age and is also moderately associated with both RV mass and function after controlling for age, body surface area, and sex. (©) RSNA, 2016 Online supplemental material is available for this article.

Improved Estimation of Cardiac Function Parameters Using a Combination of Independent Automated Segmentation Results in Cardiovascular Magnetic Resonance Imaging.

This work aimed at combining different segmentation approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by estimating six cardiac function parameters resulting from the left ventricle contour delineation using a public cardiac cine MRI database. Eight different segmentation methods, including three expert delineations and five automated methods, were considered, and sixteen combinations of the automated methods using STAPLE were investigated. The supervised and unsupervised evaluations demonstrated that in most cases, STAPLE results provided better estimates than individual automated segmentation methods. Overall, combining different automated segmentation methods improved the reliability of the segmentation result compared to that obtained using an individual method and could achieve the accuracy of an expert.

Estimation of aortic pulse wave transit time in cardiovascular magnetic resonance using complex wavelet cross-spectrum analysis.

BACKGROUND: Aortic pulse wave velocity (PWV), which substantially increases with arterial stiffness and aging, is a major predictor of cardiovascular mortality. It is commonly estimated using applanation tonometry at carotid and femoral arterial sites (cfPWV). More recently, several cardiovascular magnetic resonance (CMR) studies have focused on the measurement of aortic arch PWV (archPWV). Although the excellent anatomical coverage of CMR offers reliable segmental measurement of arterial length, accurate transit time (TT) determination remains a challenge. Recently, it has been demonstrated that Fourier-based methods were more robust to low temporal resolution than time-based approaches. METHODS: We developed a wavelet-based method, which enables temporal localization of signal frequencies, to estimate TT from ascending and descending aortic CMR flow curves. This method (archPWVWU) combines the robustness of Fourier-based methods to low temporal resolution with the possibility to restrict the analysis to the reflectionless systolic upslope. We compared this method with Fourier-based (archPWVF) and time domain upslope (archPWVTU) methods in relation to linear correlations with age, cfPWV and effects of decreasing temporal resolution by factors of 2, 3 and 4. We studied 71 healthy subjects (45 ± 15 years, 29 females) who underwent CMR velocity acquisitions and cfPWV measurements. RESULTS: Comparison with age resulted in the highest correlation for the wavelet-based method (archPWVWU:r = 0.84,p < 0.001; archPWVTU:r = 0.74,p < 0.001; archPWVF:r = 0.63,p < 0.001). Associations with cfPWV resulted in the highest correlations for upslope techniques whether based on wavelet (archPWVWU:r = 0.58,p < 0.001) or time (archPWVTU:r = 0.58,p < 0.001) approach. Furthermore, while decreasing temporal resolution by 4-fold induced only a minor decrease in correlation of both archPWVWU (r decreased from 0.84 to 0.80) and archPWVF (r decreased from 0.63 to 0.51) with age, it induced a major decrease for the archPWVTU age relationship (r decreased from 0.74 to 0.38). CONCLUSIONS: By CMR, measurement of aortic arch flow TT using systolic upslopes resulted in a better correlation with age and cfPWV, as compared to the Fourier-based approach applied on the entire cardiac cycle. Furthermore, methods based on harmonic decomposition were less affected by low temporal resolution. Since the proposed wavelet approach combines these two advantages, it might help to overcome current technical limitations related to CMR temporal resolution and evaluation of patients with highly stiff arteries.

Kinetic index combining native and postcontrast myocardial T1 in hypertrophic cardiomyopathy.

BACKGROUND: To evaluate ability of pre- and postcontrast apparent T1* indices, as well as their combination to characterize myocardial structural changes in hypertrophic cardiomyopathy (HCM). METHODS: Study protocol was approved by institutional review board and informed consent was obtained. T1 mapping was performed using MOLLI sequence (1.5T magnet) on: (i) tubes with known T1 and varied heart-rates (HR), (ii) 17 HCM (55 ± 15 years) and 18 controls (49 ± 16 years), before contrast and every 5 min over 20 min postcontrast. Global and segmental native T1 (T1*Native ), extracellular volume (ECV) and percentage of decrease in myocardial T1* (T1*decay = 100·[1-T1*Post-contrast /T1*Native ]) were estimated. Correlation coefficients of associations between T1 and LV indices, such as left ventricular wall thickness (WT) and mass index (LVMi) were provided. Receiver operator curve analysis was performed on per-patient basis to assess ability of T1* indices to identify HCM. RESULTS: While up to a T1* of 1000 ms the effect of HR was minor, it was more pronounced above 1000 ms. T1*Native (754 ± 76 ms versus 1014 ± 130 ms, P < 0.001), ECV20min (23 ± 5% versus 27 ± 4%, P = 0.005), and T1*decay5, 10, 15 or 20min (38 ± 8% versus 54 ± 6%, P < 0.001) showed significant differences between controls and HCM. Correlation coefficients for associations with WT and LVMi were higher for T1*Native and T1decay, independent of acquisition time (with WT/LVMi: r = 0.58/0.44 (P < 0.05) for T1*Native ; r = 0.23 (P < 0.05)/0.23 for ECV20min ; r > 0.51/ > 0.45(P < 0.05) for T1*decay5, 20min ). T1*Native (97.1%) and T1*decay (91.2%) characterized HCM with higher accuracy (P < 0.02) than ECV (69%). CONCLUSION: T1*Native and T1*decay were able to characterize HCM more accurately than ECV, even in the absence of myocardial hypertrophy and late-gadolinium enhancement.

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 ±â€Š16 years) individuals and 16 hypertensive (61 ±â€Š9 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 ±â€Š8 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.

Age-specific changes in left ventricular diastolic function: a velocity-encoded magnetic resonance imaging study.

OBJECTIVES: Our objectives were to assess the ability of phasecontrast MRI (PC-MRI) to detect sub-clinical age-related variations of left ventricular (LV) diastolic parameters and thus to provide age-related reference ranges currently available for echocardiography but not for MRI-PC, and to identify independent associates of such variations. METHODS: We studied 100 healthy volunteers (age = 42 ± 15years, 50 females) who had MRI with simultaneous blood pressure measurements. LV mass and volumes were assessed. Semiautomated analysis of PC-MRI data provided: 1) early transmitral (Ef) and atrial (Af) peak filling flow-rates (ml/s) and filling volume (FV), 2) deceleration time (DT), isovolumic relaxation time (IVRT), and 3) early myocardial longitudinal (E') peak velocity. RESULTS: MRI-PC diastolic parameters were reproducible as reflected by low coefficients of variations (ranged between 0.31 to 6.26 %). Peak myocardial velocity E' (r = -0.63, p < 0.0001) and flow-rate parameters were strongly and independently associated to age (Ef/Af:r = -0.63, DT:r = 0.46, IVRT:r = 0.44, Ef/FV:r = -0.55, Af/FV:r = 0.56, p < 0.0001). Furthermore, LV relaxation parameters (E', DT, IVRT), were independently associated to LV remodelling (LV mass/end-diastolic volume) and myocardial wall thickness (p < 0.01). CONCLUSIONS: PC-MRI age-related reference ranges of diastolic parameters are provided. Such parameters might be useful for a fast, reproducible and reliable characterization of diastolic function in patients referred for clinical MRI exam KEY POINTS: • MRI age-related reference values of left ventricular diastolic parameters are provided. • MRI diastolic parameters can characterise sub-clinical age-related variations in healthy individuals. • Diastolic function would complement cardiac MRI exam with currently neglected data. • Diastolic function would enhance MRI diagnostic value in cardiomyopathy and heartfailure.

MR and applanation tonometry derived aortic impedance: association with aging and left ventricular remodeling.

PURPOSE: We sought to noninvasively estimate aortic impedance indices from MR and tonometric data. MATERIALS AND METHODS: MR aortic velocity-encoded and carotid applanation tonometry pressure data of 70 healthy subjects (19-79 years) were used to calculate the following indices from impedance spectrum: (i) characteristic impedance (Zc) reflecting pulsatile component of left ventricular (LV) afterload, (ii) frequency of the minimal impedance magnitude related to arterial compliance (FMIN ), (iii) total peripheral resistance (TPR) related to steady LV load, (iv) impedance oscillatory index (ZINDEX ) related to proximal reflections, and (v) reflection magnitude (RM). Associations with age and LV remodeling (LV mass/end-diastolic volume) were investigated using multivariate analysis. RESULTS: All indices except Zc were associated with age independent of subjects characteristics and systolic blood pressures. They were all significantly associated with the well-established carotid-femoral pulse wave velocity (r ≥ 0.29; P < 0.01). However, such associations were not independent of age. Pulsatile index Zc was independently associated with carotid pulse pressure (r = 0.53, P < 0.001). Moreover, conversely to conventional stiffness indices, Zc and TPR were independently associated with LV remodeling (r = 0.30, r = 0.43, respectively, P < 0.01). CONCLUSION: We estimated aortic impedance from velocity-encoded MR and tonometry data resulting in reliable impedance and reflection indices as confirmed by their significant and independent associations with age and LV remodeling.

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.

Pixel-wise absolute pressures in the aortic arch from 3D MRI velocity data and carotid artery applanation tonometry.

A pixel-wise method for absolute and local aortic pressures estimation using 3D velocities in MRI and carotid pressure curves to set-up reference pressure values is presented. This method is based on the Navier-Stokes equation and a fast iterative algorithm. Its reliability was demonstrated: 1) in a synthetic phantom by comparison against simplified Bernoulli equation applied at peak velocities, and 2) in a healthy subject and a patient with aortic coarctation, in which absolute pressure distribution within the aortic arch was consistent with established physiopathological knowledge. Such local absolute aortic pressures may be useful in the understanding of hemodynamic changes secondary to cardiovascular alterations. Also, their addition to the already available indices of risk of aortic complications such as dilatation and dissection definition may prove of major clinical usefulness.