Background Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) enables the estimation of myocardial infarct (MI) extent. Nevertheless, manual quantification is time consuming and subjective. We sought to assess MI volume with different quantitative methods in both acute (AMI) and chronic MI (CMI). Methods CMR was performed 50±21 h after MI in 52 patients and was repeated 100±21 days later in a subgroup of 34 patients. Then, necrosis volumes were quantified using: 1) manual delineation, 2) automated fuzzy c-means method, and 3) +2 to 6SD thresholding approaches. Results were compared against peak values of serum Troponin I (TnI), creatine kinase (CK) and left ventricular (LV) functional parameters: LV ejection fraction (LVEF), indexed end-diastolic (EDVi), end-systolic volumes (ESVi) and the number of hypokinetic segments (NbHk). Results For CMI, quantitative evaluation of infarct size using manual, +2SD, +3SD and fuzzy c-means provided equivalent results in terms of correlation coefficients for comparisons of MI volumes against LV function parameters (LVEF: r>0.79, p<0.0001; ESVi: r>0.82, p<0.0001, EDVi: r>0.67, p<0.0001, NbHk: r>0.54, p<0.0009). For AMI, +2SD and fuzzy c-means approaches provided higher correlations for comparisons of AMI volumes against biochemical markers (CK: r>0.79, p<0.0001,TnI: r>0.77, p<0.0001) and chronic LV function parameters (LVEF: r>0.82, p<0.0001, NbHk: r>0.59, p<0.0002). Conclusions The fuzzy c-means and 2SD methods provided highest correlations with biochemical MI quantification as well as LV function parameters. The fuzzy c-means approach which does not require an arbitrary identification of the remote myocardium is fast and reproducible. It may be clinically useful in the evaluation of patients with MI.

Early detection of diastolic dysfunction is crucial for patients with incipient heart failure. Our goal was to develop a robust process to automatically estimate diastolic parameters from phase-contrast cardiovascular magnetic resonance (PC-CMR) data and to test their ability to characterize left ventricular (LV) dysfunction. We studied 53 subjects (35 controls and 18 patients with a severe aortic valve stenosis) who had PC-CMR and Doppler echocardiography on the same day. PC-CMR data were analyzed using custom software to extract diastolic parameters. Our technique was reproducible, as reflected by a small variability (<;4.25 ± 5.89 %). The PC-CMR diastolic parameters significantly (p<;0.0002) varied in patients as opposed to controls. Moreover, PC-CMR diastolic parameters were consistent with echocardiographic values (r>;0.71) and were able to accurately separate patients from controls (accuracy>;0.85). Of note, a superiority in terms of correlation with echocardiography and accuracy to detect LV abnormalities were found for flow-rate parameters. A fast and reproducible technique was proposed and was successfully used to extract consistent PC-CMR diastolic parameters. This technique provides a valuable addition to established CMR tools in evaluation of patients with diastolic dysfunction.

We sought to assess myocardial infarct (MI) volume with different quantitative methods in both acute (AMI) and chronic MI (CMI) from CMR late Gadolinium Enhancement images. CMR exam was performed 50±21 hours after MI in 52 patients and was repeated 100±21 days later in a subgroup of 34 patients. Necrosis volumes were quantified using: 1) manual delineation, 2) automated fuzzy c-means method, and 3) +2 to 6SD thresholding approaches. Results were compared against peak values of serum Troponin I (TnI), creatine kinase (CK) and LV functional parameters. For CMI, quantitative evaluation of infarct size using manual, +2SD, +3SD and fuzzy c-means provided equivalent results for comparisons of MI volumes against LV function parameters (r>;0.79, p<;0.0001). For AMI, +2SD and fuzzy c-means approaches provided higher correlations for comparisons of AMI volumes against biochemical markers (r>;0.77, p<;0.0001) and chronic LV function parameters (r>;0.59, p<;0.0002). The fuzzy c-means and +2SD methods provided highest correlations with biochemical MI quantification as well as LV function parameters. The fuzzy c-means approach which does not require an arbitrary identification of the remote myocardium is fast and reproducible. It may be clinically useful in the evaluation of patients with MI.

A 3D estimation of the length of the aortic arch using sagittal and axial acquisitions is proposed and compared with the conventional 2D method using a single view of the aorta.

Transposition of the great arteries (TGA) is the consequences of abnormal aorticopulmonary septation. Animal embryonic data indicate that septation and elastogenesis are related events. It was showed that carotid artery is markedly and constitutionally stiffer in patients with TGA. to assess aortic dimensions and aortic elasticity in patients with TGA using magnetic resonance imaging (MRI). MRI was performed in 29 patients with simple TGA operated by an atrial switch procedure (22 male; mean age 29 ± 4 years) and 29 age and gender-matched healthy subjects. TGA patients showed aortic root dilatation (7.7 ± 2.1 vs 6.2 ± 1.2 cm∑, p = 0, 0018, in systole, and 6.8 ± 2.1 vs 5.0 ± 1.2 cm∑, p = 0.0003, in diastole, at tubular level), reduced aortic root distension (13.5 ± 5.9 vs 24.3 ± 11.7, p<0.0001) and reduced aortic root distensibility (3.5 ± 1.6 vs 5.3 ± 2.4 mmHg −1 .10 −3 , p = 0.0009). Biomechanical properties of the descending aorta and pulse wave velocity were similar in TGA patients and in healthy subjects. Body mass index, systolic blood pressure, diastolic blood pressure and pulse pressure were similar between patients and healthy subjects, and had no influence on ascending aorta stiffness. No significant correlation was found between index of aortic stiffness and right ventricle (RV) function (end-diastolic and end systolic volumes, RVEF, RV mass, presence or absence of myocardial fibrosis). It did not change after indexation to body surface area of RV function values. Aortic stiffness in TGA is markedly increased and localized to the ascending aorta. This property could contribute to the dilatation of the ascending aorta part of the new aorta in arterial switch procedure.

-12.88 -6.9 SV were successfully estimated using cardiac and aortic studies. In the latter case, no failure of the automated procedure was reported in the studied population. Using these values and heart rate (mean value 68 bpm, range 34-102) cardiac output (CO) was computed. Finally cardiac index (Figure 2) was derived by introducing the body surface area (mean value: 1.83 m 2 , range 1.37- 2.23). Linear regression between the cardiac and aortic series of values showed a high correlation: r=0.80 for VE, r=0.78 for CO and r=0.76 for CI. However, the VEa, COa, and CIa values derived from PC aortic sequences were clearly underestimated when compared to the same values derived from cardiac images. For the three indices, the underestimation ratio was estimated to be 15%.

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. © 2010 Wiley‐Liss, Inc.

Contrast-enhanced ultrasound (CEUS), with the recent development of both contrast-specific imaging modalities and microbubble-based contrast agents, allows noninvasive quantification of microcirculation in vivo. Nevertheless, functional parameters obtained by modeling contrast uptake kinetics could be impaired by respiratory motion. Accordingly, we developed an automatic respiratory gating method and tested it on 35 CEUS hepatic datasets with focal lesions. Each dataset included fundamental mode and cadence contrast pulse sequencing (CPS) mode sequences acquired simultaneously. The developed method consisted in (1) the estimation of the respiratory kinetics as a linear combination of the first components provided by a principal components analysis constrained by a prior knowledge on the respiratory rate in the frequency domain, (2) the automated generation of two respiratory-gated subsequences from the CPS mode sequence by detecting end-of-inspiration and end-of-expiration phases from the respiratory kinetics. The fundamental mode enabled a more reliable estimation of the respiratory kinetics than the CPS mode. The k-means algorithm was applied on both the original CPS mode sequences and the respiratory-gated subsequences resulting in clustering maps and associated mean kinetics. Our respiratory gating process allowed better superimposition of manually drawn lesion contours on k-means clustering maps as well as substantial improvement of the quality of contrast uptake kinetics. While the quality of maps and kinetics was satisfactory in only 11/35 datasets before gating, it was satisfactory in 34/35 datasets after gating. Moreover, noise amplitude estimated within the delineated lesions was reduced from 62 ± 21 to 40 ± 10 (p < 0.01) after gating. These findings were supported by the low residual horizontal (0.44 ± 0.29 mm) and vertical (0.15 ± 0.16 mm) shifts found during manual motion correction of each respiratory-gated subsequence. The developed technique could be used as a basis for accurate quantification of perfusion parameters for the evaluation and follow-up of patients under antiangiogenic therapies.

Objective. - To investigate the accuracy in the estimation of the aortic lumen area and distensibility obtained from Steady-State Free-Precession (SSFP) and Phase Contrast (PC) MR sequences.Subjects and methods. - Systolic and diastolic aortic lumen of the ascending and descending aorta of 50 subjects. collected with both acquisition sequences, were extracted using a 2D + t automated segmentation method.Results. - While the statistical study indicated very similar lumen areas for SSFP and PC data (slope = 1, r = 0.99), the corresponding distensibility values were less correlated (r = 0.54). Comparison between distensibility values in the ascending and descending aorta and study of these values with aging indicated a greater coherence with expected physiological behavior of the aorta when using SSFP images.Discussion. - Flow artifacts were more severe in PC images and could explain the better results obtained when using SSFP sequences.Conclusion. - A more accurate local assessment of the aortic stiffness is obtained from SSFP image sequences than from PC image sequences. (C) 2011 Elsevier Masson SAS. All rights reserved.

The efficiency of a new transit time (Delta t) estimator (MSeg) for Pulse Wave Velocity (PWV) estimation is compared with three previously described methods (MUpslope, MFoot, MPoint), in terms of correlation with aging and reproducibility. SSFP and PC acquisitions from 40 subjects (42+/-15 year), recorded at the level of the aortic arch were studied. Delta t was defined as the time shift between the flow curves in the ascending (CA) and descending (CD) aorta and calculated with: 1) MSeg, by minimizing the area delimited by two sigmoid curves fitted to the systolic up-slope of CA and CD, 2) MUpslope, by minimizing the area between the systolic up-slope of CA and the CD curve, 3) MFoot using CA and CD feet, 4) MPoin, t using the half maximum of CA and CD. The MSeg estimator resulted in a higher reproducibility (6%), better correlation of pulse wave velocity with aging (r=0.85), and less overlap between the < 40 and >= 40 years groups.

PURPOSE:To investigate the efficiency of a new method (TT-Upslope) for transit time (Δt) estimation from cardiovascular MR (CMR) velocity curves. MATERIALS AND METHODS:Fifty healthy volunteers (40 ± 15 years) underwent applanation tonometry to estimate carotid-femoral pulse wave velocity (cf-PWV) and carotid pressure measurements, and CMR to estimate aortic arch-PWV and ascending aorta distensibility (AAD). The Δt was calculated with TT-Upslope by minimizing the area delimited by two sigmoid curves fitted to the systolic upslope of the ascending (AAC) and descending (DAC) aorta velocity curves, and compared with previously described methods: TT-Point using the half maximum of AAC and DAC, TT-Foot using AAC and DAC feet, and TT-Wave by minimizing the area between AAC and DAC curves using cross correlation. RESULTS:All the Δt methods provided a high reproducibility of arch-PWV. However, TT-Upslope and TT-Wave resulted in better correlations with aging (r = 0.83/r = 0.83 versus r = 0.47/r = 0.72), cf-PWV (r = 0.69/r = 0.70 versus r = 0.34/r = 0.59), and AAD (r = 0.81/r = 0.71 versus r = 0.61/r = 0.60). Furthermore, TT-Upslope resulted in stronger relationship between arch-PWV and AAD according to a theoretical model and provided better characterization of older subjects compared with TT-Wave. CONCLUSION:Arch-PWV estimated with CMR using the TT-Upslope method was found to be reproducible and accurate, providing strong correlations with age and aortic stiffness indices.

Background: 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.Results: Forty-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%).Conclusions: The 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.

Assessment of diastolic function with phase-contrast (PC) Magnetic Resonance Imaging (MRI) is not used in clinical routine because of the lack of automated analyses. Thus, our aim was to develop a process to automatically analyze PC data. We studied PC data of 25 controls with a custom software, designed for automated segmentation of PC images and analysis of velocity and flow rate curves to derive diastolic parameters. Segmentation was successful on all subjects. Also, our conventional parameters were consistent with those previously presented in the literature and our new parameters highly correlated with those known to have a high prognosis value. Our process may provide a valuable addition to the established cardiac MRI tools.

The accuracy of the estimation of the aortic lumen area was investigated using an automated segmentation method (ART-FUN). The study included both Steady State Free Precession (SSFP) and Phase Contrast (PC) MR acquisition sequences. The precision of the segmented lumen area was tested against expert manual contouring for 860 aorta sections from three different MR scanners. Comparison of lumen areas and distensibility values obtained from both SSFP and PC sequences was also performed in a group of 50 subjects. While linear regressions indicated very similar manual and automated segmentations for SSFP and PC data (slope=1, r=0.99), the corresponding distensibility values were less correlated (slope=0.76, r=0.54).

The evaluation of diastolic function from phase-contrast (PC) Magnetic Resonance (MR) data in clinical routine is not yet established. Thus, our goal was to develop a reproducible process to analyze PC data. These developments were used to estimate mitral flow and myocardial velocities from PC data of 40 controls. Besides, the reproducibility was assessed on a sub-group of 20 subjects. Transmitral flow and myocardial patterns were successfully delineated on each cardiac phase, resulting in conventional diastolic parameters, consistent with echocardiographic literature. Moreover, new proposed parameters correlated strongly (r >; 0.8) with those with high prognostic value. Finally, the flow segmentation was reproducible (99.5 ± 2.1% of overlap between two segmentations), and a low inter-operators variability (<;3.65%) in diastolic parameters measurements was obtained. Our technique provides a valuable addition to established cardiac MR tools.

INTRODUCTION Aortic stiffness indices such as aortic deformability (AD) and aortic pulse wave velocity (PWV) are considered as independent predictors of cardiovascular risk [1]. These two indices can be assessed directly and non-invasively from morphological and hemodynamic Magnetic Resonance (MR) data. The aim of this study was to evaluate the consistency of these indices by using a theoretical model derived from the Moens-Korteweg equation [2]. This model gives a relationship between AD, PWV, the aortic pulse pressure (APP) as well as the blood density (ρ): ) ( 2 PWV APP AD × = ρ . To achieve this aim: 1) the local AD of the ascending aorta, and the regional PWV derived from the propagation speed of the velocity waveform in the aortic arch were estimated from MR data, and 2) the global aortic deformability (ADe) was estimated from PWV and carotid pulse pressure (CPP) using the above equation. Finally, the relationship between AD and PWV and between ADe and AD were studied. METHODS Axial and coronal cine acquisitions and axial phase contrast (PC) acquisitions at the level of the pulmonary artery bifurcation were recorded on forty volunteers. The AD was calculated as the ratio between the variation in the areas of the ascending aorta lumen between systole and diastole and the diastolic area. These areas were automatically measured on cine MR acquisitions using a custom snake based automatic contouring. The PWV was calculated by using the 3D length of the aortic arch and the transit time of the systolic flow curves between the ascending and descending aorta. The 3D length of the aortic arch was calculated by interpolating the centers of the aortic lumen selected on the axial and coronal cine acquisitions using a 3D cardinal spline. The transit time was automatically calculated from PC sequences using an algorithm based on the least squares minimization applied on the upslope of the normalized flow curves in the ascending and descending aorta. ADe was finally estimated using the pulse pressure measured at the carotid artery by applanation tonometry according to the theoretical model derived from the Moens-Korteweg equation. Of note, the CPP was accepted as representative for APP. RESULTS According to the power regression, the relationship between PWV and AD was better characterized with a second order model (r2=0.61) and, thus, was consistent with the theoretical model between aortic deformability and pulse wave velocity. Moreover, the change of the estimated global index ADe according to the local index AD was linear (r=0.7, slope=0.82) (Figure 1). The corresponding Bland-Altman showed a good agreement between AD and ADe, resulting in a mean difference of 0.05 and a standard deviation of 0.1. CONCLUSION The AD and PWV were separately measured from MR acquisitions using a local and automated approach. These indices which provided a direct characterisation of the aortic stiffness were inversely related and were well described by the theoretical model derived from the Moens-Korteweg equation. In addition, the global index ADe estimated from the theoretical model gave a similar description of stiffness of the ascending aorta as the local index AD. REFERENCES [1]Laurent S, Boutouyrie P, Asmar R, et al. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension 2001;37:1236–41 [2] Marque V, Van Essen H, Struijker Boudier H, Atkinson J, Lartaud Idjouadiene I. Determination of Aortic Elastic Modulus by Pulse Wave Velocity and Wall Tracking in a Rat Model of Aortic Stiffness. J Vasc Res 2001;38:546–550

For the viability assessment in patients with infarcts, myocardial hyperenhancement on Delayed-Enhancement Cardiac MRI (DE) can be anatomically localized using Cine Cardiac MRI (Cine). An automatic rigid registration method, using the Normalized Mutual Information (NMI) maximization was proposed to refine the registration of the functional (DE) and anatomical (Cine) images. The full process including: 1) a coarse DE/Cine spatiotemporal alignment, 2) a refined DE/Cine registration, 3) a GVF-Snakes segmentation of myocardial contours on Cine images and 4) a myocardial infarction extent (MIE) quantification using a fuzzy c-means algorithm, was applied to ten patients with myocardial infarction. The qualitative and quantitative evaluation of the registration method showed high-quality alignment. The comparison between visual and automatic MIE quantification agreement (±1 grade) showed an improvement from 86% before to 91% after the refined registration step.

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.

BACKGROUND: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. RESULTS:We 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. CONCLUSIONS:A 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.