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.

Measurement of aortic arch pulse wave velocity in cardiovascular MR: comparison of transit time estimators and description of a new approach.

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.

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

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.

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

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.

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

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.

Increased central aortic stiffness and left ventricular mass in normotensive young subjects after successful coarctation repair.

BACKGROUND: Hypertension occurs in 20% to 40% of survivors of anatomically successful repair of aortic coarctation (CoA). The aim of the present study was to examine the role of central aortic function in this setting. METHODS: Forty normotensive asymptomatic subjects with successful CoA repair (age 12 +/- 8 years) and 20 age- and sex-matched control subjects underwent detailed magnetic resonance imaging investigation of the thoracic aorta and left ventricle. Aortic distensibility, compliance, and stiffness beta index were calculated in the central (precoarctation) and descending (postcoarctation) aorta. Aortic pulse wave velocity was measured and left ventricular mass was calculated. RESULTS: Compared to control subjects, CoA subjects had markedly decreased central aortic distensibility (2.8 +/- 0.7 vs 4.2 +/- 0.5 mm Hg(-1) x 10(-3), P < .001) and compliance (1.7 +/- 0.3 vs 2.5 +/- 0.6 mm2 mm Hg(-1), P < .001) and increased stiffness beta index (5.2 +/- 1 vs 2.5 +/- 0.6, P < .001). Pulse wave velocity was also significantly increased in the CoA subjects (4.7 +/- 1.3 vs 3.3 +/- 0.6 m/sec, P < .001). Left ventricular mass index was higher in the CoA subjects (84 +/-11 vs 73 +/-10 g/m2, P = .01) and correlated significantly with aortic stiffness beta index (r2 = 0.8, P < .0001). By contrast, descending aortic characteristics were similar in the CoA and control subjects. CONCLUSION: Central aortic stiffness is markedly increased and associated with increased left ventricular mass in normotensive young subjects after successful early repair of CoA.

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.

An automated image-processing strategy to analyze dynamic arterial spin labeling perfusion studies. Application to human skeletal muscle under stress.

Arterial spin labeling (ASL) perfusion measurements allow the follow-up of muscle perfusion with high temporal resolution during a stress test. Automated image processing is proposed to estimate perfusion maps from ASL images. It is based on two successive analyses: at first, automated rejection of the image pairs between which a large displacement is detected is performed, followed by factor analysis of the dynamic data and cluster analysis to classify pixels with large signal variation characteristic of vessels. Then, after masking these "vascular" pixels, factor analysis and cluster analysis are further applied to separate the different muscles between low or high perfusion increase, yielding a functional map of the leg. Data from 10 subjects (five normal volunteers and five elite sportsmen) had been analyzed. Resulting time perfusion curves from a region of interest (ROI) in active muscles show a good accordance whether extracted with automated processing or with manual processing. This method of functional segmentation allows automated suppression of vessels and fast visualization of muscles with high, medium or low perfusion, without any a priori knowledge.

Ultrasound elastography based on multiscale estimations of regularized displacement fields.

Elasticity imaging is based on the measurements of local tissue deformation. The approach to ultrasound elasticity imaging presented in this paper relies on the estimation of dense displacement fields by a coarse-to-fine minimization of an energy function that combines constraints of conservation of echo amplitude and displacement field continuity. The multiscale optimization scheme presents several characteristics aimed at improving and accelerating the convergence of the minimization process. This includes the nonregularized initialization at the coarsest resolution and the use of adaptive configuration spaces. Parameters of the energy model and optimization were adjusted using data obtained from a tissue-like phantom material. Elasticity images from normal in vivo breast tissue were subsequently obtained with these parameters. Introducing a smoothness constraint into motion field estimation helped solve ambiguities due to incoherent motion, leading to elastograms less degraded by decorrelation noise than the ones obtained from correlation-based techniques.

Automated estimation of regional mean transition times and radial velocities from cine magnetic resonance images: evaluation in normal subjects.

PURPOSE: To assess regional ventricular function via an accurate and automated definition of functional parameters. MATERIALS AND METHODS: An automated method is proposed that estimates reliable regional normalized mean transition times (F(mc)) and mean radial velocities (V(m)) from cine images. This approach combines a quantitative parametric imaging method and an automated detection of the endocardial border, which is robust to the presence of papillary muscles and nonhomogeneities within the left ventricular cavity. Steady-state free-precession cine-magnetic resonance imaging (MRI) of 36 healthy subjects was analyzed. RESULTS: The quality of the automated segmentation was assessed on a subgroup of 20 subjects by comparing the results with the manual contours traced by an expert. The comparison of functional parameters estimated consequently using the automated and the manual contours yielded (y = 0.959x + 0.016, R = 0.964) for F(mc) and (y = 0.883x + 0.505, R = 0.935) for V(m). On the entire group, F(mc) was equal to 0.392 +/- 0.069 and V(m) to 5.4 +/- 2.3 cm/s. Increasing values of the temporal parameter from the apex to the base and larger values in the septal wall than in lateral wall were demonstrated and were in accordance with the physiology. CONCLUSION: The proposed method ensures an automated and robust assessment of regional wall motion parameters, which could be clinically useful.

Robust assessment of the transmural extent of myocardial infarction in late gadolinium-enhanced MRI studies using appropriate angular and circumferential subdivision of the myocardium.

A computer-assisted method is proposed to estimate transmural extent of myocardial infarction. In 40 patients with chronic myocardial infarction and 3 control subjects, late gadolinium enhancement images were acquired with magnetic resonance imaging. Segmental infarct transmural extent was visually assessed by two experts on a 5-point scale. A fuzzy c-means algorithm was applied on both the cavity and myocardium to estimate an enhancement index for 12 sub-regions of each segment. A threshold was defined on a training database (n=29) to establish the transmurality extent of each sub-segment and was applied to the validation database (n=14). Inter-observer reproducibility reached an absolute agreement (Aa) of 85% and a kappa value (kappa) of 0.83 when considering the whole training database; Aa decreased to 62% and kappa to 0.68 when excluding homogeneous segments. On the validation database, segments were subdivided into three angular sub-segments. Then, inter-observer visual reproducibility reached Aa of 93% and kappa of 0.92. Moreover, the absolute comparison of each expert with the computer-assisted method yielded Aa higher than 88% and kappa higher than 0.86. The computer-assisted method quantifies infarct transmurality without defining remote and infarcted regions, and the transmural extent is accurately characterized when dividing each segment into three angular sub-segments.

Angular (Gothic) aortic arch leads to enhanced systolic wave reflection, central aortic stiffness, and increased left ventricular mass late after aortic coarctation repair: evaluation with magnetic resonance flow mapping.

OBJECTIVE: We sought to investigate the mechanism whereby a particular deformity of the aortic arch, an angulated Gothic shape, might lead to hypertension late after anatomically successful repair of aortic coarctation. METHODS: Fifty-five normotensive patients with anatomically successful repair of aortic coarctation and either a Gothic (angulated) or a Romanesque (smooth and rounded) arch were studied with magnetic resonance angiography and flow mapping in both the ascending and descending aortas. Systolic waveforms, central aortic stiffness, and pulse velocity were measured. We hypothesized that arch angulation would result in enhanced systolic wave reflection with loss of energy across the aortic arch, as well as increased central aortic stiffness. RESULTS: Twenty patients were found to have a Gothic, and 35 a Romanesque, arch. Patients with a Gothic arch showed markedly augmented systolic wave reflection (12 +/- 6 vs 5 +/- 0.3 mL, P < .001) and greater loss of systolic wave height in the distal aorta (30% +/- 16% vs 22% +/- 12%, P < .01) compared with that of subjects with a Romanesque arch. Pulse wave velocity was also increased with a Gothic arch (5.6 +/- 1.1 vs 4.1 +/- 1 m/s, P < .0001), as well as left ventricular mass index (85 +/- 15 vs 77 +/- 20 g/m2). Patients with a Romanesque arch had increased aortic stiffness compared with that of control subjects (stiffness beta-index, 3.9 +/- 0.9 vs 2.9 +/- 1; P = .03). CONCLUSIONS: Angulated Gothic aortic arch is associated with increased systolic wave reflection, as well as increased central aortic stiffness and left ventricular mass index. These findings explain (at least in part) the association between this pattern of arch geometry and late hypertension at rest and on exercise in subjects after coarctation repair.

Automatic detection of end systole within a sequence of left ventricular echocardiographic images using autocorrelation and mitral valve motion detection.

The automatic detection of end diastole and end systole is the first step of any software developed for a fully automatic calculation of the ejection fraction. In this study, methods of image processing were applied to black and white echocardiographic image sequences corresponding to a cardiac cycle and the end systolic image number was automatically estimated. The first method took the advantage of the rapid mitral valve motion to estimate the end systole from the time signal intensity variation in a cavity region defined thanks to three landmarks usually used for the standard left ventricular segmentation. The second method was fully automatic; it was based on the left ventricular deformation during the cardiac cycle. The deformation curve was estimated using correlation and its minimal value was used to detect end systole. Method 3 was a combination of the two previous methods to overcome their limitations. The three methods were tested on a group of 37 patients (four chambers and two chambers apical views). The first image exhibiting the beginning of the mitral opening was considered as the end systolic on the visual readings. Compared with this visual reference reading, a linear regression led to a correlation coefficient r of 0.84 for the first method. This coefficient was improved to 0.87 for the second method and increased significantly to r=0.93 for the third method.

An original methodology for quantitative assessment of perfusion in small animal studies using contrast-enhanced ultrasound.

The aim of this paper was to validate the combination of two original methods for assessing perfusion in small animal studies using Contrast-Enhanced Ultrasound. Respiratory motion was first removed using a frame selection method. This method, based on a Principal Component Analysis, enabled the definition of two subsequences, corresponding to the end-of-inspiration plane and to the end-of-expiration plane. Attenuation caused by contrast agent microbubbles was then estimated. The developed method, based on the assumption that a linear relationship holds between local attenuation and backscatter, used the time-intensity variation in a highly echogenic distal area without contrast uptake to estimate local attenuation coefficients. Ten murine renal perfusion studies were investigated after a bolus injection of SonoVue. Replenishment kinetics were acquired too and were finally modeled with an exponential function. Preliminary results were promising. Indeed, the SonoVue concentration was more faithfully represented than on native images, which allowed a better assessment of perfusion parameters in the whole field of view.

Evaluation of regional myocardial function using automated wall motion analysis of cine MR images: Contribution of parametric images, contraction times, and radial velocities.

PURPOSE: To develop fast and robust procedures for a clinical evaluation of regional myocardial contractile function. MATERIALS AND METHODS: Parametric analysis of main motion was applied to steady-state free-precession (SSFP) cine MR images. From the time-signal intensity curve associated with each pixel, parametric maps of mean high and low amplitudes and transition times between muscle and cavity were automatically computed. Then, regional time to first contraction, T(fc), mean contraction time, T(mc) and radial component of the endocardial velocity, V(m) were estimated from these parametric maps and a user-defined endocardial end-diastolic contour. The method was applied to short-axis slices in 22 subjects: eight controls, 13 myocardial infarctions (MIs), and one left bundle branch block (LBBB). RESULTS: Typical patterns of normality and pathology on parametric maps are indicated. For controls, the mean values +/- standard deviations (SDs) of T(fc), T(mc), and V(m) were: 70 +/- 25 msec, 318 +/- 43 msec, and 4.6 +/- 1.8 cm second(-1). An apex to base gradient of T(fc), a significant septal delay in T(fc) and T(mc), and a decrease of V(m) between the lateral and septal walls were observed. For MI, T(fc) and T(mc) increased and V(m) decreased significantly in pathological segments. For LBBB, large delays were estimated in the septal wall. CONCLUSION: The proposed method is promising for clinical assessment of regional wall contraction.

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.

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

PURPOSE: 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. MATERIALS AND METHODS: Eleven patients having a significant stenosis of at least one coronary artery detected by coronarography were examined by thallium tomoscintigraphy and perfusion MRI (first-pass of Gd-DTPA-BMA) at rest and under pharmacologic stress. The MRI images were analyzed by ASSERT to correct for rigid motion in the acquisition plane and to reject those images that were severely deformed or acquired outside the slice plane. The images thus obtained were analyzed by FAMIS. The resulting factor images representing myocardial perfusion were read to identify the ischemic territories corresponding to left anterior descending coronary arteries and right coronary arteries. RESULTS: ASSERT allowed automatic correction for motion and the exclusion of images that could not be registered. The ischemic territories, identified from the factor images of the myocardium, agreed with those identified by coronarography and tomoscintigraphy for 20 of the 22 territories. CONCLUSION: The results demonstrate the feasibility of analyzing myocardial perfusion using MRI acquisition and treating the resulting images by ASSERT and FAMIS. Extending this method to multislice examinations will enable evaluation of the perfusion of the whole myocardium.