Oana Mirea

Effects of aging and body size on proximal and ascending aorta and aortic arch: Inner edge-to-inner edge reference values in a large adult population by two-dimensional transthoracic echocardiography

BACKGROUND Aortic size is known to vary significantly by age and body size and to be an important predictor of cardiovascular diseases. The aim of this study was to determine reference values for proximal thoracic aorta diameters, using the inner edge technique and two-dimensional transthoracic echocardiography. METHODS Diameters of the aortic annulus, sinuses of Valsalva, sinotubular junction, arch, and ascending aorta and the angle of insertion of the aorta were measured in 500 subjects (231 women; mean age, 48 ± 18 years) with normal echocardiographic findings, retrospectively enrolled. The relations of age and body size with aortic measurements were investigated using bivariate and multiple linear regressions. RESULTS Measurements were highly feasible (83% for the aortic arch, 100% for the other segments). All aortic diameters significantly related to age, weight and body surface area, while height was correlated only with annular diameter. In predictive models adjusted for gender, older age was associated with increased aortic diameters (R(2) values ranged from 0.36 for the sinotubular junction to 0.52 for the sinuses of Valsalva). Adjustments for height and weight led to significant improvements (R(2) values ranged from 0.43 for the sinotubular junction to 0.58 for the sinuses of Valsalva). Similar correlations were observed for men and women. Angle was found to be dependent only on age and gender. Reproducibility analysis showed good to excellent accordance between repeated measurements. CONCLUSIONS The results of this study show the effect of aging on the proximal thoracic aorta and emphasize the importance of accounting for gender and body size when assessing aortic size. The obtained reference ranges will help standardize the assessment of aortic dimensions by applying inner edge convention and facilitate comparisons with other imaging techniques.

Reliability and feasibility of longitudinal AFI global and segmental strain compared with 2D left ventricular volumes and ejection fraction: intra- and inter-operator, test–retest, and inter-cycle reproducibility

AIMS Echocardiographic evaluation of 2D longitudinal peak systolic strain (LPSS) can detect initial impairment of left ventricular (LV) function in heart disease. Global LPSS (GLPSS) variability has been assessed in small groups and segmental LPSS has not been determined. We compared variability of GLPSS and segmental LPSS with that of 2D LV volumes and ejection fraction (EF) in patients with and without heart diseases. METHODS AND RESULTS 2D speckle tracking analysis was performed on LV apical views using automated function imaging (AFI) software (GE Healthcare). Intra-operator, inter-cycle, and test-retest variability (bias and CR, coefficient of reproducibility; MPE, mean percent error; CV, coefficient of variation) was assessed for GLPSS, 18 segments of LPSS, and LV volumes and EF in 40 patients (720 segments), and inter-operator variability in 250 patients (4500 segments). Feasibility of segmental tracking was 93.1%. Variability of GLPSS increased from a minimum intra-operator CV = -2.6% to a maximum test-retest CV = -5.4% and was lower than that assessed for volumes and EF. Segmental intra-operator LPSS CV ranged from -5.6 to -14.7%, and test-retest from -8 to -22%, and was at worst similar to variability of end-systolic volume. In the 8.3% of segments with the highest variability, this was related to suboptimal imaging, minor changes in scan angulation, and insufficient ROI width. CONCLUSION Overall, reproducibility of GLPSS is excellent and superior to that of 2D EF, whereas segmental LPSS reproducibility is good and similar to that of LV volumes. Both are suitable for diagnosis and follow-up of LV global and regional systolic function.

Recent advances in echocardiography: strain and strain rate imaging

Deformation imaging by echocardiography is a well-established research tool which has been gaining interest from clinical cardiologists since the introduction of speckle tracking. Post-processing of echo images to analyze deformation has become readily available at the fingertips of the user. New parameters such as global longitudinal strain have been shown to provide added diagnostic value, and ongoing efforts of the imaging societies and industry aimed at harmonizing methods will improve the technique further. This review focuses on recent advances in the field of echocardiographic strain and strain rate imaging, and provides an overview on its current and potential future clinical applications.

Comparison of Feasibility, Accuracy, and Reproducibility of Layer-Specific Global Longitudinal Strain Measurements Among Five Different Vendors: A Report from the EACVI-ASE Strain Standardization Task Force

Background: Despite standardization efforts, vendors still use information from different myocardial layers to calculate global longitudinal strain (GLS). Little is known about potential advantages or disadvantages of using these different layers in clinical practice. The authors therefore investigated the reproducibility and accuracy of GLS measurements from different myocardial layers. Methods: Sixty‐three subjects were prospectively enrolled, in whom the intervendor bias and test‐retest variability of endocardial GLS (E‐GLS) and midwall GLS (M‐GLS) were calculated, using software packages from five vendors that allow layer‐specific GLS calculation (GE, Hitachi, Siemens, Toshiba, and TomTec). The impact of tracking quality and the interdependence of strain values from different layers were assessed by comparing test‐retest errors between layers. Results: For both E‐GLS and M‐GLS, significant bias was found among vendors. Relative test‐retest variability of E‐GLS values differed significantly among vendors, whereas M‐GLS showed no significant difference (range, 5.4%–9.5% [P = .032] and 7.0%–11.2% [P = .200], respectively). Within‐vendor test‐retest variability was similar between E‐GLS and M‐GLS for all but one vendor. Absolute test‐retest errors were highly correlated between E‐GLS and M‐GLS for all vendors. Conclusions: E‐GLS and M‐GLS measurements showed no relevant differences in robustness among vendors, although intervendor bias was higher for M‐GLS compared with E‐GLS. These data provide no technical argument in favor of a certain myocardial layer for global left ventricular functional assessment. Currently, the choice of which layer to use should therefore be based on the available clinical evidence in the literature.

Machine learning of the spatio-temporal characteristics of echocardiographic deformation curves for infarct classification

The aim of this study was to analyze the whole temporal profiles of the segmental deformation curves of the left ventricle (LV) and describe their interrelations to obtain more detailed information concerning global LV function in order to be able to identify abnormal changes in LV mechanics. The temporal characteristics of the segmental LV deformation curves were compactly described using an efficient decomposition into major patterns of variation through a statistical method, called Principal Component Analysis (PCA). In order to describe the spatial relations between the segmental traces, the PCA-derived temporal features of all LV segments were concatenated. The obtained set of features was then used to build an automatic classification system. The proposed methodology was applied to a group of 60 MRI-delayed enhancement confirmed infarct patients and 60 controls in order to detect myocardial infarction. An average classification accuracy of 87% with corresponding sensitivity and specificity rates of 89% and 85%, respectively was obtained by the proposed methodology applied on the strain rate curves. This classification performance was better than that obtained with the same methodology applied on the strain curves, reading of two expert cardiologists as well as comparative classification systems using only the spatial distribution of the end-systolic strain and peak-systolic strain rate values. This study shows the potential of machine learning in the field of cardiac deformation imaging where an efficient representation of the spatio-temporal characteristics of the segmental deformation curves allowed automatic classification of infarcted from control hearts with high accuracy.

Multidirectional left ventricle and longitudinal right ventricle deformation analysis by two dimensional speckle tracking echocardiography in young elite athletes.

Objective By using a multiparametric two-dimensional speckle tracking analysis we aimed at investigating whether high performance sport induces changes in the left and right ventricular mechanics in young subjects. Methods and results Young elite athletes (n = 37, mean age 17.5 ± 3.7 years) divided by type of activity in endurance athletes [EAs] (n = 30) and strength athletes [SAs] (n = 7) and sedentary subjects (n = 22, mean age 20.1 ± 4.6 years) were prospectively enrolled. The subjects were analysed using standard two-dimensional echocardiography and two-dimensional speckle tracking echocardiography. Left ventricle (LV) deformation measurements included global peak systolic (GLPSS) and maximum longitudinal strain (GLMS), circumferential (GCMS) and radial strain (GRMS). Additionally, LV postsystolic index (PSI) and rotational components were investigated. Right ventricle (RV) deformation evaluation consisted of mean longitudinal peak systolic strain (LPSS). Athletes presented increased LV mass (P <0.05) and hypertrophy of the RV free wall (P <0.01) No difference regarding LV volumes or ejection fraction was found. RV end-systolic (P <0.05) and end-diastolic area (P <0.01) and RA end-systolic (P <0.05) and end-diastolic volumes (P <0.05) were larger in athletes. GLPSS (P <0.01) and GLMS (P <0.05) were decreased in athletes, with SAs presenting the lowest values, while no significant differences concerning PSI, GCMS, GRMS or the rotational components were found in athletes when compared to controls. RV LPSS was similar in both groups. Conclusions Young performance athletes demonstrate a subtle but significant reduction of LV longitudinal deformation, more pronounced in strength performers while circumferential and radial deformations as well as the RV longitudinal strain.

Automatic detection of ischemic myocardium by spatio-temporal analysis of echocardiographic strain and strain rate curves

Interpretation of ultrasonic deformation traces for making a diagnosis on local myocardial function has been known to be a challenging task in daily clinical practice. A traditional approach is to use values extracted at specific time points during the cardiac cycle which has the main drawback of not taking the temporal information of the deformation traces into account. This paper presents a framework for the automatic detection of ischemic myocardium by statistical analysis of the entire segmental strain and strain rate curves using principal component analysis (PCA). Having the PCA-derived parameters of the regional temporal profiles at hand, a spatio-temporal representation of the global left ventricle (LV) function is established to train a classification system. Experimental outcomes show that the proposed deformation representation of the LV can outperform its traditional counterpart in categorizing healthy from ischemic myocardium.

Right ventricular remodelling after transcatheter pulmonary valve implantation

To define the optimal timing for percutaneous pulmonary valve implantation (PPVI) in patients with severe pulmonary regurgitation (PR) after Fallots Tetralogy (ToF) correction.

Spatiotemporal registration of multiple three-dimensional echocardiographic recordings for enhanced field of view imaging

Abstract. The use of three-dimensional (3-D) echocardiography is limited by signal dropouts and narrow field of view. Data compounding is proposed as a solution to overcome these limitations by combining multiple 3-D recordings to form a wide field of view. The first step of the solution requires registration between the recordings both in the spatial and temporal dimension for dynamic organs such as the heart. Accurate registration between the individual echo recordings is crucial for the quality of compounded volumes. A temporal registration method based on a piecewise one-dimensional cubic B-spline in combination with multiscale iterative Farnebäck optic flow method for spatial registration was described. The temporal registration method was validated on in vivo data sets with annotated timing of mitral valve opening. The spatial registration method was validated using in vivo data and compared to registration with Procrustes analysis using manual contouring as a benchmark. The spatial accuracy was assessed in terms of mean of absolute distance and Hausdorff distance between the left ventricular contours. The results showed that the temporal registration accuracy is in the range of half the time resolution of the echo recordings and the achieved spatial accuracy of the proposed method is comparable to manual registration.

Integration of Multi-Plane Tissue Doppler and B-Mode Echocardiographic Images for Left Ventricular Motion Estimation

Although modern ultrasound acquisition systems allow recording of 3D echocardiographic images, tracking anatomical structures from them is still challenging. In addition, since these images are typically created from information obtained across several cardiac cycles, it is not yet possible to acquire high-quality 3D images from patients presenting varying heart rhythms. In this paper, we propose a method to estimate the motion field from multi-plane echocardiographic images of the left ventricle, which are acquired simultaneously during a single cardiac cycle. The method integrates tri-plane B-mode and tissue Doppler images acquired at different rotation angles around the long axis of the left ventricle. It uses a diffeomorphic continuous spatio-temporal transformation model with a spherical data representation for a better interpolation in the circumferential direction. This framework allows exploiting the spatial relation among the acquired planes. In addition, higher temporal resolution of the transformation in the beam direction is achieved by uncoupling the estimation of the different components of the velocity field. The method was validated using a realistic synthetic dataset including healthy and ischemic cases, obtaining errors of 0.14 ± 0.09 mm for displacements, 0.96 ± 1.03% for longitudinal strain and 3.94 ± 4.38% for radial strain estimation. In addition, the method was also demonstrated on a healthy volunteer and two patients with ischemia.