Two-dimensional strain rate and Doppler tissue myocardial velocities: analysis by echocardiography of hemodynamic and functional changes of the failed left ventricle during different degrees of extracorporeal life support.

BACKGROUND: To evaluate hemodynamic and functional changes of the failed left ventricle by Velocity Vector Imaging (VVI) and tissue Doppler, 22 patients with cardiogenic shock supported by extracorporeal life support (ECLS) were imaged during ECLS output variations inducing severe load manipulations. METHODS: The following data were acquired: (1) mean arterial pressure, aortic Doppler velocity-time integral, left ventricular end-diastolic volume, and mitral Doppler E wave; (2) tissue Doppler systolic (Sa) and early diastolic (Ea) velocities; and (3) systolic peak velocity (Sv), strain, and strain rate using VVI. RESULTS: Load variations were documented by a significant decrease in afterload (mean arterial pressure, -21%), an increase in preload (left ventricular end-diastolic volume, +12%; E, +46%; E/Ea ratio, +22%), and an increase in the velocity-time integral (+45%). VVI parameters increased (Sv, +36%; strain, +81%; and strain rate, +67%; P < .05), unlike tissue Doppler systolic velocities (+2%; P = NS). Whatever the ECLS flow, Sa was higher in patients who survived. CONCLUSIONS: VVI parameters are not useful in characterizing the failed left ventricle with rapidly varying load conditions. Tissue Doppler systolic velocities appear to be load independent and thus could help in the management of ECLS patients.

Diagnostic value of parametric imaging of left ventricular wall motion from contrast-enhanced echocardiograms in patients with poor acoustic windows.

BACKGROUND: Analysis of left ventricular (LV) regional wall motion (RWM) is subjective and may be challenging in patients with suboptimal images, even with contrast enhancement. It was hypothesized that the amplitude and timing of RWM obtained from contrast-enhanced echocardiograms can be accurately represented in still-frame parametric images. This study was designed to (1) test this hypothesis, (2) establish the diagnostic value of these images as an aid for inexperienced readers, and (3) test the feasibility of automated quantitative analysis of RWM. METHODS: Contrast-enhanced apical 4-chamber, 2-chamber, and 3-chamber LV views were acquired in 45 patients with poor acoustic windows. The interpretation of dynamic images by an experienced reader who classified RWM as normal or abnormal was used as a reference for comparisons against (1) visual interpretation of parametric images, (2) interpretation of dynamic images by two inexperienced readers (American Society of Echocardiography level I) without and subsequently with parametric images, and (3) automated quantification of RWM. RESULTS: Expert readers detected abnormal RWM in 30 patients (437 of 945 segments). Visual interpretation of parametric images showed good agreement with the reference (sensitivity, 85%; specificity, 82%; accuracy, 84%). The interpretations by inexperienced readers improved with the addition of parametric images, with increases in specificity (from 58% to 79%) and accuracy (from 74% to 84%), despite a slight decrease in sensitivity (from 92% to 91%). Automated classification was feasible and accurate (sensitivity, 82%; specificity, 78%; accuracy, 80%). CONCLUSION: Parametric images derived from contrast-enhanced echocardiograms of patients with poor acoustic windows accurately depicted RWM, improved the diagnostic accuracy of inexperienced readers, and allowed the objective detection of RWM abnormalities.

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.

Optimization of factor analysis of the left ventricle in echocardiography for detecting wall motion abnormalities.

This study has tested solutions to optimize the ability of factor analysis of the left ventricle in echocardiography (FALVE) to detect segmental wall motion abnormalities automatically. On four- and two-chamber views of 38 patients, two factors (one flat curve and one curve describing the contraction-relaxation sequence) were extracted and associated factor images were combined to synthesize a parametric image (constant image in green, positive/negative values of the contraction-relaxation image in red/blue). The segments were graded on the visual and the parametric views. The impact of selecting a whole cardiac cycle, masking the left ventricle and realigning the image sequence on the results, was demonstrated. Systematic realignment had a positive impact, especially for patients with left bundle branch block or pacemaker. After alignment, for the entire population, the absolute concordance was 68.6% and the relative concordance (within one grade) was 99%. Thus, FALVE is promising for detecting segmental wall motion abnormalities.

Factor analysis of the left ventricle by echocardiography (FALVE): a new tool for detecting regional wall motion abnormalities.

BACKGROUND: Factor analysis of the left ventricle in echography was developed to study the regional wall motion. Two factors and associated factor images were estimated using specific constraints: one "constant" factor and another "contraction-relaxation" factor. The constant factor was encoded in green, the positive component of the contraction in red and the negative in blue. METHODS: The evaluation was carried out on 12 patients with LBBB or pacemaker (group A), and on 26 others (group B). The segments were graded separately on the cine-loops by three experienced echocardiographers. Similarly, the three-color combination of the factor images was read at the endocardial border and each segment was scored. RESULTS: An absolute concordance was obtained for 64.8% of the segments and a relative concordance (within one grade) for 97.2%. They were 71% and 99.6% in group B. Most of the discordant cases were explained by the global motion during the cardiac cycle. The standard deviation of the difference between the mean wall motion scores was 0.38 for all the patients; it was reduced to 0.30 in group B. CONCLUSION: Factor analysis is a promising tool to study the regional wall motion. It might become useful for assessing segmental wall motion in 2D and 3D echo.