It's time for a paradigm shift in the quantitative evaluation of left ventricular dyssynchrony

Variability in the Assessment of Myocardial Strain Patterns: Implications for Adequate Interpretation

Variability in global and regional peak strain has been thoroughly studied, but variability in spatiotemporal myocardial strain patterns has not been studied as well. This study reports on such variability and its implications for adequate disease interpretation. Forty in-training operators, distributed on 20 workstations, analyzed six cases with representative deformation patterns with commercial speckle tracking. Inter-operator differences were quantified through the variability in myocardial delineations, spatiotemporal longitudinal strain patterns and peak longitudinal strain. Intra-operator differences were assessed similarly using 10 repeated measurements from a single clinician expert. Delineations varied mainly along the lateral wall and at the valve level. Peak longitudinal strain variability was low to moderate. The spatiotemporal strain patterns were consistent despite high variability at the apex and near the valve. The results indicate that relevant pattern assessment is possible despite heterogeneous experience with speckle tracking and that careful interpretation of pattern abnormalities should be recommended before a more systematic quantitative analysis.

A framework for combining a motion atlas with non-motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction

We present a framework for combining a cardiac motion atlas with non-motion data. The atlas represents cardiac cycle motion across a number of subjects in a common space based on rich motion descriptors capturing 3D displacement, velocity, strain and strain rate. The non-motion data are derived from a variety of sources such as imaging, electrocardiogram (ECG) and clinical reports. Once in the atlas space, we apply a novel supervised learning approach based on random projections and ensemble learning to learn the relationship between the atlas data and some desired clinical output. We apply our framework to the problem of predicting response to Cardiac Resynchronisation Therapy (CRT). Using a cohort of 34 patients selected for CRT using conventional criteria, results show that the combination of motion and non-motion data enables CRT response to be predicted with 91.2% accuracy (100% sensitivity and 62.5% specificity), which compares favourably with the current state-of-the-art in CRT response prediction.

Recoordination of opposing walls drives the response to cardiac resynchronization therapy: a longitudinal study using a strain discoordination index

BACKGROUND AND AIMS

Intraventricular dyssynchrony has traditionally been studied by means of contraction delays between different myocardial segments. Recently, the discoordination of opposing wall contraction throughout the cardiac cycle has been proposed as a more faithful predictor of response. Aim of the current study was to evaluate which parameters - mechanical dyssynchrony or discoordination - normalize with left ventricular response to cardiac resynchronization therapy (CRT).

METHODS

Cardiac mechanics were analysed before and after 6 months of CRT in 53 patients with left bundle branch block and advanced heart failure. Discoordination was quantified by means of the transverse strain discoordination index (TSDI) at basal and mid-ventricular segments; this index takes into account the percentage of time in the cardiac cycle in which cardiac deformation (transverse strain) of the two opposing walls occurs in noncoordinated directions. Dyssynchrony indices included septal to lateral peak-to-peak transverse strain delay and the standard deviation of time to peak tissue velocity in 12 mid-basal segments (Yu index).

RESULTS

Around 63% of patients met the response criteria. Several baseline indices were predictive of reverse remodelling; TSDI at the mid-ventricular level demonstrated the best accuracy. Time from Q to peak velocity and strain tended to increase in all explored myocardial segments; despite a trend towards a decrease in septal-to-lateral strain delay, the latter decreased equally in responders and in nonresponding patients. Yu index decreased in responders more than in nonresponders, with borderline significance. Basal and medium TSDI remained unchanged in nonresponders and consistently normalized in patients who responded to CRT. The changes in TSDI were significantly correlated with improvements in left ventricular end-systolic volume and ejection fraction; the strongest correlation was observed for changes in TSDI measured at the mid-ventricular level.

CONCLUSION

Left ventricular reverse remodelling after CRT is accompanied by the recoordination of opposite-wall contraction, as testified by changes in mid-ventricular TSDI, which also reveals as a very good predictor of response. On the contrary, changes of segmental peak-to-peak delays (dyssynchrony indices) fail to capture the complex nature of left ventricular response to CRT.

Measures of dyssynchrony in the left ventricle of healthy children and young patients with dilated cardiomyopathy

BACKGROUND

Doppler tissue imaging may help identify children with dyssynchrony who could benefit from resynchronization therapy. However, few studies have quantified dyssynchrony measures in children; no study has investigated the relationship among age, heart rate, and dyssynchrony measures in children; and no study has quantified cross-correlation delay in children. The aim of this study was to test the hypotheses that measures of left ventricular dyssynchrony would correlate with age, primarily because of the correlation between heart rate and age, and that children with cardiomyopathy would have left ventricular dyssynchrony.

METHODS

Sixty healthy children and 11 children with dilated cardiomyopathy were prospectively enrolled. Seven dyssynchrony measures were quantified: septal-to-lateral delay, peak velocity difference, the standard deviations of times to peak in 12 segments in systole and diastole, and cross-correlation delay in systole, diastole, and the whole cycle.

RESULTS

The seven dyssynchrony measures were either not correlated with age or only weakly correlated with age after correcting for heart rate using Bazett's formula. Septal-to-lateral delay, peak velocity difference, and the standard deviation of times to peak in 12 segments in systole showed dyssynchrony in 57% to 85% of normal controls, compared with 20% for cross-correlation delay in the whole cycle and 3% for the standard deviation of times to peak in 12 segments in diastole. Cross-correlation delay in systole, cross-correlation delay in diastole, cross-correlation delay in the whole cycle, and the standard deviation of times to peak in 12 segments in diastole were elevated in children with dilated cardiomyopathy compared with controls.

CONCLUSIONS

Echocardiographic dyssynchrony measures should be corrected for heart rate using Bazett's formula in children. Time-to-peak Doppler tissue imaging dyssynchrony measures classify many healthy children as having abnormalities with the timing of left ventricular contraction, which suggests that the methodology is not accurate in children. In preliminary studies, cross-correlation dyssynchrony measures show elevated systolic and diastolic measures of dyssynchrony in children with dilated cardiomyopathy compared with controls, which deserves further investigation to help identify children who may benefit from resynchronization therapy.

Atlas-based quantification of myocardial motion abnormalities: added-value for understanding the effect of cardiac resynchronization therapy

Statistical atlases may help improving the analysis of cardiac wall-motion abnormalities. This study aims at demonstrating the clinical value of such a method to better understand the effect of cardiac resynchronization therapy (CRT). We compared an atlas of normal septal motion built using apical four-chamber two-dimensional echocardiographic sequences from healthy volunteers with 88 patients undergoing CRT at baseline and at 12 months follow-up. Abnormal motion was quantified locally using a p value based on a statistical distance to normality. Reduction ≥15% in left ventricle end-systolic volume defined CRT response. Responders showed significantly higher reduction of abnormalities (p ≤ 0.001). Non-responders conserved abnormal septal motion at the end of the isovolumic contraction (IVC). A specific inward-outward motion of the septum during IVC predominated in responders and was corrected at follow-up. The method is of interest to characterize patterns of mechanical dyssynchrony and to study the link between their evolution and CRT response.

Constrained manifold learning for the characterization of pathological deviations from normality

This paper describes a technique to (1) learn the representation of a pathological motion pattern from a given population, and (2) compare individuals to this population. Our hypothesis is that this pattern can be modeled as a deviation from normal motion by means of non-linear embedding techniques. Each subject is represented by a 2D map of local motion abnormalities, obtained from a statistical atlas of myocardial motion built from a healthy population. The algorithm estimates a manifold from a set of patients with varying degrees of the same disease, and compares individuals to the training population using a mapping to the manifold and a distance to normality along the manifold. The approach extends recent manifold learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Interpolation techniques using locally adjustable kernel improve the accuracy of the method. The technique is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssynchrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 37 CRT candidates and 21 healthy volunteers. Experiments highlight the relevance of non-linear techniques to model a pathological pattern from the training set and compare new individuals to this pattern.

A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities

In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT.