Risk profiles for ventricular arrhythmias in hypertrophic cardiomyopathy through clustering analysis including left ventricular strain.

AIMS: The prediction of ventricular arrhythmia (VA) in hypertrophic cardiomyopathy (HCM) remains challenging. We sought to characterize the VA risk profile in HCM patients through clustering analysis combining clinical and conventional imaging parameters with information derived from left ventricular longitudinal strain analysis (LV-LS). METHODS: A total of 434 HCM patients (65% men, mean age 56 years) were included from two referral centers and followed longitudinally (mean duration 6 years). Mechanical and temporal parameters were automatically extracted from the LV-LS segmental curves of each patient in addition to conventional clinical and imaging data. A total of 287 features were analyzed using a clustering approach (k-means). The principal endpoint was VA. RESULTS: 4 clusters were identified with a higher rhythmic risk for clusters 1 and 4 (VA rates of 26%(28/108), 13%(13/97), 12%(14/120), and 31%(34/109) for cluster 1,2,3 and 4 respectively). These 4 clusters differed mainly by LV-mechanics with a severe and homogeneous decrease of myocardial deformation for cluster 4, a small decrease for clusters 2 and 3 and a marked deformation delay and temporal dispersion for cluster 1 associated with a moderate decrease of the GLS (p < 0.0001 for GLS comparison between clusters). Patients from cluster 4 had the most severe phenotype (mean LV mass index 123 vs. 112 g/m2; p = 0.0003) with LV and left atrium (LA) remodeling (LA-volume index (LAVI) 46.6 vs. 41.5 ml/m2, p = 0.04 and LVEF 59.7 vs. 66.3%, p < 0.001) and impaired exercise capacity (% predicted peak VO2 58.6 vs. 69.5%; p = 0.025). CONCLUSION: Processing LV-LS parameters in HCM patients 4 clusters with specific LV-strain patterns and different rhythmic risk levels are identified. Automatic extraction and analysis of LV strain parameters improves the risk stratification for VA in HCM patients.

The saga of dyssynchrony imaging: Are we getting to the point.

Cardiac resynchronisation therapy (CRT) has an established role in the management of patients with heart failure, reduced left ventricular ejection fraction (LVEF < 35%) and widened QRS (>130 msec). Despite the complex pathophysiology of left ventricular (LV) dyssynchrony and the increasing evidence supporting the identification of specific electromechanical substrates that are associated with a higher probability of CRT response, the assessment of LVEF is the only imaging-derived parameter used for the selection of CRT candidates. This review aims to (1) provide an overview of the evolution of cardiac imaging for the assessment of LV dyssynchrony and its role in the selection of patients undergoing CRT; (2) highlight the main pitfalls and advantages of the application of cardiac imaging for the assessment of LV dyssynchrony; (3) provide some perspectives for clinical application and future research in this field. Conclusion: the road for a more individualized approach to resynchronization therapy delivery is open and imaging might provide important input beyond the assessment of LVEF.

Evolution of non-invasive myocardial work variables after transcatheter aortic valve implantation in patients with severe aortic stenosis.

INTRODUCTION: Guidelines recommend aortic valve replacement in patients with severe aortic stenosis who present with symptoms or left ventricular ejection fraction<50%, both conditions representing a late stage of the disease. Whereas global longitudinal strain is load dependent, but interesting for assessing prognosis, myocardial work has emerged. AIM: To evaluate acute changes in myocardial work occurring in patients undergoing transcatheter aortic valve implantation (TAVI). METHODS: Patients who underwent TAVI were evaluated before and after by echocardiography. Complete echocardiographies were considered. Myocardial work indices (global work index, global constructive work, global work efficiency, global wasted work) were calculated integrating mean transaortic pressure gradient and brachial cuff systolic pressure. RESULTS: One hundred and twenty-five patients underwent successful TAVI, with a significant decrease in mean transaortic gradient (from 52.5±16.1 to 12.2±5.0; P<0.0001). There was no significant change in left ventricular ejection fraction after TAVI. Myocardial work data after TAVI showed a significant reduction in global work index (1389±537 vs. 2014±714; P<0.0001), global constructive work (1693±543 vs. 2379±761; P<0.0001) and global work efficiency (85.0±7.06 vs. 87.1±5.98; P=0.0034). The decrease in global work index and global constructive work after TAVI was homogeneous among different subgroups, based on global longitudinal strain, left ventricular ejection fraction and New York Heart Association status before TAVI. We observed a significant association between global work index and global constructive work before TAVI, and global longitudinal strain degradation after TAVI. CONCLUSIONS: Myocardial work variables show promising potential in best understanding the left ventricular myocardial consequences of aortic stenosis and its correction. Given their ability to discriminate between New York Heart Association status and global longitudinal strain evolution, we can hypothesize about their clinical value.

How myocardial work could be relevant in patients with an aortic valve stenosis?

AIMS: Myocardial work (MW) calculation is an attractive method to assess left ventricular (LV) myocardial function. In case of aortic stenosis (AS), assessment of work indices is challenging because it requires an accurate evaluation of LV-pressure curves. We sought to evaluate the performances of two distinct methods and to provide a quantitative comparison with invasive data. METHODS AND RESULTS: Model-based and template-based methods were defined and applied for the evaluation of LV-pressures on 67 AS-patient. Global Constructive (GCW), Wasted (GWW), Positive (GPW), Negative (GNW) MW and Global Work Efficiency (GWE), and Index (GWI) parameters were calculated using the available software computing the indices using brachial blood-pressure and trans-aortic mean pressure gradient (MPG) for estimating the LV-pressures vs. using a model-based and homemade software. A complete comparison was performed with invasive measurements. Patients were characterized by MPG of 49.8 ± 14.8 mmHg, the global longitudinal strain (GLS) was -15.0 ± 4.04%, GCW was 2107 ± 800 mmHg.% (model-based) and 2483 ± 1068 mmHg.% (template-based). The root mean square error (RMSE) and correlation were calculated for each patient and pressure estimation methods. The mean RMSE are 33.9 mmHg and 40.4 mmHg and the mean correlation coefficients are 0.81 and 0.72 for the model-based and template-based methods, respectively. The two methods present correlation coefficient r2 >0.75 for all the indices. CONCLUSION: The two non-invasive methods of LV pressure estimation and work indices computation correlate with invasive measurements. Although the model-based approach requires less information and is associated with slightly better performances, the implementation of template-based method is easier and is appropriate for clinical practice.

Desynchronization Strain Patterns and Contractility in Left Bundle Branch Block through Computer Model Simulation.

Left bundle branch block (LBBB) is associated with specific septal-to-lateral wall activation patterns which are strongly influenced by the intrinsic left ventricular (LV) contractility and myocardial scar localization. The objective of this study was to propose a computational-model-based interpretation of the different patterns of LV contraction observed in the case of LBBB and preserved contractility or myocardial scarring. Two-dimensional transthoracic echocardiography was used to obtain LV volumes and deformation patterns in three patients with LBBB: (1) a patient with non-ischemic dilated cardiomyopathy, (2) a patient with antero-septal myocardial scar, and (3) a patient with lateral myocardial scar. Scar was confirmed by the distribution of late gadolinium enhancement with cardiac magnetic resonance imaging (cMRI). Model parameters were evaluated manually to reproduce patient-derived data such as strain curves obtained from echocardiographic apical views. The model was able to reproduce the specific strain patterns observed in patients. A typical septal flash with pre-ejection shortening, rebound stretch, and delayed lateral wall activation was observed in the case of non-ischemic cardiomyopathy. In the case of lateral scar, the contractility of the lateral wall was significantly impaired and septal flash was absent. In the case of septal scar, septal flash and rebound stretch were also present as previously described in the literature. Interestingly, the model was also able to simulate the specific contractile properties of the myocardium, providing an excellent localization of LV scar in ischemic patients. The model was able to simulate the electromechanical delay and specific contractility patterns observed in patients with LBBB of ischemic and non-ischemic etiology. With further improvement and validation, this technique might be a useful tool for the diagnosis and treatment planning of heart failure patients needing CRT.