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.

Reproducibility of the 2016 American Society of Echocardiography-European Association of Cardiovascular Imaging Algorithm for Estimation of Left Ventricular Filling Pattern: Not Perfect but Good Enough.

The 2016 American Society of Echocardiography (ASE) and European Association of Cardiovascular Imaging (EACVI) guidelines for the evaluation of left ventricular diastolic function reported a new algorithm to assess diastolic function and to estimate left ventricular filling pressure (LVFP). At least five to six different parameters were necessary to conclude, each of them with their own inter-observer variability. This article examines the reproducibility of each parameter of the algorithm and its influence on the final decision of the clinician. Echocardiographic exams of 12 non-selected patients without any known cardiac disease or follow-up but addressed to the hospital for symptoms were analyzed by two readers (one junior and one senior) in five French cardiologic tertiary centers. Inter-observer reproducibility at each step of the algorithm and final decision were analyzed. There was mild agreement on the final decision. The main reasons of discrepancy were disagreement on the significance of mitral annular calcifications and measured values that are just around the cut-off (despite good reproducibility, a slight variation could lead to misclassification of a dichotomous choice between a normal measure and a pathologic measure). Without considering performance, this multicentric French study puts forward limits to the actual algorithm recommended for LVFP pattern assessment. Agreement is excellent in caricatural (easy) cases (left ventricular pressure clearly normal or clearly elevated) but a great discordance exists in the gray zone. Improvement in the algorithm and in the method for LVFP determination is proposed.

Left atrial strain is a predictor of left ventricular systolic and diastolic reverse remodelling in CRT candidates.

AIMS: The left atrium (LA) has a pivotal role in cardiac performance and LA deformation is a well-known prognostic predictor in several clinical conditions including heart failure with reduced ejection fraction. The aim of this study is to investigate the effect of cardiac resynchronization therapy (CRT) on both LA morphology and function and to assess the impact of LA reservoir strain (LARS) on left ventricular (LV) systolic and diastolic remodelling after CRT. METHODS AND RESULTS: Two hundred and twenty-one CRT-candidates were prospectively included in the study in four tertiary centres and underwent echocardiography before CRT-implantation and at 6-month follow-up (FU). CRT-response was defined by a 15% reduction in LV end-systolic volume. LV systolic and diastolic remodelling were defined as the percent reduction in LV end-systolic and end-diastolic volume at FU. Indexed LA volume (LAVI) and LV-global longitudinal (GLS) strain were the main parameters correlated with LARS, with LV-GLS being the strongest determinant of LARS (r = -0.59, P < 0.0001). CRT induced a significant improvement in LAVI and LARS in responders (both P < 0.0001). LARS was an independent predictor of both LV systolic and diastolic remodelling at follow-up (r = -0.14, P = 0.049 and r = -0.17, P = 0.002, respectively). CONCLUSION: CRT induces a significant improvement in LAVI and LARS in responders. In CRT candidates, the evaluation of LARS before CRT delivery is an independent predictor of LV systolic and diastolic remodelling at FU.

Rational and Design of the SIMULATOR Study: A Multicentre Randomized Study to Assess the Impact of SIMULation-bAsed Training on Transoesophageal echocardiOgraphy leaRning for Cardiology Residents.

Introduction: Simulation-based training in transesophageal echocardiography (TEE) seems promising. However, data are limited to non-randomized or single-center studies. To assess the impact of simulation-based vs. traditional teaching on TEE knowledge and performance for medical residents in cardiology. Materials and Methods: Nationwide prospective randomized multicenter study involving 43 centers throughout France allowing for the inclusion of >70% of all French cardiology residents. All cardiology residents naive from TEE will be included. Randomization with stratification by center will allocate residents to either a control group receiving theoretical knowledge by e-learning only, or to an intervention group receiving two simulation-based training sessions on a TEE simulator in addition. Results: All residents will undergo both a theoretical test (0-100 points) and a practical test on a TEE simulator (0-100 points) before and 3 months after the training. Satisfaction will be assessed by a 5-points Likert scale. The primary outcomes will be to compare the scores in the final theoretical and practical tests between the two groups, 3 months after the completion of the training. Conclusion: Data regarding simulation-based learning in TEE are limited to non-randomized or single-center studies. The randomized multicenter SIMULATOR study will assess the impact of simulation-based vs. traditional teaching on TEE knowledge and performance for medical residents in cardiology, and whether such an educational program should be proposed in first line for TEE teaching.

Echocardiographic view and feature selection for the estimation of the response to CRT.

Cardiac resynchronization therapy (CRT) is an implant-based therapy applied to patients with a specific heart failure (HF) profile. The identification of patients that may benefit from CRT is a challenging task and the application of current guidelines still induce a non-responder rate of about 30%. Several studies have shown that the assessment of left ventricular (LV) mechanics by speckle tracking echocardiography can provide useful information for CRT patient selection. A comprehensive evaluation of LV mechanics is normally performed using three different echocardioraphic views: 4, 3 or 2-chamber views. The aim of this study is to estimate the relative importance of strain-based features extracted from these three views, for the estimation of CRT response. Several features were extracted from the longitudinal strain curves of 130 patients and different methods of feature selection (out-of-bag random forest, wrapping and filtering) have been applied. Results show that more than 50% of the 20 most important features are calculated from the 4-chamber view. Although features from the 2- and 3-chamber views are less represented in the most important features, some of the former have been identified to provide complementary information. A thorough analysis and interpretation of the most informative features is also provided, as a first step towards the construction of a machine-learning chain for an improved selection of CRT candidates.

One year prognostic value of B-lines in dyspnoeic patients.

AIMS: Studies have demonstrated the reliability of B-lines evaluated by lung ultrasonography to identify pulmonary congestion, but information is lacking about its utility as a prognostic marker of heart failure (HF). We sought to assess the prognostic midterm value of B-lines in ambulatory patients presenting with dyspnoea, as an additive tool for patient management and to avoid acute HF exacerbations. METHODS AND RESULTS: A total of 93 patients presenting with dyspnoea (New York Heart Association ≥2) were prospectively recruited in an outpatient clinic, and underwent clinical and echocardiographic evaluation, as well as B-line evaluation with lung ultrasonography in eight zones. Primary endpoint was HF hospitalization at 1 year. A total of 88 patients were included, age 72.3 ± 9.6, with left ventricular ejection 47.7 ± 28.6%; E/e' 16.9 ± 10.9, left atrial volume 51.9 ± 22.5 mL/m2 ; peak tricuspid regurgitation velocity 2.6 ± 0.5 m/s, average B-line count 7.7 ± 10. 8 (9%) patients were hospitalized for HF, seven of which had ≥6 B-lines. B-line cut-off ≥6 (specificity = 66.2%; sensitivity = 87.5%) was predictive for HF hospitalization, with an odds ratio at 13.7 for HF hospitalization at 1 year [IC95% (1.6-117.4), P = 0.017]. CONCLUSIONS: Ambulatory patients with ≥6 B-lines have a higher risk of HF hospitalization at 1 year. This study highlights the prognostic value of B-lines in evaluating HF risk in dyspnoeic patients.

Characterization of Responder Profiles for Cardiac Resynchronization Therapy through Unsupervised Clustering of Clinical and Strain Data.

BACKGROUND: The mechanisms of improvement of left ventricular (LV) function with cardiac resynchronization therapy (CRT) are not yet elucidated. The aim of this study was to characterize CRT responder profiles through clustering analysis, on the basis of clinical and echocardiographic preimplantation data, integrating automatic quantification of longitudinal strain signals. METHODS: This was a multicenter observational study of 250 patients with chronic heart failure evaluated before CRT device implantation and followed up to 4 years. Clinical, electrocardiographic, and echocardiographic data were collected. Regional longitudinal strain signals were also analyzed with custom-made algorithms in addition to existing approaches, including myocardial work indices. Response was defined as a decrease of ≥15% in LV end-systolic volume. Death and hospitalization for heart failure at 4 years were considered adverse events. Seventy features were analyzed using a clustering approach (k-means clustering). RESULTS: Five clusters were identified, with response rates between 50% in cluster 1 and 92.7% in cluster 5. These five clusters differed mainly by the characteristics of LV mechanics, evaluated using strain integrals. There was a significant difference in event-free survival at 4 years between cluster 1 and the other clusters. The quantitative analysis of strain curves, especially in the lateral wall, was more discriminative than apical rocking, septal flash, or myocardial work in most phenogroups. CONCLUSIONS: Five clusters are described, defining groups of below-average to excellent responders to CRT. These clusters demonstrate the complexity of LV mechanics and prediction of response to CRT. Automatic quantitative analysis of longitudinal strain curves appears to be a promising tool to improve the understanding of LV mechanics, patient characterization, and selection for CRT.

Importance of Systematic Right Ventricular Assessment in Cardiac Resynchronization Therapy Candidates: A Machine Learning Approach.

BACKGROUND: Despite all having systolic heart failure and broad QRS intervals, patients screened for cardiac resynchronization therapy (CRT) are highly heterogeneous, and it remains extremely challenging to predict the impact of CRT devices on left ventricular function and outcomes. The aim of this study was to evaluate the relative impact of clinical, electrocardiographic, and echocardiographic data on the left ventricular remodeling and prognosis of CRT candidates by the application of machine learning approaches. METHODS: One hundred ninety-three patients with systolic heart failure receiving CRT according to current recommendations were prospectively included in this multicenter study. A combination of the Boruta algorithm and random forest methods was used to identify features predicting both CRT volumetric response and prognosis. Model performance was tested using the area under the receiver operating characteristic curve. The k-medoid method was also applied to identify clusters of phenotypically similar patients. RESULTS: From 28 clinical, electrocardiographic, and echocardiographic variables, 16 features were predictive of CRT response, and 11 features were predictive of prognosis. Among the predictors of CRT response, eight variables (50%) pertained to right ventricular size or function. Tricuspid annular plane systolic excursion was the main feature associated with prognosis. The selected features were associated with particularly good prediction of both CRT response (area under the curve, 0.81; 95% CI, 0.74-0.87) and outcomes (area under the curve, 0.84; 95% CI, 0.75-0.93). An unsupervised machine learning approach allowed the identification of two phenogroups of patients who differed significantly in clinical variables and parameters of biventricular size and right ventricular function. The two phenogroups had significantly different prognosis (hazard ratio, 4.70; 95% CI, 2.1-10.0; P < .0001; log-rank P < .0001). CONCLUSIONS: Machine learning can reliably identify clinical and echocardiographic features associated with CRT response and prognosis. The evaluation of both right ventricular size and functional parameters has pivotal importance for the risk stratification of CRT candidates and should be systematically performed in patients undergoing CRT.

Left ventricular strain for predicting the response to cardiac resynchronization therapy: two methods for one question.

AIMS: Myocardial work (manually controlled software) and integral-derived longitudinal strain (automatic quantification of strain curves) are two promising tools to quantify dyssynchrony and potentially select the patients that are most likely to have a reverse remodelling due to cardiac resynchronization therapy (CRT). We sought to test and compare the value of these two methods in the prediction of CRT-response. MATERIALS AND RESULTS: Two hundred and forty-three patients undergoing CRT-implantation from three European referral centres were considered. The characteristics from the six-segment of the four-chamber view were computed to obtain regional myocardial work and the automatically generated integrals of strain. The characteristics were studied in mono-parametric and multiparametric evaluations to predict CRT-induced 6-month reverse remodelling. For each characteristic, the performance to estimate the CRT response was determined with the receiver operating characteristic (ROC) curve and the difference between the performances was statistically evaluated. The best area under the curve (AUC) when only one characteristic used was obtained for a myocardial work (AUC = 0.73) and the ROC curve was significantly better than the others. The best AUC for the integrals was 0.63, and the ROC curve was not significantly greater than the others. However, with the best combination of works and integrals, the ROC curves were not significantly different and the AUCs were 0.77 and 0.72. CONCLUSION: Myocardial work used in a mono-parametric estimation of the CRT-response has better performance compared to other methods. However, in a multiparametric application such as what could be done in a machine-learning approach, the two methods provide similar results.

Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic and echocardiographic parameters, could enhance the appraisal of the likelihood of reverse remodeling and prognosis of favorable clinical evolution to improve the response of cardiac resynchronization therapy (CRT). Three hundred and twenty-three heart failure patients were retrospectively included in this multicenter study. 221 patients (68%) were responders, defined by a decrease in left ventricle end-systolic volume ≥15% at the 6-month follow-up. In addition, strain data coming from echocardiography were analyzed with custom-made signal processing methods. Integrals of regional longitudinal strain signals from the beginning of the cardiac cycle to strain peak and to the instant of aortic valve closure were analyzed. QRS duration, septal flash and different other features manually extracted were also included in the analysis. The random forest (RF) method was applied to analyze the relative feature importance, to select the most significant features and to build an ensemble classifier with the objective of predicting response to CRT. The set of most significant features was composed of Septal Flash, E, E/A, E/EA, QRS, left ventricular end-diastolic volume and eight features extracted from strain curves. A Monte Carlo cross-validation method with 100 runs was applied, using, in each run, different random sets of 80% of patients for training and 20% for testing. Results show a mean area under the curve (AUC) of 0.809 with a standard deviation of 0.05. A multiparametric approach using a combination of echo-based parameters of left ventricular dyssynchrony and QRS duration helped to improve the prediction of the response to cardiac resynchronization therapy.

New expectations for diastolic function assessment in transthoracic echocardiography based on a semi-automated computing of strain-volume loops.

AIMS: Early diagnosis of heart failure with preserved ejection fraction (HFpEF) by determination of diastolic dysfunction is challenging. Strain-volume loop (SVL) is a new tool to analyse left ventricular function. We propose a new semi-automated method to calculate SVL area and explore the added value of this index for diastolic function assessment. METHOD AND RESULTS: Fifty patients (25 amyloidosis, 25 HFpEF) were included in the study and compared with 25 healthy control subjects. Left ventricular ejection fraction was preserved and similar between groups. Classical indices of diastolic function were pathological in HFpEF and amyloidosis groups with greater left atrial volume index, greater mitral average E/e' ratio, faster tricuspid regurgitation (P < 0.0001 compared with controls). SVL analysis demonstrated a significant difference of the global area between groups, with the smaller area in amyloidosis group, the greater in controls and a mid-range value in HFpEF group (37 vs. 120 vs. 72 mL.%, respectively, P < 0.0001). Applying a linear discriminant analysis (LDA) classifier, results show a mean area under the curve of 0.91 for the comparison between HFpEF and amyloidosis groups. CONCLUSION: SVLs area is efficient to identify patients with a diastolic dysfunction. This new semi-automated tool is very promising for future development of automated diagnosis with machine-learning algorithms.

Reproducibility of reading echocardiographic parameters to assess severity of mitral regurgitation. Insights from a French multicentre study.

BACKGROUND: Poor reproducibility in assessment of mitral regurgitation (MR) has been reported. AIM: To investigate the robustness of echocardiographic MR assessment in 2019, based on improvements in technology and the skill of echocardiographists regarding MR quantification. METHODS: Reproducibility in parameters of MR severity and global rating were tested using transthoracic echocardiography in 25 consecutive patients independently analysed by 16 junior and senior cardiologists specialized in echocardiography (400 analyses per parameter). RESULTS: Overall interobserver agreement for mechanism definition, effective regurgitant orifice area (EROA) and regurgitant volume (RVol) was moderate, and was lower in secondary MR. Interobserver agreement was substantial for EROA [0.61, 95% confidence interval (CI) 0.45-0.75] and moderate for RVol with the PISA method (0.50, 95% CI 0.33-0.56) in senior physicians and was fair in junior physicians (0.33, 95% CI 0.19-0.51 and 0.36, 95% CI 0.36-0.43, respectively). Using a multiparametric approach, overall interobserver agreement for grading MR severity was fair (0.30), was slightly better in senior than in junior physicians (0.31 vs. 0.28, respectively) with substantial or almost perfect agreement more frequently observed in senior versus junior physicians (52% vs. 36%, respectively). CONCLUSION: Reproducible transthoracic echocardiography MR quantification remains challenging in 2019, despite the expected high skills of echocardiographers regarding MR at the time of dedicated percutaneous intervention. The multiparametric approach does not entirely alleviate the substantial dispersion in measurement of MR severity parameters, whereas reader experience seems to partially address the issue. Our study emphasizes the continuing need for multimodality imaging and education in the evaluation of MR among cardiologists.

Imaging predictors of response to cardiac resynchronization therapy: left ventricular work asymmetry by echocardiography and septal viability by cardiac magnetic resonance.

AIMS: Left ventricular (LV) failure in left bundle branch block is caused by loss of septal function and compensatory hyperfunction of the LV lateral wall (LW) which stimulates adverse remodelling. This study investigates if septal and LW function measured as myocardial work, alone and combined with assessment of septal viability, identifies responders to cardiac resynchronization therapy (CRT). METHODS AND RESULTS: In a prospective multicentre study of 200 CRT recipients, myocardial work was measured by pressure-strain analysis and viability by cardiac magnetic resonance (CMR) imaging (n = 125). CRT response was defined as ≥15% reduction in LV end-systolic volume after 6 months. Before CRT, septal work was markedly lower than LW work (P < 0.0001), and the difference was largest in CRT responders (P < 0.001). Work difference between septum and LW predicted CRT response with area under the curve (AUC) 0.77 (95% CI: 0.70-0.84) and was feasible in 98% of patients. In patients undergoing CMR, combining work difference and septal viability significantly increased AUC to 0.88 (95% CI: 0.81-0.95). This was superior to the predictive power of QRS morphology, QRS duration and the echocardiographic parameters septal flash, apical rocking, and systolic stretch index. Accuracy was similar for the subgroup of patients with QRS 120-150 ms as for the entire study group. Both work difference alone and work difference combined with septal viability predicted long-term survival without heart transplantation with hazard ratio 0.36 (95% CI: 0.18-0.74) and 0.21 (95% CI: 0.072-0.61), respectively. CONCLUSION: Assessment of myocardial work and septal viability identified CRT responders with high accuracy.

Prognostic Usefulness of Myocardial Work in Patients With Heart Failure and Reduced Ejection Fraction Treated by Sacubitril/Valsartan.

The noninvasive assessment of myocardial work (MW) by pressure-strain loops analysis (PSL) is a relative new tool for the evaluation of myocardial performance. Sacubitril/Valsartan is a treatment for heart failure with reduced ejection fraction (HFrEF) which has a spectacular effect on the reduction of cardiovascular events (major adverse cardiovascular events [MACEs]). This study aimed to evaluate the short- and medium-term effect of Sacubitril/Valsartan treatment on MW parameters and the prognostic value of MW in this specific group of patients. Seventy-nine patients with HFrEF (mean age: 66 ± 12 years; LV ejection fraction: 28% ± 9%) were prospectively included in the study and treated with Sacubitril/Valsartan. Echocardiographic examination was performed at baseline, and after 6- and 12-month of therapy with Sacubitril/Valsartan. Sacubitril/Valsartan significantly increased myocardial constructive work (CW) (1023 ± 449 vs 1424 ± 484 mm Hg%, p <0.0001) and myocardial work efficiency (WE) [87 (78to 90) vs 90 (86 to 95), p <0.0001]. During FU (2.6 ± 0.9 years), MACEs occurred in 13 (16%) patients. After correction for LV size, LV ejection fraction and WE, global myocardial constructive work (CW) was the only predictor of MACEs [hazard ratio [HR] 0.99 (0.99 to 1.00), p = 0.04]. A CW <910 mm Hg identified patients at particularly increase risk of MACEs [HR 11.09 (1.45 to 98.94), p = 0.002, log-rank test p <0.0001]. In conclusion, in patients with HFrEF who receive a comprehensive background beta-blocker and mineral-corticoid receptor antagonist therapy, Sacubitril/Valsartan induces a significant improvement of myocardial CW and WE. In this population, the estimation of CW before the initiation of Sacubitril/Valsartan allows the prediction of MACEs.

Model-based estimation of left ventricular pressure and myocardial work in aortic stenosis.

This paper proposes a model-based estimation of left ventricular (LV) pressure for the evaluation of constructive and wasted myocardial work of patients with aortic stenosis (AS). A model of the cardiovascular system is proposed, including descriptions of i) cardiac electrical activity, ii) elastance-based cardiac cavities, iii) systemic and pulmonary circulations and iv) heart valves. After a sensitivity analysis of model parameters, an identification strategy was implemented using a Monte-Carlo cross-validation approach. Parameter identification procedure consists in two steps for the estimation of LV pressures: step 1) from invasive, intraventricular measurements and step 2) from non-invasive data. The proposed approach was validated on data obtained from 12 patients with AS. The total relative errors between estimated and measured pressures were on average 11.9% and 12.27% and mean R2 were equal to 0.96 and 0.91, respectively for steps 1 and 2 of parameter identification strategy. Using LV pressures obtained from non-invasive measurements (step 2) and patient-specific simulations, Global Constructive (GCW), Wasted (GWW) myocardial Work and Global Work Efficiency (GWE) parameters were calculated. Correlations between measures and model-based estimations were 0.88, 0.80, 0.91 respectively for GCW, GWW and GWE. The main contributions concern the proposal of the parameter identification procedure, applied on an integrated cardiovascular model, able to reproduce LV pressure specifically to each AS patient, by non-invasive procedures, as well as a new method for the non-invasive estimation of constructive, wasted myocardial work and work efficiency in AS.

Association of estimated plasma volume status with hemodynamic and echocardiographic parameters.

BACKGROUND: Estimated plasma volume status (ePVS) has diagnostic and prognostic value in patients with heart failure (HF). However, it remains unclear which congestion markers (i.e., biological, imaging, and hemodynamic markers) are preferentially associated with ePVS. In addition, there is evidence of sex differences in both the hematopoietic process and myocardial structure/function. METHOD AND RESULTS: Patients with significant dyspnea (NYHA ≥ 2) underwent echocardiography and lung ultrasound within 4 h prior to cardiac catheterization. Patients were divided according to tertiles based on sex-specific ePVS thresholds calculated from hemoglobin and hematocrit measurements using Duarte's formula. Among the 78 included patients (median age 74.5 years; males 69.2%; HF 48.7%), median ePVS was 4.1 (percentile25-75 = 3.7-4.9) mL/g in males (N = 54) and 4.8 (4.4-5.3) mL/g in females (N = 24). Patients with the highest ePVS had more frequently HF, higher NT-proBNP, larger left atrial volume, and higher E/e' (all p values < 0.05), but no difference in inferior vena cava diameter or pulmonary congestion assessed by lung ultrasound (all p values > 0.10). In multivariable analysis, higher E/e' and lower diastolic blood pressure were significantly associated with increased ePVS. The association between ePVS and congestion variables was not sex-dependent except for left-ventricular end-diastolic pressure, which was only correlated with ePVS in females (Spearman Rho = 0.53, p < 0.01 in females and Spearman Rho = - 0.04, p = 0.76 in males; pinteraction = 0.08). CONCLUSION: ePVS is associated with E/e' regardless of sex, while only associated with invasively measured left-ventricular end-diastolic pressure in females. These results suggest that ePVS is preferably associated with left-sided hemodynamic markers of congestion.

Sensitivity Analysis of a Left Ventricle Model in the Context of Intraventricular Dyssynchrony.

The objective of the current study was to propose a sensitivity analysis of a 3D left ventricle model in order to assess the influence of parameters on myocardial mechanical dispersion. A finite element model of LV electro-mechanical activity was proposed and a screening method was used to evaluate the sensitivity of model parameters on the standard deviation of time to peak strain. Results highlight the importance of propagation parameters associated with septal and lateral segments activation. Simulated curves were compared to myocardial strains, obtained from echocardiography of one healthy subject and one patient diagnosed with intraventricular dyssynchrony and coronary artery disease. Results show a close match between simulation and clinical strains and illustrate the model ability to reproduce myocardial strains in the context of intraventricular dyssynchrony.