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.

Parametric analysis of an integrated cardio-respiratory model in preterm newborns during apnea.

The analysis of the complex interactions involved in the acute physiological response to apnea-bradycardia events in preterm newborns remains a challenging task. This paper presents a novel integrated model of cardio-respiratory interactions, adapted to preterm newborns. A sensitivity analysis, based Morris' screening method, was applied to study the effects of physiological parameters on heart rate and desaturation, during the simulation of a 15-seconds apnea-bradycardia episode. The most sensitive parameters are associated with fundamental, integrative physiological mechanisms involving: (i) respiratory mechanics (intermediate airways and lung compliance), (ii) fraction of inspired oxygen, (iii) metabolic rates (oxygen consumption rate), (iv) heart rate regulation and (v) chemoreflex (gain). Results highlight the relevant influence of physiological variables, involved in preterm apnea-bradycardia events.

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.

Quantification of Neural Conduction Block on the Rat Sciatic Nerve based on EMG Response.

Neural conduction block performed by balanced-charge kilohertz frequency alternating currents (KHFAC) has been identified as a potential technique for therapy delivery in different clinical setups. The underlying mechanisms that contribute to this phenomenon have been studied through computational models and animal experiments. However, the optimal stimulation parameters to achieve axonal conduction block are difficult to define, since they depend on the species, the nerve being targeted, as well as the technical and experimental setup. This study proposes an experimental setup along with an original data processing approach for the quantification of the effectiveness of neural conduction block. Experiments were performed on the sciatic nerve of two Sprague-Dawley rats, by evaluating different groups of stimulation parameters with varying amplitudes and frequencies, ranging from 1 to 10 mA and from 2 to 10 kHz, respectively. Results suggest that the effectiveness of axonal conduction block strongly depends on the selection of the stimulation parameters. In this work, more effective blockages were achieved for frequencies around 4 kHz and within an approximate amplitude range of 2 to 8 mA.

Global Sensitivity Analysis of a Cardiovascular Model for the Study of the Autonomic Response to Head-up Tilt Testing.

This paper proposes the integration and analysis of a mathematical model representing the cardiovascular system and its short-term autonomic response to head-up tilt (HUT) testing. A Latin Hypercube Sampling method was applied to design an optimal experimental space, including 19 model parameters coming from the cardiovascular and baroreflex control systems. Then, a global, variance-based sensitivity analysis was applied to quantity the effects of these parameters on heart rate and systolic blood pressure. Results highlight the relevant influence of the intrinsic heart rate and the sympathetic and parasympathetic baroreflex gains on heart rate regulation, as well as the impact of left ventricle diastolic parameters on systolic blood pressure. Moreover, a significant effect of right ventricle dynamics on blood pressure was noted. These results provide valuable information for the application of such an integrated model for the analysis of the autonomic mechanisms regulating the cardiovascular response induced by postural changes. In particular, they suggest a convenient set of parameters to be identified in a subject-specific manner.