Towards an atrio-ventricular delay optimization assessed by a computer model for cardiac resynchronization therapy

In this paper, lumped-parameter models of the cardiovascular system, the cardiac electrical conduction system and a pacemaker are coupled to generate mitral ow pro les for di erent atrio-ventricular delay (AVD) con gurations, in the context of cardiac resynchronization therapy (CRT). First, we perform a local sensitivity analysis of left ventricular and left atrial parameters on mitral ow characteristics, namely E and A wave amplitude, mitral ow duration, and mitral ow time integral. Additionally, a global sensitivity analysis over all model parameters is presented to screen for the most relevant parameters that a ect the same mitral ow characteristics. Results provide insight on the in uence of left ventricle and atrium in uence on mitral ow pro les. This information will be useful for future parameter estimation of the model that could reproduce the mitral ow pro les and cardiovascular hemodynamics of patients undergoing AVD optimization during CRT.

[1]  J. Clark,et al.  A dynamic model of ventricular interaction and pericardial influence. , 1997, The American journal of physiology.

[2]  Guy Carrault,et al.  Model-based interpretation of cardiac beats by evolutionary algorithms: signal and model interaction , 2002, Artif. Intell. Medicine.

[3]  Erwan Donal,et al.  Atrioventricular delay optimization in cardiac resynchronization therapy assessed by a computer model , 2010, 2010 Computing in Cardiology.

[4]  Jean-Louis Coatrieux,et al.  Transvenous Path Finding in Cardiac Resynchronization Therapy , 2005, FIMH.

[5]  Albert Meijer,et al.  Correlation of echo-Doppler optimization of atrioventricular delay in cardiac resynchronization therapy with invasive hemodynamics in patients with heart failure secondary to ischemic or idiopathic dilated cardiomyopathy. , 2006, The American journal of cardiology.

[6]  Erwan Donal,et al.  Model-based analysis of myocardial strain data acquired by tissue Doppler imaging , 2008, Artif. Intell. Medicine.

[7]  Max D. Morris,et al.  Factorial sampling plans for preliminary computational experiments , 1991 .

[8]  R. Mark,et al.  Computational modeling of cardiovascular response to orthostatic stress. , 2002, Journal of applied physiology.

[9]  J. Geoffrey Chase,et al.  Simulation of cardiovascular system diseases by including the autonomic nervous system into a minimal model , 2007, Comput. Methods Programs Biomed..

[10]  Jiang Ding,et al.  A Prospective Comparison of AV Delay Programming Methods for Hemodynamic Optimization during Cardiac Resynchronization Therapy , 2007, Journal of cardiovascular electrophysiology.

[11]  L. Padeletti,et al.  Determination of the optimal atrioventricular delay in DDD pacing. Comparison between echo and peak endocardial acceleration measurements. , 1999, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[12]  Thomas Lavergne,et al.  Effects of multisite biventricular pacing in patients with heart failure and intraventricular conduction delay , 2001 .

[13]  A. Cipriano,et al.  Estimation of cardiac function from computer analysis of the arterial pressure waveform , 1998, IEEE Transactions on Biomedical Engineering.

[14]  F. Ghorbel,et al.  A human cardiopulmonary system model applied to the analysis of the Valsalva maneuver. , 2001, American journal of physiology. Heart and circulatory physiology.

[15]  A. Hughes,et al.  Haemodynamic effects of changes in atrioventricular and interventricular delay in cardiac resynchronisation therapy show a consistent pattern: analysis of shape, magnitude and relative importance of atrioventricular and interventricular delay , 2006, Heart.

[16]  Ben Vandermeer,et al.  Cardiac resynchronization therapy for patients with left ventricular systolic dysfunction: a systematic review. , 2007, JAMA.