Computerized optimization of biventricular pacing using body surface potential map

Abstract

An improvement of biventricular pacing (BVP) could be possible by detecting the patient specific optimal pacemaker parameters. Body surface potential map (BSPM) is used to obtain the electrophysiology and pathology of an individual patient non-invasively. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. The computer model of the heart is used to simulate the dyssynchrony of the ventricles and myocardial infarction (MI). Cardiac electrophysiology is simulated with ten Tusscher cell model, while excitation propagation is intended with adaptive cellular automaton at physiological and pathological conduction stages. The optimal electrode configurations are identified by minimizing the QRS duration error of healthy and pathology case with/without pacing between pre and post-implantation. Afterwards, the simulated ECGs for optimal pacing are compared to the post implantation clinically measured ECGs. The optimal electrode positions found by simulation are comparable to the ones meausured in hospital. The QRS duration reduction error between measured and simulated 12 ECG signals are similar with a constant offset of 15 ms. The personalized model present in this research is an effective tool for therapy planning of BVP in patients with congestive heart failure.

The Right Ventricular Septum Presents the Optimum Site for Maximal Electrical Separation During Left Ventricular Pacing

“…However, we speculate that in patients with LBBB, the conduction wavefront from the LV lead would be unable to traverse the interventricular septum because of LBBB; therefore, travel in an epicardial manner would dominate and, physically, the apex and RVOT would meet the excitation wave sooner than the mid‐septum. Miri et al 17 demonstrated this in a computer generated 3D model of the human heart adapted for investigation of optimal site for biventricular pacing. They used MRI and detailed ECG data from 10 patients and modeled differing electrode positions to obtain optimum synchrony.…”