Scalable and Accurate ECG Simulation for Reaction-Diffusion Models of the Human Heart

International audienceRealistic electrocardiogram (ECG) simulation with numerical models is important for research linking cellular and molecular physiology to clinically observable signals, and crucial for patient tailoring of numerical heart models. However, ECG simulation with a realistic torso model is computationally much harder than simulation of cardiac activity itself, so that many studies with sophisticated heart models have resorted to crude approximations of the ECG. This paper shows how the classical concept of electrocardiographic lead fields can be used for an ECG simulation method that matches the realism of modern heart models. The accuracy and resource requirements were compared to those of a full-torso solution for the potential and scaling was tested up to 14,336 cores with a heart model consisting of 11 million nodes. Reference ECGs were computed on a 3.3 billion-node heart-torso mesh at 0.2 mm resolution. The results show that the lead-field method is more efficient than a full-torso solution when the number of simulated samples is larger than the number of computed ECG leads. While the initial computation of the lead fields remains a hard and poorly scalable problem, the ECG computation itself scales almost perfectly and, even for several hundreds of ECG leads, takes much less time than the underlying simulation of cardiac activity

Prediction of the Exit Site of Ventricular Tachycardia Based on Different ECG Lead Systems

The effectiveness of a computer-based method forlocalization of arrhythmia exit sites was studied.The proposed algorithm works on any set of 3 or moreECG leads. The QRS complex integral of an ectopic beatis reduced to principal components treated as coordinatesof the exit site in ECG space and then projected to realspace by a linear transformation. The accuracy of themethod was tested on 5 patient-tailored models of humanheart and torso. For each model ~500 simulations wererun, each for different stimulus location. All locationswere then estimated from simulated surface ECGs andmethod accuracy was investigated.The algorithm performed better for the left ventriclethan for the right ventricle. The group mean absolute andrelative (to a neighboring stimulation site) localizationerrors in millimeters were: 11.5 (SD=2.5), 2.6 (SD=0.5)for the 252-lead ECG; 12.2 (SD=2.7), 2.7 (SD=0.5) forthe 12-lead ECG; and 11.7 (SD=2.4), 2.7 (SD=0.5) forthe Frank VCG.This study suggest that the proposed method canpredict exit sites with a precision in the order of acentimeter. Low values of error for neighbouringactivation sites suggest opportunity for algorithmimprovement. The use of vectorcardiographic leads isenough to obtain a precision comparable to a 252-leadECG