Key result
Including computer-simulated activation maps as 50% of the training set for statistical estimation worsened the mean correlation coefficient only from 0.93 to 0.92 and localization error from 9.65 to 12.14 mm.
Why the study?
Does including cardiac simulation results in the training set maintain the accuracy of source localization for focal epicardial arrhythmias?
Does including cardiac simulation results in the training set maintain the accuracy of source localization for focal epicardial arrhythmias?
Including cardiac simulation results in the training set for statistical estimation is a feasible method for source localization of focal epicardial arrhythmias, potentially reducing the need for open-chest data acquisition.
Accuracy largely preserved with 50% simulated maps in animals; leaves open clinical translation for focal arrhythmia localization.
Mapping of the epicardium is possible with the usage of multielectrode venous catheters; however, most of epicardial surface is still inaccessible. To overcome this problem a method called statistical estimation was proposed, in which the relationship between catheter measurements and the remaining sites are created from previously obtained high resolution maps, called the training set. Thus, there is a need for the acquisition of high resolution epicardial maps from patients during open-chest procedures. In this study we hypothesize that epicardial maps created from computer simulations might be used in combination with maps from patients, so that the need for data acquisition during open-chest procedures would be reduced. We used high-resolution epicardial activation maps acquired from 13 dog heart experiments, 470 maps from 12 experiments (training set) and 50 maps from a separate experiment (test set). Hearts were paced from sites regularly distributed over the epicardium. The simulations of focal arrhythmias originating from epicardium were performed using a modified version of FitzHugh-Nagumo cardiac model within the ventricles of the Auckland canine heart model. We registered the experimental and simulation heart geometries using iterative closest-points algorithm and procrustes method. We started simulations from sites that corresponded to the pacing sites on the experimental geometry and created a simulated activation map database (470 maps) and compared the simulation results with the corresponding experimental maps. Finally, we performed the statistical estimation on the test set by adjusting the content of the training set in such a way that simulated maps constituted 100%, 75%, 50%, 25%, and 0% of the training set. Mean correlation coefficient (CC) between the simulated and experimental activation maps was 0.88. Mean CC and the arrhythmia source localization error worsened only from 0.93 to 0.92, and 9.65 mm to 12.14 mm when simulated activation maps constituted 50% of the training set. This study showed the feasibility of including cardiac simulation results in the training set for source localization of focal epicardial arrhythmias using statistical estimation.
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Cunedioǧlu et al. (2008) studied Focal epicardial arrhythmias (n=13). Cardiac simulation results in the training set vs. Experimental maps only was evaluated on Mean correlation coefficient (CC) and arrhythmia source localization error. Including computer-simulated activation maps as 50% of the training set for statistical estimation worsened the mean correlation coefficient only from 0.93 to 0.92 and localization error from 9.65 to 12.14 mm.
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