Usage of Cardiac Simulation Results in Source Localization of Focal Epicardial Arrhythmias using Statistical Estimation


Cunedioglu U., Baysoy E., Yilmaz B.

30th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, Vancouver, Canada, 20 - 24 August 2008, pp.589-590 identifier identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/iembs.2008.4649221
  • City: Vancouver
  • Country: Canada
  • Page Numbers: pp.589-590

Abstract

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 mill 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.