Model study of influence of extracardial factors on the inverse localization of preexcitation sites.
Inverse solution techniques are expected to help in noninvasive localization of ventricular preexcitation sites. The influence of selected extracardial factors on the accuracy of the inverse localization of the initial activation sites was studied on a model. Each of 8 simulated activation sequences was initiated in a different single starting point at the atrioventricular ring. Corresponding ecg potentials on the surface of a realistic model of inhomogeneous torso were used for the inverse localization procedure. A multiple dipole (MD) model of the cardiac generator composed of 39 segmental dipoles was used in the inverse computations. As it was shown in a previous study, the method was able to localize the 8 starting points even if a simplified torso model and a limited number of leads was used. In this study, influence of another two factors was evaluated: inaccuracy of location of the MD generator and presence of noise in surface potentials. Several shifts and rotations of the heart generator relative to its exact position were modeled. When the mean deviation of starting points was about 1 cm the mean localization error varied from 0.5 cm up to 1.0 cm for complete model data--198 surface potentials and a torso model including lungs and ventricular cavities. When a noise with uniform and Gaussian distribution was added to the surface potentials, the use of averaged body surface potentials significantly improved accuracy and stability of the inverse solution. For root mean square value of noise sigma = 14 microV the mean error of localization was 0.9 cm. For higher noise (sigma = 30 microV) the results were substantially deteriorated. The influence of a noise was studied on complete model data. (Tab. 3, Fig. 5. Ref. 6.)
Turzová
M
M
Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia. umerturz@savba.sk
Tysler
M
M
Svehlíková
J
J
Tinová
M
M
D018780:Body Surface Potential Mapping; D003198:Computer Simulation; D006801:Humans