Background Ventricular tachycardia with structural heart disease is dependent on re-entry within scar regions. We set out to assess the VT circuit in greater detail than has hitherto been possible, using ultra highdensity mapping. Methods All ultra high-density mapping guided ventricular tachycardia ablation cases from six high-volume European centres were assessed. Maps were analysed offline to generate activation maps of tachycardia circuits. Topography, conduction velocity and voltage of the VT circuit were analyzed in complete maps. Results Thirty-six tachycardias in 31 patients were identified, 29 male and 27 ischaemic. VT circuits and isthmuses were complex, eleven were single-loop and 25 double-loop; three had two entrances, five had two exits and 15 had dead ends of activation. Isthmuses were defined by barriers which included anatomical obstacles, lines of complete block and slow conduction (in 27/36 isthmuses). Median conduction velocity was 0.08m/s in entrance zones, 0.29m/s in isthmus regions (p<0.001), and 0.11m/s in exit regions (p=0.002). Median local voltage in the isthmus was 0.12mV during tachycardia and 0.06mV in paced/sinus rhythm. Two circuits were identifiable in five patients. The median timing of activation was 16% of diastole in entrances, 47% in the mid isthmus, and 77% in exits. Conclusions VT circuits identified were complex, some of them having multiple entrances, exits and dead ends. The barriers to conduction in the isthmus appear to be partly functional in 75% of circuits. 3 Conduction velocity in the VT isthmus slowed at isthmus entrances and exits, when compared with the mid isthmus. Isthmus voltage is often higher in VT than in sinus or paced rhythms.
This study shows that localized structural alterations underlie a significant subset of previously unexplained sudden cardiac death. In the other subset, Purkinje electrical pathology seems as a dominant mechanism.
Mark Potse, Corentin Dallet, et al.. Effect of the torso conductivity heterogeneities on the ECGI inverse problem solution.Abstract-The effect of torso conductivity heterogeneities on the electrocardiographic imaging (ECGI) inverse problem solution is still subject of debate. In this study we present a method to assess the effect of these heterogeneities. We use an anatomical model containing the heart the lungs the bones and the torso surfaces. We use the bidomain model and we solve it using finite element methods in order to generate in silico data taking into account the torso heterogeneities. We add different noise levels on the body surface potentials and we solve the inverse problem for both homogenous and heterogeneous torso conductivities. We analyse the reconstructed solution using the relative error and the correlation coefficient.
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