Patient-specific generation of the Purkinje network driven by clinical measurements

The propagation of the electrical signal in the Purkinje network is the starting point for the activation of the muscular cells leading to the contraction of the heart. In the computational models describing the electrical activity of the ventricle is therefore important to account for the Purkinje fibers. Until now, the inclusion of such fibers has been obtained by using surrogates such as space-dependent conduction properties or by generating a network based only on an a priori anatomical knowledge. Aim of this work was to propose a new method for the generation of the Purkinje network by using clinical measures of the activation times on the endocardium allowing to generate a patient-specific network. To assess the accuracy of the proposed method we compared its accuracy with that of other strategies proposed so far in the literature for three cases with a normal electrical propagation. The results showed that with the proposed method we were able to reduce the errors by at least 25% with respect to the best of the other strategies. This highlighted the reliability of the proposed method and the importance of including a patientspecific Purkinje network in computational models.