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

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Abstract

The propagation of the electrical signal in the Purkinje network is the starting point for the activation of the ventricular muscular cells leading to the contraction of the ventricle. 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 either by using surrogates such as space-dependent conduction properties or by generating a network based on an a priori anatomical knowledge. The aim of this work was to propose a new method for the generation of the Purkinje network using clinical measures of the activation times on the endocardium related to a normal electrical propagation, allowing to generate a patient-specific network. The measures were acquired by means of the EnSite NavX system. This system allows to measure for each point of the ventricular endocardium the time at which the activation front, that spreads through the ventricle, has reached the subjacent muscle. We compared the accuracy of the proposed method with the one of other strategies proposed so far in the literature for three subjects with a normal electrical propagation. The results showed that with our method we were able to reduce the absolute errors, intended as the difference between the measured and the computed data, by a factor in the range 9–25 %, with respect to the best of the other strategies. This highlighted the reliability of the proposed method and the importance of including a patient-specific Purkinje network in computational models.

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Abbreviations

PF:

Purkinje fibers

CCS:

Cardiac conduction system

PMJ:

Purkinje muscular junctions

MRI:

Magnetic resonance imaging

3D:

Three dimensional

AV:

Atrioventricular

ECG:

Electrocardiogram

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Acknowledgments

The present study has been funded by Fondazione Cassa di Risparmio di Trento e Rovereto (CARITRO) within the project “Numerical modelling of the electrical activity of the heart for the study of the ventricular dyssynchrony”. The authors would like also to acknowledge St. Jude Medical Inc. and in particular Eng Indiani for their helpful assistance for the description of the technical characteristics of the NavX system.

Conflict of interest

We state that there are no disclosures.

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Authors and Affiliations

  1. Dipartimento di Ingegneria, Università di Bergamo, Viale Marconi 5, 24044, Dalmine, BG, Italy

    Christian Vergara

  2. MOX, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20131, Milan, Italy

    Simone Palamara, Fabio Nobile, Elena Faggiano & Alfio Quarteroni

  3. Divisione di Cardiologia, Ospedale S. Maria del Carmine, Corso Verona, 4, 38068, Rovereto, TN, Italy

    Domenico Catanzariti, Cesarino Pangrazzi, Massimiliano Maines & Giuseppe Vergara

  4. MATHICSE-CSQI, École Polytechnique Fédérale de Lausanne, SB SMA-GE, MA B2 444 (Bâtiment MA), Station 8, 1015, Lausanne, Switzerland

    Fabio Nobile & Alfio Quarteroni

  5. LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20131, Milan, Italy

    Elena Faggiano

  6. U.O. di Radiologia di Borgo-Pergine, Viale Vicenza 9, 38051, Borgo Valsugana, TN, Italy

    Maurizio Centonze

Authors
  1. Christian Vergara
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  2. Simone Palamara
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  3. Domenico Catanzariti
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  4. Fabio Nobile
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  5. Elena Faggiano
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  6. Cesarino Pangrazzi
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  7. Maurizio Centonze
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  8. Massimiliano Maines
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  9. Alfio Quarteroni
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  10. Giuseppe Vergara
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Corresponding author

Correspondence to Christian Vergara.

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Vergara, C., Palamara, S., Catanzariti, D. et al. Patient-specific generation of the Purkinje network driven by clinical measurements of a normal propagation. Med Biol Eng Comput 52, 813–826 (2014). https://doi.org/10.1007/s11517-014-1183-5

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  • DOI: https://doi.org/10.1007/s11517-014-1183-5

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