Literature DB >> 26073786

Estimation of Purkinje trees from electro-anatomical mapping of the left ventricle using minimal cost geodesics.

Rubén Cárdenes1, Rafael Sebastian2, David Soto-Iglesias3, Antonio Berruezo4, Oscar Camara3.   

Abstract

The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, patient-specific activation times on ventricular chambers can be estimated from electro-anatomical maps, providing crucial information to clinicians for guiding cardiac radio-frequency ablation treatment. However, some relevant electrical pathways such as those of the Purkinje system are very difficult to interpret from these maps due to sparsity of data and the limited spatial resolution of the system. We present here a novel method to estimate these fast electrical pathways from the local activations maps (LATs) obtained from electro-anatomical maps. The location of Purkinje-myocardial junctions (PMJs) is estimated considering them as critical points of a distance map defined by the activation maps, and then minimal cost geodesic paths are computed on the ventricular surface between the detected junctions. Experiments to validate the proposed method have been carried out in simplified and realistic simulated data, showing good performance on recovering the main characteristics of simulated Purkinje networks (e.g. PMJs). A feasibility study with real cases of fascicular VT was also performed, showing promising results.
Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cardiac arrhythmias; Electro-anatomical mapping; Fascicular ventricular tachycardia; Fast marching; Minimal cost geodesic paths; Purkinje system; Singular points

Mesh:

Year:  2015        PMID: 26073786     DOI: 10.1016/j.media.2015.05.007

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  7 in total

1.  An Inverse Eikonal Method for Identifying Ventricular Activation Sequences from Epicardial Activation Maps.

Authors:  Thomas Grandits; Karli Gillette; Aurel Neic; Jason Bayer; Edward Vigmond; Thomas Pock; Gernot Plank
Journal:  J Comput Phys       Date:  2020-07-03       Impact factor: 3.553

2.  Analysis of Microstructure of the Cardiac Conduction System Based on Three-Dimensional Confocal Microscopy.

Authors:  Daniel Romero; Oscar Camara; Frank Sachse; Rafael Sebastian
Journal:  PLoS One       Date:  2016-10-07       Impact factor: 3.240

3.  Human Purkinje in silico model enables mechanistic investigations into automaticity and pro-arrhythmic abnormalities.

Authors:  Cristian Trovato; Elisa Passini; Norbert Nagy; András Varró; Najah Abi-Gerges; Stefano Severi; Blanca Rodriguez
Journal:  J Mol Cell Cardiol       Date:  2020-04-03       Impact factor: 5.000

4.  A rule-based method for predicting the electrical activation of the heart with cardiac resynchronization therapy from non-invasive clinical data.

Authors:  A W C Lee; U C Nguyen; O Razeghi; J Gould; B S Sidhu; B Sieniewicz; J Behar; M Mafi-Rad; G Plank; F W Prinzen; C A Rinaldi; K Vernooy; S Niederer
Journal:  Med Image Anal       Date:  2019-07-05       Impact factor: 8.545

5.  Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology.

Authors:  Karli Gillette; Matthias A F Gsell; Julien Bouyssier; Anton J Prassl; Aurel Neic; Edward J Vigmond; Gernot Plank
Journal:  Ann Biomed Eng       Date:  2021-08-24       Impact factor: 3.934

6.  Graph-based homogenisation for modelling cardiac fibrosis.

Authors:  Megan E Farquhar; Kevin Burrage; Rodrigo Weber Dos Santos; Alfonso Bueno-Orovio; Brodie A J Lawson
Journal:  J Comput Phys       Date:  2022-06-15       Impact factor: 4.645

7.  Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias.

Authors:  Ruben Doste; Miguel Lozano; Guillermo Jimenez-Perez; Lluis Mont; Antonio Berruezo; Diego Penela; Oscar Camara; Rafael Sebastian
Journal:  Front Physiol       Date:  2022-08-12       Impact factor: 4.755

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.