DOI: 10.5281/zenodo.12570032
title: Modelling and simulation of conduction delays in the ventricular conduction system in human post myocardial infarction
title: Computational framework for cardiac simulations on MonoAlg3D

description: This dataset contains the necessary files to run biophysically detailed simulations of human ventricular electrophysiology in myocardial infarction conditions on the solver MonoAlg3D. 

Specifically, the present framework allows modelling and simulation of anteroseptal myocardial infarction co-existing with conduction delays in the ventricular conduction system (VCS), namely in the Purkinje network and/or the bundle branches. The simulations reproduce the electrocardiographic signature of myocardial infarction patients with conduction delays, such as left/right bundle branch block (LBBB, RBBB).

The dataset includes multiple scenarios presenting variability in the conduction delay regions in the VCS, considering different locations, sizes, the inclusion of a bundle branch or the overlap with the myocardial infarction region.

Contents:



simulation_scripts: this folder contains the simulation files required to run an extensive collection of human myocardial scenario scenarios with variable conduction delay regions in the ventricular conduction system

geometries: 3 different ventricular meshes are included (healthy, small infarction and large infarction), which can be combined with any VCS tree. These files must be stored in a directory accessible by MonoAlg3D. Additionally, this folder contains the Matlab files used to create the different VCS trees from the original healthy tree.


To run the simulations, the solver MonoAlg3D is required, and the files in this repository need to be incorporated into the MonoAlg3D installation directory. As a result, electrical potential in the ventricular tissue and the simulated electrocardiographic signal will be computed. MonoAlg3D can be installed in Linux operating systems and computational performance is drastically enhanced in computers fitted with an Nvidia GPU.

The figure below showcases the set of scenarios in the dataset.

This work should be cited via the following references:









Leto Luana Riebel, Zhinuo Jenny Wang, Hector Martinez-Navarro, Cristian Trovato, Julia Camps, Lucas Arantes Berg, Xin Zhou, Ruben Doste, Rafael Sachetto Oliveira, Rodrigo Weber dos Santos, Jacopo Biasetti, Blanca Rodriguez

In Silico Evaluation of Cell Therapy in Acute versus Chronic Infarction: Role of Automaticity, Heterogeneity and Purkinje in Human


bioRxiv 2023.12.11.570780; doi: https://doi.org/10.1101/2023.12.11.570780

 



Camps J, Berg LA, Wang ZJ, Sebastian R, Riebel LL, Doste R, Zhou X, Sachetto R, Coleman J, Lawson B, Grau V, Burrage K, Bueno-Orovio A, Weber Dos Santos R, Rodriguez B.Digital twinning of the human ventricular activation sequence to Clinical 12-lead ECGs and magnetic resonance imaging using realistic Purkinje networks for in silico clinical trials. Med Image Anal. 2024 May;94:103108. doi: 10.1016/j.media.2024.103108. Epub 2024 Feb 28. PMID: 38447244.

 

Oliveira RS, Rocha BM, Burgarelli D, Meira Jr W, Constantinides C, dos Santos RW. Performance evaluation of GPU parallelization, space‐time adaptive algorithms, and their combination for simulating cardiac electrophysiology. Int J Numer Meth Biomed Engng. 2018;34:e2913. https://doi.org/10.1002/cnm.2913