Integration of different cardiac electrophysiological models into a single simulation pipeline

2012

Clinical translation of computational models of the heart has been hampered by the absence of complete and rigorous technical and clinical validation, as well as benchmarking of the developed tools. To address this issue, a dataset containing the cardiac anatomy and fibre orientations from magnetic resonance images (MRI), as well as epicardial transmembrane potentials from optical mapping acquired on ex-vivo porcine hearts, have previously been made available to the community. Image processing techniques were developed to integrate MRI images with electrical information. Different models were tested and compared with the integrated data1, including: i) a new methodology to customize and reg…

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

2018

Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the “Automatic Cardiac Diagnosis Challenge” dataset (ACDC), the largest publicly available and fully annotated dataset for the purpose of cardiac MRI (CMR) assessment. The dataset contains data from 150 multi-equipments CMRI recordings with reference measurements and classification from two medical experts. The overarching objective of this paper is to measure how f…

OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project

2011

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level b…

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

2016

The specialised conducting tissues present in the ventricles are responsible for the fast distribution of the electrical impulse from the atrio-ventricular node to regions in the subendocardial myocardium. Characterisation of anatomical features of the specialised conducting tissues in the ventricles is highly challenging, in particular its most distal section, which is connected to the working myocardium via Purkinje-myocardial junctions. The goal of this work is to characterise the architecture of the distal section of the Purkinje network by differentiating Purkinje cells from surrounding tissue, performing a segmentation of Purkinje fibres at cellular scale, and mathematically describin…

Modelización computacional cardiaca

2020

[EN] Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's response. Within this framework, the Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective of the VHeart-SN network is the development of an integrated, modular and multiscale multiphysical computational model of the heart. This general objective is addressed through the following spe…

Estimation of Electrical Pathways Finding Minimal Cost Paths from Electro-Anatomical Mapping of the Left Ventricle

2014

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, electro-anatomical mappings of patient-specific activation times on the left ventricle surface can be estimated, providing crucial information to the clinicians for guiding cardiac treatment. However, some electrical pathways of particular interest such as Purkinje or still viable conduction channels are difficult to interpret in these maps. We present here a novel method to find some of these electrical pathways using minimal cost paths computations on surface maps. Experiments to validate the propos…

In silico pace-mapping: prediction of left vs. right outflow tract origin in idiopathic ventricular arrhythmias with patient-specific electrophysiolo…

2019

Abstract Aims A pre-operative non-invasive identification of the site of origin (SOO) of outflow tract ventricular arrhythmias (OTVAs) is important to properly plan radiofrequency ablation procedures. Although some algorithms based on electrocardiograms (ECGs) have been developed to predict left vs. right ventricular origins, their accuracy is still limited, especially in complex anatomies. The aim of this work is to use patient-specific electrophysiological simulations of the heart to predict the SOO in OTVA patients. Methods and results An in silico pace-mapping procedure was designed and used on 11 heart geometries, generating for each case simulated ECGs from 12 clinically plausible SOO…

Sensitivity analysis of mesh warping and subsampling strategies for generating large scale electrophysiological simulation data

2011

The analysis of large-scale simulation data from virtual populations can be effective to gain computational insight into disease mechanisms and treatment strategies, which can serve for generating hypotheses for and focusing subsequent clinical trials. This can be instrumental in shortening the critical path in medical product development and more cost-effective clinical trials. A previously published pipeline established point correspondence among volumetric meshes to enable meaningful statistics on cardiac electrophysiological simulations on the anatomical distribution of a large-scale virtual population. Thin Plate Splines (TPS), derived from surface deformations, were used to warp a tem…

Personalization of Fast Conduction Purkinje System in Eikonal-Based Electrophysiological Models with Optical Mapping Data

2010

We present a pipeline for the personalization of model-based Purkinje fast conduction system using fast electrophysiological models and optical mapping data acquired from ex-vivo porcine hearts. The regional density of the Purkinje terminals as well as the latest endocardial activation time were the parameters personalized in an iterative procedure maximizing the similarity between the outcome of the electrophysiological simulations and measurements obtained from optical mapping data. We used a fast wave-front Eikonal-based electrophysiological model that generated the depolarization time maps that were subsequently compared with measurements at each iteration of the optimization stage. The…

Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardi…

2011

International audience; Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a per…

Quasi-Conformal Technique for Integrating and Validating Myocardial Tissue Characterization in MRI with Ex-Vivo Human Histological Data

2017

Ventricular tachycardia caused by a circuit of re-entry is one of the most critical arrhythmias. It is usually related with heterogeneous scar regions where slow velocity of conduction tissue is mixed with non-conductive tissue, creating pathways (CC) responsible for the tachycardia. Pre-operative DE-MRI can provide information on myocardial tissue viability and then improve therapy planning. However, the current DE-MRI resolution is not sufficient for identifying small CCs and therefore they have to be identified during the intervention, which requires considerable operator experience. In this work, we studied the relationship of histological data (with 10 \(\mu \)m resolution), with in-vi…

Effect of Scar Development on Fast Electrophysiological Models of the Human Heart: In-Silico Study on Atlas-Based Virtual Populations

2011

The main goal of this work is to study the effect of scar development in the electrophysiological function of the human left ventricle by statistically analyzing large-scale simulation data including hypertrophic and dilated hearts. Electrophysiological simulations are obtained by solving the classical Eikonal equation in both the ventricular tissue and a customized Purkinje system. This Purkinje system is obtained assuming a geodesic rule to connect different Purkinje-myocardial junctions into a tree-like structure. Infarction shape and function is modeled with taking into account the occlusion in coronary arteries. Infarct, core and border zones of the scar are estimated by calculating bl…

A rule‐based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts

2019

Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the endocardium of the right ventricle, the inter…

87Non-invasive virtual prediction of site of origin in outflow tract ventricular arrhythmias with a patient-specific computational model

2017

A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias

2017

Comunicació presentada a: FIMH 2017 9th International Conference, celebrada a Toronto, Canadà, de l'11 al 13 de juny de 2017. Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomi- cal models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In conse- quence, fiber information from RBM does not match with histological data in other areas of the heart, having a negative impact in cardiac simulations beyond the LV. In this work, we present a RBM where fiber orientation is separately mode…

Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data

2022

Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables b…

Atlas construction and image analysis using statistical cardiac models

2010

International audience; This paper presents a brief overview of current trends in the construction of population and multi-modal heart atlases in our group and their application to atlas-based cardiac image analysis. The technical challenges around the construction of these atlases are organized around two main axes: groupwise image registration of anatomical, motion and fiber images and construction of statistical shape models. Application-wise, this paper focuses on the extraction of atlas-based biomarkers for the detection of local shape or motion abnormalities, addressing several cardiac applications where the extracted information is used to study and grade different pathologies. The p…

Modelización computacional cardiaca

2020

Resumen Las enfermedades cardiovasculares tienen en la actualidad un gran impacto social y economico y constituyen una de las principales causas de mortalidad y morbilidad. Los modelos computacionales personalizados del corazon estan demostrando ser utiles tanto para ayudar a comprender los mecanismos subyacentes a las patologias cardiacas como para optimizar su tratamiento prediciendo la respuesta del paciente. En este contexto, se ha puesto en marcha la Red Espanola de Investigacion en Modelizacion Computacional Cardiaca (V-Heart SN). El objetivo general de V-Heart SN es el desarrollo de un modelo computacional multifisico y multiescala integrado del corazon. Este objetivo general se abor…

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

2015

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 activati…

Influence of geometric variations on LV activation times: A study on an atlas-based virtual population

2010

We present the fully automated pipeline we have developed to obtain electrophysiological simulations of the heart on a large atlas-based virtual population. This virtual population was generated from a statistical model of left ventricular geometry, represented by a surface model. Correspondence between tetrahedralized volumetric meshes was obtained using Thin Plate Spline warps. Simulations are based on the fast solving of Eikonal equations, and stimulation sites correspond to physiological activation. We report variations of total activation time introduced by geometry, as well as variations in the location of last activation. The obtained results suggest that the total activation time ha…

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

2022

In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automatize the process and improve generalization, but their performance is hampered by the lack of large enough OTVA databases. We propose the use of detailed electrophysiological simulations of OTVAs to train a machine learning classification model to predict the ventricular origin of the SOO of ectopic beats. We generated a synthetic database of 12-l…