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Start Over Author "Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC" Publisher computing in cardiology
6 results on '"Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC"'

1. Segmentation Uncertainty Quantification in Cardiac Propagation Models

Author

'Jess Tate, Nejib Zemzemi, Shireen Elhabian, Beata Ondrusova, Machteld Boonstra, Peter van Dam, Dana Brooks, Akil Narayan, Rob MacLeod\\', Scientific Computing and Imaging Institute (SCI Institute), University of Utah, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux], Slovak University of Technology in Bratislava, University Medical Center [Utrecht], and Northeastern University [Boston]

Subjects
[SPI]Engineering Sciences [physics]
Abstract

International audience; A key part of patient-specific cardiac simulations is segmentation, yet the impact of this subjective and errorprone process hasn't been quantified in most simulation pipelines. In this study we quantify the dependence of a cardiac propagation model on from segmentation variability. We used statistical shape modeling and polynomial Chaos (PC) to capture segmentation variability dependence and applied its affects to a propagation model. We evaluated the predicted local activation times (LATs) an body surface potentials (BSPs) from two modeling pipelines: an EIkonal propagation model and a surfacebased fastest route model. The predicted uncertainty due to segmentation shape variability was distributed near the base of the heart and near high amplitude torso potential regions. Our results suggest that modeling pipelines may have to accommodate segmentation errors if regions of interest correspond to high segmentation error. Further, even small errors could proliferate if modeling results are used to to feed further computations, such as ECGI.

Published
2022

2. The Effect of Segmentation Variability in Forward ECG Simulation

Author

'Beata Ondrusova, Machteld Boonstra, Jana Svehlikova, Dana Brooks, Peter van Dam, Ali Rababah, Akil Narayan, Rob MacLeod, Nejib Zemzemi, Jess Tate\\', Institute of Measurement Science (IMS), Slovak Academy of Sciences (SAS), University Medical Center [Utrecht], Slovak University of Technology in Bratislava, Northeastern University [Boston], Jordanian Royal Medical Services, Scientific Computing and Imaging Institute (SCI Institute), University of Utah, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, and Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux]

Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
Abstract

International audience; Segmentation of patient-specific anatomical models is one of the first steps in Electrocardiographic imaging (ECGI). However, the effect of segmentation variability on ECGI remains unexplored. In this study, we assess the effect of heart segmentation variability on ECG simulation. We generated a statistical shape model from segmentations of the same patient and generated 262 cardiac geometries to run in an ECG forward computation of body surface potentials (BSPs) using an equivalent dipole layer cardiac source model and 5 ventricular stimulation protocols. Variability between simulated BSPs for all models and protocols was assessed using Pearson's correlation coefficient (CC). Compared to the BSPs of the mean cardiac shape model, the lowest variability (average CC = 0.98 ± 0.03) was found for apical pacing whereas the highest variability (average CC = 0.90 ± 0.23) was found for right ventricular free wall pacing. Furthermore, low amplitude BSPs show a larger variation in QRS morphology compared to high amplitude signals. The results indicate that the uncertainty in cardiac shape has a significant impact on ECGI.

Published
2022

3. 'A comparison of multithreading, vectorization, and GPU computing for the acceleration of cardiac electrophysiology models'

Author

Sakka, Chiheb, Guermouche, Amina, Aumage, Olivier, Saillard, Emmanuelle, Potse, Mark, Coudière, Yves, Barthou, Denis, STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS), IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux], ANR-18-CE46-0010,Exacard,Simulation exascale de l'électrophysiologie cardiaque pour la recherche sur les arythmies(2018), and ANR-10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010)

Subjects
[INFO]Computer Science [cs]
Abstract

International audience; Realistic simulation of cardiac electrophysiology requires both high resolution and computationally expensive models of membrane dynamics. Optimization of membrane models can therefore have a large impact on time, hardware, and energy usage. We tested both CPU-based and GPU-based optimization techniques for a human heart model with Ten Tusscher-Panfilov 2006 dynamics. Compared to a multithreaded code running on 64 CPU cores, the tested NVIDIA Tesla P100 GPU proved about 3 times faster. Effective use of the CPU's SIMD capabilities allowed a similar performance gain. GPU performance was bounded by the data transfer rate between GPU and main memory. Optimal SIMD use required explicit vectorization and an adapted data structure. We conclude that on mixed CPU-GPU systems the best results are obtained by optimizing both CPU and GPU code and using a runtime system that balances CPU and GPU load.

Published
2022

4. Global Sensitivity Analysis for Uncertain Parameters Applied to a Cardiac Mitochondrial Model

Author

Yves Coudière, Michael Leguèbe, Camille Colin, Philippe Diolez, Bachar Tarraf, Stéphane Arbault, Emmanuel Suraniti, IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux], Université de Bordeaux (UB), Institut des Sciences Moléculaires (ISM), Université Montesquieu - Bordeaux 4-Université Sciences et Technologies - Bordeaux 1 (UB)-École Nationale Supérieure de Chimie et de Physique de Bordeaux (ENSCPB)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche Cardio-Thoracique de Bordeaux [Bordeaux] (CRCTB), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut National de la Santé et de la Recherche Médicale (INSERM), This study received financial support from the French Government as part of the 'Investments of the Future' program managed by the Agence Nationale de la Recherchegrant ANR-10-IAHU-04 and also from the project MITOCARD (ANR-17-CE11-0041), ANR-10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), ANR-17-CE11-0041,MITOCARD,Electrophysiologie de la Mitochondrie Cardiaque(2017), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Université Montesquieu - Bordeaux 4-Université Sciences et Technologies - Bordeaux 1-École Nationale Supérieure de Chimie et de Physique de Bordeaux (ENSCPB)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Tarraf, Bachar, Instituts Hospitalo-Universitaires - L'Institut de Rythmologie et modélisation Cardiaque - - LIRYC2010 - ANR-10-IAHU-0004 - IAHU - VALID, and Electrophysiologie de la Mitochondrie Cardiaque - - MITOCARD2017 - ANR-17-CE11-0041 - AAPG2017 - VALID

Subjects
0303 health sciences, Mathematical model, Computer science, Ode, Experimental data, [MATH] Mathematics [math], 01 natural sciences, 03 medical and health sciences, Order (biology), Global sensitivity analysis, Ordinary differential equation, 0103 physical sciences, Genetic algorithm, Trajectory, [MATH]Mathematics [math], Biological system, 010303 astronomy & astrophysics, 030304 developmental biology
Abstract

International audience; Cardiac mitochondria are intracellular organelles that have several important roles. For instance, they ensure energy metabolism and calcium regulation, thus are linked to the excitation-contraction cycle of the heart cell. Mathematical models are useful to better understand the complexity of mitochondrial dynamics within a cardiac cell, and we are specifically interested in the dynamics of calcium. Litterature models reflect this complexity, especially in terms of number of equations and parameters, which makes them impossible to calibrate to experimental data. In this paper, we apply a global sensitivity analysis on our previously discussed simple mitochondria model [1], in order to quantify the uncertainty of the parameters. This analysis is done in two steps. First we eliminate non-influential parameters of the internal fluxes governing the activity of the mitochondria. Then we perform this analysis on the outputs of our ODE (ordinary differential equation) model, which are the respiratory rates. Finally, we calibrate the remaining influential parameters using a genetic algorithm with respect to experimental respiratory data.

Published
2020

5. Direct Mapping from Body Surface Potentials to Cardiac Activation Maps Using Neural Networks

Author

Karoui, Amel, Bendahamane, Mostafa, Zemzemi, Nejib, IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
0303 health sciences, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 030204 cardiovascular system & hematology, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 030304 developmental biology
Abstract

International audience

Published
2019

6. Prediction of the Exit Site of Ventricular Tachycardia Based on Different ECG Lead Systems

Author

Michal Kania, Mark Potse, Hubert Cochet, Michel Haïssaguerre, Pierre Jaïs, Yves Coudière, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-CHU Bordeaux [Bordeaux], IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], This work was granted access to the HPC resources of TGCC and CINES under the allocation 2016-A0010307379 made by GENCI, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
medicine.medical_specialty, 0206 medical engineering, Ectopic beat, 010103 numerical & computational mathematics, 02 engineering and technology, Ventricular tachycardia, 01 natural sciences, QRS complex, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Internal medicine, medicine, 0101 mathematics, Mathematics, Centimeter, business.industry, Pattern recognition, Torso, medicine.disease, 020601 biomedical engineering, MESH: Cardiac Electrophysiology, medicine.anatomical_structure, Ventricle, Ventricular Fibrillation, Principal component analysis, Ventricular fibrillation, Cardiology, Catheter ablation, Artificial intelligence, business
Abstract

The effectiveness of a computer-based method for localization of arrhythmia exit sites was studied. The proposed algorithm works on any set of 3 or more ECG leads. The QRS complex integral of an ectopic beat is reduced to principal components treated as coordinates of the exit site in ECG space and then projected to real space by a linear transformation. The accuracy of the method was tested on 5 patient-tailored models of human heart and torso. For each model ∼500 simulations were run, each for different stimulus location. All locations were then estimated from simulated surface ECGs and method accuracy was investigated. The algorithm performed better for the left ventricle than for the right ventricle. The group mean absolute and relative (to a neighboring stimulation site) localization errors in millimeters were: 11.5 (SD=2.5), 2.6 (SD=0.5) for the 252-lead ECG; 12.2 (SD=2.7), 2.7 (SD=0.5) for the 12-lead ECG; and 11.7 (SD=2.4), 2.7 (SD=0.5) for the Frank VCG. This study suggest that the proposed method can predict exit sites with a precision in the order of a centimeter. Low values of error for neighbouring activation sites suggest opportunity for algorithm improvement. The use of vectorcardiographic leads is enough to obtain a precision comparable to a 252-lead ECG.

Published
2017

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