11 results on '"Edward Vigmond"'
Search Results
2. In silico Comparison of Left Atrial Ablation Techniques That Target the Anatomical, Structural, and Electrical Substrates of Atrial Fibrillation
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Caroline H. Roney, Marianne L. Beach, Arihant M. Mehta, Iain Sim, Cesare Corrado, Rokas Bendikas, Jose A. Solis-Lemus, Orod Razeghi, John Whitaker, Louisa O’Neill, Gernot Plank, Edward Vigmond, Steven E. Williams, Mark D. O’Neill, and Steven A. Niederer
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atrial fibrillation ,virtual cohort ,catheter ablation ,atrial fibrosis ,phase singularity mapping ,Physiology ,QP1-981 - Abstract
Catheter ablation therapy for persistent atrial fibrillation (AF) typically includes pulmonary vein isolation (PVI) and may include additional ablation lesions that target patient-specific anatomical, electrical, or structural features. Clinical centers employ different ablation strategies, which use imaging data together with electroanatomic mapping data, depending on data availability. The aim of this study was to compare ablation techniques across a virtual cohort of AF patients. We constructed 20 paroxysmal and 30 persistent AF patient-specific left atrial (LA) bilayer models incorporating fibrotic remodeling from late-gadolinium enhancement (LGE) MRI scans. AF was simulated and post-processed using phase mapping to determine electrical driver locations over 15 s. Six different ablation approaches were tested: (i) PVI alone, modeled as wide-area encirclement of the pulmonary veins; PVI together with: (ii) roof and inferior lines to model posterior wall box isolation; (iii) isolating the largest fibrotic area (identified by LGE-MRI); (iv) isolating all fibrotic areas; (v) isolating the largest driver hotspot region [identified as high simulated phase singularity (PS) density]; and (vi) isolating all driver hotspot regions. Ablation efficacy was assessed to predict optimal ablation therapies for individual patients. We subsequently trained a random forest classifier to predict ablation response using (a) imaging metrics alone, (b) imaging and electrical metrics, or (c) imaging, electrical, and ablation lesion metrics. The optimal ablation approach resulting in termination, or if not possible atrial tachycardia (AT), varied among the virtual patient cohort: (i) 20% PVI alone, (ii) 6% box ablation, (iii) 2% largest fibrosis area, (iv) 4% all fibrosis areas, (v) 2% largest driver hotspot, and (vi) 46% all driver hotspots. Around 20% of cases remained in AF for all ablation strategies. The addition of patient-specific and ablation pattern specific lesion metrics to the trained random forest classifier improved predictive capability from an accuracy of 0.73 to 0.83. The trained classifier results demonstrate that the surface areas of pre-ablation driver regions and of fibrotic tissue not isolated by the proposed ablation strategy are both important for predicting ablation outcome. Overall, our study demonstrates the need to select the optimal ablation strategy for each patient. It suggests that both patient-specific fibrosis properties and driver locations are important for planning ablation approaches, and the distribution of lesions is important for predicting an acute response.
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- 2020
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3. The Left and Right Ventricles Respond Differently to Variation of Pacing Delays in Cardiac Resynchronization Therapy: A Combined Experimental- Computational Approach
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Erik Willemen, Rick Schreurs, Peter R. Huntjens, Marc Strik, Gernot Plank, Edward Vigmond, John Walmsley, Kevin Vernooy, Tammo Delhaas, Frits W. Prinzen, and Joost Lumens
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cardiac resynchronization therapy ,right ventricle ,optimization ,computer simulation ,therapy optimization studies ,CircAdapt ,Physiology ,QP1-981 - Abstract
Introduction: Timing of atrial, right (RV), and left ventricular (LV) stimulation in cardiac resynchronization therapy (CRT) is known to affect electrical activation and pump function of the LV. In this study, we used computer simulations, with input from animal experiments, to investigate the effect of varying pacing delays on both LV and RV electrical dyssynchrony and contractile function.Methods: A pacing protocol was performed in dogs with atrioventricular block (N = 6), using 100 different combinations of atrial (A)-LV and A-RV pacing delays. Regional LV and RV electrical activation times were measured using 112 electrodes and LV and RV pressures were measured with catheter-tip micromanometers. Contractile response to a pacing delay was defined as relative change of the maximum rate of LV and RV pressure rise (dP/dtmax) compared to RV pacing with an A-RV delay of 125 ms. The pacing protocol was simulated in the CircAdapt model of cardiovascular system dynamics, using the experimentally acquired electrical mapping data as input.Results: Ventricular electrical activation changed with changes in the amount of LV or RV pre-excitation. The resulting changes in dP/dtmax differed markedly between the LV and RV. Pacing the LV 10–50 ms before the RV led to the largest increases in LV dP/dtmax. In contrast, RV dP/dtmax was highest with RV pre-excitation and decreased up to 33% with LV pre-excitation. These opposite patterns of changes in RV and LV dP/dtmax were reproduced by the simulations. The simulations extended these observations by showing that changes in steady-state biventricular cardiac output differed from changes in both LV and RV dP/dtmax. The model allowed to explain the discrepant changes in dP/dtmax and cardiac output by coupling between atria and ventricles as well as between the ventricles.Conclusion: The LV and the RV respond in a opposite manner to variation in the amount of LV or RV pre-excitation. Computer simulations capture LV and RV behavior during pacing delay variation and may be used in the design of new CRT optimization studies.
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- 2019
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4. Virtual electrodes around anatomical structures and their roles in defibrillation.
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Adam Connolly, Edward Vigmond, and Martin Bishop
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Medicine ,Science - Abstract
BackgroundVirtual electrodes from structural/conductivity heterogeneities are known to elicit wavefront propagation, upon field-stimulation, and are thought to be important for defibrillation. In this work we investigate how the constitutive and geometrical parameters associated with such anatomical heterogeneities, represented by endo/epicardial surfaces and intramural surfaces in the form of blood-vessels, affect the virtual electrode patterns produced.Methods and resultsThe steady-state bidomain model is used to obtain, using analytical and numerical methods, the virtual electrode patterns created around idealized endocardial trabeculations and blood-vessels. The virtual electrode pattern around blood-vessels is shown to be composed of two dominant effects; current traversing the vessel surface and conductivity heterogeneity from the fibre-architecture. The relative magnitudes of these two effects explain the swapping of the virtual electrode polarity observed, as a function of the vessel radius, and aid in the understanding of the virtual electrode patterns predicted by numerical bidomain modelling. The relatively high conductivity of blood, compared to myocardium, is shown to cause stronger depolarizations in the endocardial trabeculae grooves than the protrusions.ConclusionsThe results provide additional quantitative understanding of the virtual electrodes produced by small-scale ventricular anatomy, and highlight the importance of faithfully representing the physiology and the physics in the context of computational modelling of field stimulation.
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- 2017
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5. Computational assessment of the functional role of sinoatrial node exit pathways in the human heart.
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Sanjay R Kharche, Edward Vigmond, Igor R Efimov, and Halina Dobrzynski
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Medicine ,Science - Abstract
AimThe human right atrium and sinoatrial node (SAN) anatomy is complex. Optical mapping experiments suggest that the SAN is functionally insulated from atrial tissue except at discrete SAN-atrial electrical junctions called SAN exit pathways, SEPs. Additionally, histological imaging suggests the presence of a secondary pacemaker close to the SAN. We hypothesise that a) an insulating border-SEP anatomical configuration is related to SAN arrhythmia; and b) a secondary pacemaker, the paranodal area, is an alternate pacemaker but accentuates tachycardia. A 3D electro-anatomical computational model was used to test these hypotheses.MethodsA detailed 3D human SAN electro-anatomical mathematical model was developed based on our previous anatomical reconstruction. Electrical activity was simulated using tissue specific variants of the Fenton-Karma action potential equations. Simulation experiments were designed to deploy this complex electro-anatomical system to assess the roles of border-SEPs and paranodal area by mimicking experimentally observed SAN arrhythmia. Robust and accurate numerical algorithms were implemented for solving the mono domain reaction-diffusion equation implicitly, calculating 3D filament traces, and computing dominant frequency among other quantitative measurements.ResultsA centre to periphery gradient of increasing diffusion was sufficient to permit initiation of pacemaking at the centre of the 3D SAN. Re-entry within the SAN, micro re-entry, was possible by imposing significant SAN fibrosis in the presence of the insulating border. SEPs promoted the micro re-entry to generate more complex SAN-atrial tachycardia. Simulation of macro re-entry, i.e. re-entry around the SAN, was possible by inclusion of atrial fibrosis in the presence of the insulating border. The border shielded the SAN from atrial tachycardia. However, SAN micro-structure intercellular gap junctional coupling and the paranodal area contributed to prolonged atrial fibrillation. Finally, the micro-structure was found to be sufficient to explain shifts of leading pacemaker site location.ConclusionsThe simulations establish a relationship between anatomy and SAN electrical function. Microstructure, in the form of intercellular gap junction coupling, was found to regulate SAN function and arrhythmia.
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- 2017
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6. Regional ion channel gene expression heterogeneity and ventricular fibrillation dynamics in human hearts.
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Gopal Sivagangabalan, Hamed Nazzari, Olivier Bignolais, Ange Maguy, Patrice Naud, Talha Farid, Stéphane Massé, Nathalie Gaborit, Andras Varro, Krishnakumar Nair, Peter Backx, Edward Vigmond, Stanley Nattel, Sophie Demolombe, and Kumaraswamy Nanthakumar
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Medicine ,Science - Abstract
Structural differences between ventricular regions may not be the sole determinant of local ventricular fibrillation (VF) dynamics and molecular remodeling may play a role.To define regional ion channel expression in myopathic hearts compared to normal hearts, and correlate expression to regional VF dynamics.High throughput real-time RT-PCR was used to quantify the expression patterns of 84 ion-channel, calcium cycling, connexin and related gene transcripts from sites in the LV, septum, and RV in 8 patients undergoing transplantation. An additional eight non-diseased donor human hearts served as controls. To relate local ion channel expression change to VF dynamics localized VF mapping was performed on the explanted myopathic hearts right adjacent to sampled regions. Compared to non-diseased ventricles, significant differences (p
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- 2014
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7. Predicting atrial fibrillation recurrence by combining population data and virtual cohorts of patient-specific left atrial models
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Caroline H. Roney, Iain Sim, Jin Yu, Marianne Beach, Arihant Mehta, Jose Alonso Solis-Lemus, Irum Kotadia, John Whitaker, Cesare Corrado, Orod Razeghi, Edward Vigmond, Sanjiv M. Narayan, Mark O’Neill, Steven E. Williams, and Steven A. Niederer
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Patient-Specific Modeling ,Time Factors ,Models, Cardiovascular ,Action Potentials ,Atrial Remodeling ,Fibrosis ,Magnetic Resonance Imaging ,Risk Assessment ,Machine Learning ,Treatment Outcome ,Heart Rate ,Recurrence ,Risk Factors ,Physiology (medical) ,Atrial Fibrillation ,Catheter Ablation ,Electrocardiography, Ambulatory ,Humans ,Atrial Function, Left ,Cardiology and Cardiovascular Medicine - Abstract
Background: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. Methods: Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. Results: We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). Conclusion: A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation.
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- 2022
8. Functional Imaging and Modeling of the Heart : 10th International Conference, FIMH 2019, Bordeaux, France, June 6–8, 2019, Proceedings
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Yves Coudière, Valéry Ozenne, Edward Vigmond, Nejib Zemzemi, Yves Coudière, Valéry Ozenne, Edward Vigmond, and Nejib Zemzemi
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- Computer vision, Computer science—Mathematics, Numerical analysis, Artificial intelligence, Computer networks
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This book constitutes the refereed proceedings of the 10th International Conference on Functional Imaging and Modeling of the Heart, held in Bordeaux, France, in June 2019.The 46 revised full papers were carefully reviewed and selected from 50 submissions. The focus of the papers is on following topics: Electrophysiology: mapping and biophysical modelling; Novel imaging tools and analysis methods for myocardial tissue characterization and remodeling; Biomechanics: modeling and tissue property measurements; Advanced cardiac image analysis tools for diagnostic and interventions.
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- 2019
9. Influence of Transmural Slow-Conduction Zones on the Long- Time Behaviour Of Atrial Arrhythmia. A Numerical Study with a Human Bilayer Atrial Model
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Simon Labarthe, Edward Vigmond, Yves Coudière, Jacques Henry, Hubert Cochet, Pierre Jais, Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), IHU-LIRYC, 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, 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-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), CHU Bordeaux [Bordeaux], Hôpital Haut-Lévêque, Université Sciences et Technologies - Bordeaux 1-CHU Bordeaux [Bordeaux], plafrim, 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 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), and Université Sciences et Technologies - Bordeaux 1 (UB)-CHU Bordeaux [Bordeaux]
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cardiovascular system ,cardiovascular diseases ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation - Abstract
International audience; Atrial fibrosis is known to be a factor in the perpetu ation of atrial arrhythmia. Despite the thinness of atrial tissue, the fibrosis distribution may not be homogeneous through the entire thickness of the atria. This study aims to elucidate the respective influences of a transmural and a non-transmural distribution of fibrosis, described as a slow conduction zone, on the perpetuation of an arrhythmic episode, compared to a control situation. We used a bilayer monodomain representation of the atria that included transmural heterogeneities of fibre organisation. This model allowed long simulations for a sustainable computational load. We observed that when the fibrosis was transmural, the centre of the rotor was anchored in the slow conduction zone and was stable during a 10 seconds simulation, whereas the other simulations showed meandering rotors that disappeared after a few seconds. This study provided insight into the influence of transmural fibrosis on atrial arrhythmia perpetuation. In our model framework, only a transmural fibrosis distribution had a stabilizing effect on reentrant circuits. The bilayer model proved to be a good trade-off between accuracy and speed for observing the influence of transmural heterogeneities on atrial arrhythmia over long periods.
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- 2013
10. Left Ventricular Shape and Motion Reconstruction through a Healthy Model for Characterizing Remodeling after Infarction
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Mathieu De Craene, Eric Saloux, Nicolas Duchateau, Pascal Allain, Paolo Piro, Philips Research, MedisysResearch Lab (Medisys), Philips Research-Philips Research, Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Modeling & analysis for medical imaging and Diagnosis (MYRIAD), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Yves Coudière, Valéry Ozenne, Edward Vigmond, and Nejib Zemzemi
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Computer science ,Quantitative Biology::Tissues and Organs ,Physics::Medical Physics ,Population ,Motion (geometry) ,Infarction ,030218 nuclear medicine & medical imaging ,Anatomical space ,03 medical and health sciences ,Motion ,0302 clinical medicine ,[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system ,medicine ,[INFO.INFO-IM]Computer Science [cs]/Medical Imaging ,Computer vision ,education ,education.field_of_study ,Abnormality ,Atlas (topology) ,business.industry ,Dynamics (mechanics) ,Shape ,medicine.disease ,3. Good health ,medicine.anatomical_structure ,Ventricle ,Artificial intelligence ,Affine transformation ,business ,Cardiac ,030217 neurology & neurosurgery - Abstract
International audience; We introduce a framework for the statistical characterization of heart remodeling from both shape and dynamics of the left ventricle. Shape was characterized by thickness and radius maps, unfolded in a two-dimensional dense Bull's eye. Motion was represented as a mixture of affine transformations in an anatomical space of coordinates. Using this representation, a population can be projected (after defining spa-tiotemporal correspondences) to an atlas space built for a given reference population-here, healthy subjects using a classic PCA approach-yielding a joint model of healthy shape and motion statistics. The reconstruction error on shape and motion can then be exploited to quantify remodeling abnormalities. We demonstrate these concepts on 48 healthy subjects and 62 patients with infarct (29 with one year follow-up) imaged with 3D echocardiography, analyzing a total of 139 sequences.
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- 2019
11. Maximal conductances ionic parameters estimation in cardiac electrophysiology multiscale modelling
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Yassine Abidi, Moncef Mahjoub, Julien Bouyssier, Nejib Zemzemi, Yves Coudière, Valéry Ozenne, Edward Vigmond, Nejib Zemzemi, Laboratoire de Modélisation Mathématique et Numérique dans les Sciences de l'Ingénieur [Tunis] (LR-LAMSIN-ENIT), Ecole Nationale d'Ingénieurs de Tunis (ENIT), Université de Tunis El Manar (UTM)-Université de Tunis El Manar (UTM), IHU-LIRYC, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux], Modélisation et calculs pour l'électrophysiologie cardiaque (CARMEN), 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, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Y. Coudière, V. Ozenne, E. Vigmond and N. Zemzemi, EPICARD, LIRIMA, ANR-10-IAHU-0004,LIRYC,L'Institut de Rythmologie et modélisation Cardiaque(2010), 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]
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Optimization problem ,Physiological ionic model ,Quantitative Biology::Tissues and Organs ,Cardiac electrophysiology ,Control variable ,Ionic bonding ,010103 numerical & computational mathematics ,01 natural sciences ,Ionic model ,[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system ,First order optimality conditions ,Parameters estimation ,[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP] ,Applied mathematics ,[NLIN]Nonlinear Sciences [physics] ,0101 mathematics ,Maximal conductance ionic parameters ,Physics ,Bidomain model ,Optimal control ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,010101 applied mathematics ,Optimal control with PDE constraints ,[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] ,Gradient descent - Abstract
International audience; In this work, we present an optimal control formulation for the bidomain model in order to estimate maximal conductances parameters in the physiological ionic model. We consider a general Hodgkin-Huxley formalism to describe the ionic exchanges at the microcopic level. We consider the parameters as control variables to minimize the mismatch between the measured and the computed potentials under the constraint of the bidomain system. The solution of the optimization problem is based on a gradient descent method, where the gradient is obtained by solving an adjoint problem. We show through some numerical examples the capability of this approach to estimate the values of sodium, calcium and potassium ion channels conductances in the Luo Rudy phase I model.
- Published
- 2019
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