RESEARCH CENTRE

Inria Centre
at the University of Bordeaux

2023
ACTIVITY REPORT

IN PARTNERSHIP WITH:

Université de Bordeaux

Project-Team

CARMEN

Modélisation et calculs pour
l’électrophysiologie cardiaque

IN COLLABORATION WITH: Institut de Mathématiques de Bordeaux (IMB)

DOMAIN

Digital Health, Biology and Earth

THEME

Modeling and Control for Life Sciences

Contents

Project-Team CARMEN

1 Team members, visitors, external collaborators

2 Overall objectives

3 Research program

. . . . . . . . . . . . . . .
3.1 Complex models for the propagation of cardiac action potentials
3.2 Simplified models and inverse problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Numerical techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Cardiac electrophysiology at the microscopic scale . . . . . . . . . . . . . . . . . . . . . . . .
3.5 Models and tools for ablative therapies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 Application domains

4.1 Scientific context: IHU Liryc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Basic experimental electrophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.3 Clinical electrophysiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.4 Application in Deep Brain Stimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5 Social and environmental responsibility

5.1 Footprint of research activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Impact of research results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6 Highlights of the year

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7 New software, platforms, open data

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7.1 Evolution of existing software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
7.2 New software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
7.2.1 CEPS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.2.2 OptimDBS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
7.2.3 MUSIC - Carmen plugins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
7.3 New platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

8 New results

12
8.1 Numerical analysis and development of numerical methods . . . . . . . . . . . . . . . . . . 12
8.2 Modeling and inverse problems
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
8.3 Clinical applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
8.4 High performance computing and Microscopic models . . . . . . . . . . . . . . . . . . . . . 15

9 Bilateral contracts and grants with industry

16
9.1 Bilateral Grants with Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

10 Partnerships and cooperations

16
10.1 International initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework

10.2 International research visitors

of an Inria International Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
10.1.2 Participation in other International Programs . . . . . . . . . . . . . . . . . . . . . . . 17
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
10.2.1 Visits of international scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
10.2.2 Visits to international teams
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
10.4 National initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
10.5 Regional initiatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

10.3 European initiatives

10.3.1 H2020 projects

11 Dissemination

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11.1 Promoting scientific activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
11.1.1 Scientific events: organisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
11.1.2 Scientific events: selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
11.1.3 Invited talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
11.1.4 Leadership within the scientific community . . . . . . . . . . . . . . . . . . . . . . . . 25
11.1.5 Scientific expertise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
11.1.6 Research administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
11.2 Teaching - Supervision - Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
11.2.1 Teaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
11.2.2 Juries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.2.3 Teaching administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3 Popularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.1 Articles and contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
11.3.2 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
11.3.3 Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

12 Scientific production

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12.1 Major publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
12.2 Publications of the year
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12.3 Cited publications

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Project-Team CARMEN

Creation of the Project-Team: 2016 June 01

Keywords

Computer sciences and digital sciences

A6.1.1. – Continuous Modeling (PDE, ODE)

A6.1.2. – Stochastic Modeling

A6.1.4. – Multiscale modeling

A6.2.1. – Numerical analysis of PDE and ODE

A6.2.6. – Optimization

A6.2.7. – High performance computing

A6.2.8. – Computational geometry and meshes

A6.3.1. – Inverse problems

A6.3.2. – Data assimilation

A6.3.3. – Data processing

A6.3.5. – Uncertainty Quantification

Other research topics and application domains

B1.1.2. – Molecular and cellular biology

B1.1.8. – Mathematical biology

B2.2.1. – Cardiovascular and respiratory diseases

B2.2.6. – Neurodegenerative diseases

B2.4.1. – Pharmaco kinetics and dynamics

B2.4.3. – Surgery

B2.6.1. – Brain imaging

B2.6.2. – Cardiac imaging

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Inria Annual Report 2023

1 Team members, visitors, external collaborators

Research Scientists

• Jacques Henry [INRIA, Emeritus, HDR]

• Peter Langfield [INRIA, Researcher]

• Michael Leguebe [INRIA, Researcher]

• Nejib Zemzemi [INRIA, Researcher]

Faculty Members

• Yves Coudière [Team leader, UNIV BORDEAUX, Professor Delegation, HDR]

• Mostafa Bendahmane [UNIV BORDEAUX, Associate Professor, HDR]

• Mark Potse [UNIV BORDEAUX, researcher with a CDI]

• Lisl Weynans [UNIV BORDEAUX, Associate Professor, HDR]

Post-Doctoral Fellows

• Andony Arrieula [UNIV BORDEAUX, until Nov 2023]

• Laetitia Mottet [UNIV BORDEAUX]

PhD Students

• Zeina Chehade [UNIV BORDEAUX]

• Narimane Gassa [UNIV BORDEAUX]

• Emma Lagracie [UNIV BORDEAUX]

• Niami Nasr [BORDEAUX INP, ATER, from Oct 2023]

• Niami Nasr [UNIV BORDEAUX, until Sep 2023]

• Valentin Pannetier [UNIV BORDEAUX]

Technical Staff

• Wissam Bouymedj [UNIV BORDEAUX, Engineer, from Apr 2023]

• Corentin Prigent [UNIV BORDEAUX, Engineer]

Interns and Apprentices

• Mohamed Ahmane [INRIA, Intern, from Oct 2023]

• Narjess Ben Abid [ENIT TUNIS, Intern, from Nov 2023]

• Emna Bouaine [INRIA, Intern, from May 2023 until Oct 2023]

• Arthur Jean [UNIV BORDEAUX, Intern, from May 2023 until Aug 2023]

• Mokrane Mouzaoui [INRIA, Intern, from Jun 2023 until Aug 2023]

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Administrative Assistant

• Flavie Blondel [INRIA]

Visiting Scientists

• Hamza Ammar [University of Tunis El Manar, from May 2023 until Jun 2023]

• Blanca Rodriguez Lopez [Oxford University]

External Collaborator

• Hassaan Bukhari [University of Zaragoza]

2 Overall objectives

The Carmen team develops and uses models and numerical methods to simulate the electrophysiology
of the heart from the molecular to the whole-organ scale, and its relation to measurable signals inside the
heart and on the body surface. It aims at:

• improving understanding of normal and pathological cardiac electrophysiology,

• improving the efficiency and accuracy of numerical models,

• exploiting all available electrical signals for diagnosis,

• improving understanding and guidance of ablative treatment of cardiac arrhythmia.

The numerical models developed, analyzed, and used by the team incorporate essentially the gating
dynamics of the ion channels in the cardiac cell membranes and the heterogeneities of the cardiac tissue,
coupling processes on the cellular scale into macroscopic reaction-diffusion models. The team also work
on incorporating any new biological knowledge, at any scale, that helps to understand the mechanisms
of arrythmias, their diagnosis or treatment. At the same time we use simpler or reduced models to solve
the inverse problems related to non-invasive electrical imaging of the heart.

The fields involved in our research are: ordinary and partial differential equations (ODE & PDE),
inverse problems, numerical analysis, high-performance computing, image segmentation, and mesh
construction.

A main goal of the team is to contribute to the work packages defined in the project of IHU Liryc, an

institute founded in 2011 that focuses on cardiac arrhythmia.

We cooperate with physiologists and cardiologists on several projects. The team is building new
models and powerful simulation tools that will help to understand the mechanisms behind cardiac
arrhythmias and to establish personalized and optimized treatments. A particular challenge consists in
making the simulations reliable and accessible to the medical community.

3 Research program

3.1 Complex models for the propagation of cardiac action potentials

The contraction of the heart is coordinated by a complex electrical activation process which relies
on about a million ion channels, pumps, and exchangers of various kinds in the membrane of each
cardiac cell. Their interaction results in a periodic change in transmembrane potential called an action
potential. Action potentials in the cardiac muscle propagate rapidly from cell to cell, synchronizing the
contraction of the entire muscle to achieve an efficient pump function. The spatio-temporal pattern of
this propagation is related both to the function of the cellular membrane and to the structural organization
of the cells into tissues. Cardiac arrythmias originate from malfunctions in this process. The field of
cardiac electrophysiology studies the multiscale organization of the cardiac activation process from the
subcellular scale up to the scale of the body. It relates the molecular processes in the cell membranes to

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Inria Annual Report 2023

the propagation process through the multiscale structure of the tissue and organ, to measurable signals
in the heart and to the electrocardiogram, an electrical signal on the torso surface.

Several improvements of current models of the propagation of action potentials are being developed

in the Carmen team, based on previous work [39] and on the data available at IHU Liryc:

• Enrichment of the current monodomain and bidomain models [39, 49] by accounting for structural
heterogeneities of the tissue at cellular and intermediate scales. Here we focus on multiscale
analysis techniques applied to the various high-resolution structural data available at IHU Liryc.

• Coupling of the tissues from the different cardiac compartments and conduction systems. Here, we
develop models that couple 1D, 2D and 3D phenomena described by reaction- diffusion PDEs.

These models are essential to improve our understanding of cardiac electrical dysfunction. To this
aim, we use high-performance computing techniques in order to numerically explore the complexity of
these models.

We use these model codes for applied studies in two important areas of cardiac electrophysiology:
atrial fibrillation [41] and sudden-cardiac-death (SCD) syndromes [7], [6] [44]. This work is performed in
collaboration with several physiologists and clinicians both at IHU Liryc and abroad.

3.2 Simplified models and inverse problems

The medical and clinical exploration of the cardiac electric signals is based on accurate reconstruction of
the patterns of propagation of the action potential. The correct detection of these complex patterns by
non-invasive electrical imaging techniques has to be developed. This involves solving inverse problems
that cannot be addressed with the more complex models. We want both to develop simple and fast
models of the propagation of cardiac action potentials and improve the solutions to the reconstruction
questions of cardiac electrical imaging techniques.

These questions concern the reconstruction of diverse information, such as cardiac activation maps or,
more generally, the whole cardiac electrical activity, from high-density body surface electrocardiograms.
It is a possibly powerful diagnosis technique, which success would be considered as a breakthrough.
Although widely studied during the last decade, the reconstructed activation maps, for instance, are
highly inacurate and have a poor clinical interest. It remains a challenge for the scientific community to
understand how body surface signals can better inform on the fine details of arrhythmic mechanisms.

The most usual method consists in solving a Laplace equation on the volume delimited by the body

surface and the epicardial surface, for which we contribute by:

• studying in depth the dependance of the inverse problem on inhomogeneities in the torso, con-

ductivity values, the geometry, electrode positions, etc., and

• improving the solution to the inverse problem by using new regularization strategies, factorization

of boundary value problems, and the theory of optimal control.

In addition, we have started to explore many alternative approaches including:

• using complete propagation models in the inverse problem, like the bidomain or monodomain

equations, for instance in order to localize electrical sources,

• constructing data-based models using e.g. statistical learning techniques, which would accurately
represent some families of well-identified pathologies, or allow to combine physics and biology-
informed models and clinical data, and

• constructing simpler models of the propagation of the activation front, based on eikonal or level-set

equations.

3.3 Numerical techniques

We want our numerical simulations to be efficient, accurate, and reliable with respect to the needs of the
medical community. Based on previous work on solving the monodomain and bidomain equations [3, 4,
8, 1], we will focus on:

Project CARMEN

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• high-order numerical techniques with respect to the variables with physiological meaning, like

velocity, AP duration and restitution properties and

• efficient, dedicated preconditioning techniques coupled with parallel computing.

Existing simulation tools used in our team rely, among others, on mixtures of explicit and implicit
integration methods for ODEs, hybrid MPI-OpenMP parallellization, algebraic multigrid preconditioning,
and Krylov solvers. New developments include high-order explicit integration methods and task-based
dynamic parallellism.

3.4 Cardiac electrophysiology at the microscopic scale

Traditional numerical models of whole-heart physiology are based on the approximation of a perfect
muscle using homogenisation methods. However, due to aging and cardiomyopathies, the cellular
structure of the tissue changes. These modifications can give rise to life-threatening arrhythmias, the
mechanisms of which we are investigating in collaboration with cardiologists at the IHU Liryc. For this
research we are building models that describe the strong heterogeneity of the tissue at the cellular level.
The literature on this type of model is still very limited [54]. Existing models are two-dimensional [45]
or limited to idealized geometries, and use a linear (purely resistive) behaviour of the gap-juction channels
that connect the cells. We propose a three-dimensional approach using realistic cellular geometry
(Fig. 1), nonlinear gap-junction behaviour, and a numerical approach that can scale to hundreds of
cells while maintaining a sub-micrometer spatial resolution (10 to 100 times smaller than the size of
a cardiomyocyte). Following preliminary work in this area by us [35, 34, 33] and by others [54] we
proposed a European project with 10 partner institutes and a 5.8M€ budget to develop software that
can simulate such models, with micrometer resolution, on the scale of millions of cells, using future
exascale supercomputers (microcard.eu). This project runs from April 2021 to October 2024, and involves
also the Inria teams CAMUS, STORM and CARDAMOM as well as the Inria-led MMG Consortium. The
cell-by-cell bidomain model presents numerous mathematical and computational challenges. First,
mathematically, its unusual formulation providing time dynamics as an ordinary differential equation
(ODE) at the cell- to-cell connections and cell-to-extracellular matrix interfaces. Second, the ionic model
coupled to the non standard transmission conditions, introduce stiff non linear dynamics. Third, the
simulation would performing for a billions of myocytes, that can lead to a significantly large system. In the
MICROCARD project, we simulate the micromodel using finite volumes, finite elements and boundary
element methods.

3.5 Models and tools for ablative therapies

Today, the most effective way to treat arrhythmias is to ablate selected regions of the cardiac tissue. As the
lesions have no particular electric property, this creates conduction blocks that stop the disorganized
propagation of action potentials. The ablation procedure consists in placing a catheter in contact with
the targeted site and deliver energy into the tissue. The energy can be overheating by radio-frequency
current, electroporating electric pulses or temperature drop (cryotherapy). In practice, the choice of the
ablation site is done by the clinician based on previous signal measurements and imagery, and is also
guided during the procedure with real-time measurement of the electric signal.

Our team works on several subjects related to ablation techniques that may improve the success rate

of the treatments:

• accurate computation of electric fields generated by catheters: complex catheter shapes, contact

models, tissue heterogeneities;

• models of creation of the lesions, either through temperature rise (radio-frequency) or electropora-

tion; and

• localization tools to help clinicians target the optimal ablation sites, based on both data of previ-

ously ablated patients and synthetic data.

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Inria Annual Report 2023

Figure 1: A: The cardiac muscle consists of a branching network of elongated muscle cells, interspersed
with other structures. Sheets of connective tissue (blue) can grow between the muscle cells and become
pathogenic. B: Current models can only represent such alterations in a coarse way by replacing model
elements with different types; each cube in this illustration would represent hundreds of cells. C: This
example from the MICROCARD project [48] illustrates the type of geometric model we are experimenting
with. It represents 500 × 400 × 100 µm of tissue (corresponding to 5 × 4 blocks in panel B) and contains
1600 cells, identified with different colors. Each cell is here represented by hundreds of elements.

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4 Application domains

4.1 Scientific context: IHU Liryc

The University Hospital of Bordeaux (CHU de Bordeaux) is equipped with a specialized cardiology
hospital, the Hôpital Cardiologique du Haut-Lévêque, where the group of Professor Michel Haïssaguerre
has established itself as a global leader in the field of cardiac electrophysiology [42, 43, 37]. Their
discoveries in the area of atrial fibrillation and sudden cardiac death syndromes are widely acclaimed,
and the group is a national and international referral center for treatment of cardiac arrhythmia. Thus
the group also sees large numbers of patients with rare cardiac diseases.

In 2011 the group has won the competition for a 40 million euro Investissements d’Avenir grant for the
establishment of IHU Liryc, an institute that combines clinical, experimental, and numerical research in
the area of cardiac arrhythmia. The institute works in all areas of modern cardiac electrophysiology: atrial
arrhythmias, sudden death due to ventricular fibrillation, heart failure related to ventricular dyssynchrony,
and metabolic disorders. It is recognized worldwide as one of the most important centers in this area.

The Carmen team was founded as a part of IHU Liryc. We bring applied mathematics and scientific
computing closer to experimental and clinical cardiac electrophysiology. In collaboration with experi-
mental and clinical researchers at Liryc we work to enhance fundamental knowledge of the normal and
abnormal cardiac electrical activity and of the patterns of the electrocardiogram, and we develop new
simulation tools for training, biological, and clinical applications.

4.2 Basic experimental electrophysiology

Our modeling is carried out in coordination with the experimental teams from IHU Liryc. It helps to write
new concepts concerning the multiscale organisation of the cardiac action potentials that will serve our
understanding in many electrical pathologies. For example, we model the structural heterogeneities at
the cellular scale [36] (the MICROCARD project), and at an intermediate scale between the cellular and
tissue scales.

At the atrial level, we apply our models to understand the mechanisms of complex arrythmias
and the relation with the heterogeneities at the insertion of the pulmonary veins. We will model the
heterogeneities specific to the atria, like fibrosis or fatty infiltration [51, 41]. These heterogeneities are
thought to play a major role in the development of atrial fibrillation.

At the ventricular level, we focus on (1) modeling the complex coupling between the Purkinje network
and the ventricles, which is supposed to play a major role in sudden cardiac death, and (2) modeling the
heteogeneities related to the complex organization and disorganization of the myocytes and fibroblasts,
which is important in the study of infarct scars for instance.

4.3 Clinical electrophysiology

Treatment of cardiac arrhythmia is possible by pharmacological means, by implantation of pacemakers
and defibrillators, and by curative ablation of diseased tissue by local heating, freezing or electroporation.
In particular the ablative therapies create challenges that can be addressed by numerical means. Cardi-
ologists would like to know, preferably by noninvasive means, where an arrhythmia originates and by
what mechanism it is sustained.

We address this issue in the first place using inverse models, which attempt to estimate the cardiac
activity from a (high-density) electrocardiogram. A new project aims to perform this estimation on-site
in the catheterization laboratory and presenting the results, together with the cardiac anatomy, on the
screen that the cardiologist uses to monitor the catheter positions [46, 31].

4.4 Application in Deep Brain Stimulation

Since 2017, we have been working with neurosurgeons from the Bordeaux University Hospital (Pr Cuny
and Dr. Engelhardt) on improving the planning technique for deep brain surgery (DBS) for Parkinson’s
and Essential tremor diseases. DBS is the last resort to treat the symptoms of Parkinson’s disease after
the drug Levodopa. The surgery consists in placing electrodes in very specific regions of the patient’s

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Inria Annual Report 2023

brain. These regions are unfortunately not visible on the 1.5 Tesla MRI, the most widely available MRI
machines in hospitals. The most effective solution to date is to introduce 5 micro-electrodes (MER) to
record the activity of neurons in the patient’s brain and to prospect by moving the electrodes in order to
find the best location. However, this approach renders the surgery very cumbersome because the patient
must be awake during the exploration phase. In addition, this phase takes at least 3 hours and mobilizes
a neurologist with his staff. The total duration of the operation is between 7 and 8 hours. Many elderly
patients do not tolerate this surgery. We have proposed an approach that avoids the prospecting phase
and performs surgery under general anesthesia. The idea is to learn on pairs of clinical landmarks and
the position of active electrodes in order to predict the optimal position of the DBS from a pre-operative
image. This approach simplifies and standardizes surgery planning. We tested several approaches
doi:10.3389/fneur.2021.620360. We continue to seek approaches to fully automate the targeting process.
We carried out a proof of concept by learning on the clinical database of the Bordeaux University Hospital.
The clinical validation of our approach is in progress through a clinical trial which includes patients
from the University Hospitals of Bordeaux and Lyon. Pr Cuny has submitted a phase 3 national clinical
research hospital project (PHRCN) including 11 CHUs in France which has been accepted by the General
Directorate for Care Offers (DGOS). The aim is to compare our new approach to the ones used in the
other centers. Inria Bordeaux is a partner in this project and we maintain the OptimDBS software and
solve any technical problem related to the compatibility of the MRIs exported by our software and the
surgical robots in the different centers.

5 Social and environmental responsibility

5.1 Footprint of research activities

We avoid flying whenever we can.

5.2 Impact of research results

The MICROCARD project, which we coordinate, has energy efficiency as one of its goals. To this end, our
partners in the STORM and CAMUS teams are developing methods to increase the time- and energy-
efficiency of cardiac simulation codes.

6 Highlights of the year

• Project EITCardio co-funded by the Région Nouvelle Aquitaine, Inria and the Fondation EDF on
electrical impedance tomography for the detection of cardiac arhythmia, also in collaboration with
Inria Saclay.

The objective of this project is to develop mathematical methods for solving Electrical Impedance
Tomography (EIT) to enhance the resolution of the ECGi (Electrocardiographic Imaging) problem
and validate them experimentally. Specifically, the project consists of two parts:

– development of mathematical and numerical methods to solve the inverse problem of EIT in
the torso and identify influential parameters for the propagation of the electric field, such as
conductivities and organ movements.

– Experimental validation of the ECGi + EIT coupling. This experimental validation will be
conducted first within the experimental setup, the torso tank, currently available at Liryc,
which allows measurements for ECGi in a controlled environment. Subsequently, it will be
conducted as in-vivo experiments, meaning a context closer to clinical reality.

The project involves researchers from the Inria CARMEN team, specializing in modeling the elec-
trical activity of the heart, IHU-Liryc, and LMAP in Pau, experts in scientific computing and
uncertainty consideration.

• Project ATLAS-RV funded by the IHU Liryc internal call, led by Peter Langfield, to study typical

patterns of repolarization in the human ventricles via in-vivo contact-mapped datasets.

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7 New software, platforms, open data

7.1 Evolution of existing software

CEPS. We added to CEPS the pacemaker models derived for the SimCardioTest project. These models
required a complete rewriting of most of CEPS source code, which is now over. We developed new code
according the high Software Quality standards, using Inria’s sonarQube platform to monitor the issues.
We took advantage of this rewriting to perform a global overhaul of the code in terms of accessibility,

be it in the API or the documentation.

7.2 New software

7.2.1 CEPS

Name: Cardiac ElectroPhysiology Simulation

Keywords: Simulation, Health, Mesh, Cardiac, 3D, Cardiac Electrophysiology

Scientific Description: As compared to other existing softwares, CEPS aims at providing a more general
framework of integration for new methods or models and a better efficiency in parallel. CEPS is
designed to run on massively parallel architectures, and to make use of state-of-the-art and well
known computing libraries to achieve realistic and complex heart simulations. CEPS also includes
software engineering and validation tools.

Functional Description: CEPS is a modular high-performance computing software for performing nu-
merical simulations in cardiac electrophysiology. It is based on modules : - management of
geometries represented by meshes in 3D, 2D or 1D (volumes, surfaces, trees), - model simulation
of cellular electrophysiology, - calculating the tissue propagation of the action potentials in the
cardiac geometries, - calculation of extracardiac potentials, - time approximation methods in order
2, 3 and 4 specific to electrocardiography.

URL: https://carmen.gitlabpages.inria.fr/ceps/

Contact: Ceps Dev Team

Participants: Yves Coudière, Michael Leguebe, Valentin Pannetier, Pierre-elliott Bécue, Florian Caro,
Andjela Davidovic, Charlie Douanla Lontsi, Marc Fuentes, Mehdi Juhoor, Pauline Migerditichan,
Nejib Zemzemi

Partners: Université de Bordeaux, Fondation Bordeaux Université, CHU de Bordeaux, Inria

7.2.2 OptimDBS

Name: Optimizing the Deep Brain Stimulation

Keywords: Image analysis, Deep brain stimulation, Statistical learning

Functional Description: Targeting software for deep brain stimulation

URL: https://gitlab.inria.fr/optimdbs/optimdbs-medinria/-/wikis/home

Contact: Nejib Zemzemi

Participants: Nejib Zemzemi, Louise-Amelie Schmitt, Emmanuel Cuny, Julien Engelhardt

Partner: CHU de Bordeaux

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Inria Annual Report 2023

7.2.3 MUSIC - Carmen plugins

Name: Carmen plugins for multi-modality imaging in Cardiology

Keywords: Image segmentation, Mesh generation, Image filter, Numerical simulations, Cardiac Electro-
physiology, Inverse problem, Finite element modelling, Visualization, 3D interaction, Registration

Scientific Description: Carmen plugins is a collection of toolboxes and pipelines allowing the following
functionalities: - Segmenting and filtering the heart, the surrounding organs and the body surface.
- Generate/optimize surface and volume of computational meshes for the segmented organs. -
Generate fibers orientations for Atria and Ventricles. - Interactively annotate meshes. - Read map
and visualize electrical information collected from medical devices. - Numerical simulation of the
forward problem using finite elements method. - Method of fundamental solutions for solving the
ECGI inverse problem combined with the regularization methods including CRESO,Zero Crossing
GCV, RGCV, ADPC and Ucurve. - Landmark based mesh registration. - ECGI pipeline: including
segmentation, mesh generation, identification of the vest electrodes.

Functional Description: Carmen plugins is a collection of toolboxes and pipelines allowing the following
functionalities: - Segmenting and filtering the heart, the surrounding organs and the body surface.
- Generate/optimize surface and volume of computational meshes for the segmented organs. -
Generate fibers orientations for Atria and Ventricles. - Interactively annotate meshes. - Read map
and visualize electrical information collected from medical devices. - Numerical simulation of the
forward problem using finite elements method. - Method of fundamental solutions for solving the
ECGI inverse problem combined with the regularization methods including CRESO,Zero Crossing
GCV, RGCV, ADPC and Ucurve. - Landmark based mesh registration. - ECGI pipeline: including
segmentation, mesh generation, identification of the vest electrodes.

Publications: hal-01923927, hal-01923763, hal-01400889

Contact: Nejib Zemzemi

Participants: Hubert Cochet, Florent Collot, Mathilde Merle, Maxime Sermesant, Julien Castelneau,

Mehdi Juhoor, Pauline Migerditichan, Nejib Zemzemi, Yves Coudière

Partners: Université de Bordeaux, IHU - LIRYC

Participants: Mark Potse, Andony Arrieula, Laetitia Mottet, Corentin Prigent, Wis-

sam Bouymedj, Yves Coudière.

7.3 New platforms

OpenCARP

OpenCARP is an open cardiac electrophysiology simulator for in-silico experiments. Its source code
is public and the software is freely available for academic purposes. OpenCARP is easy to use and
offers single cell as well as multiscale simulations from ion channel to organ level. Additionally, open-
CARP includes a wide variety of functions for pre- and post-processing of data as well as visualization.
The python-based CARPutils framework enables the user to develop and share simulation pipelines,
i.e. automating in-silico experiments including all modeling/simulation steps.

KIT and the company Numericor, the main creators of openCARP, with the University of Graz, are
partners of the MICROCARD project. The openCARP simulator is developed within the MICROCARD
project targeting the creation of a microscopiv cardiac model.

We have been contributing by managing the MICROCARD consortium and its contributions to open-
CARP, and by adapting the partitionning scheme (based on parMETIS) to the context of the microscopic
model.

Project CARMEN

Mmg

11

Mmg is an open source software suite for simplicial remeshing and an open source Consortium, which
participates in the MICROCARD project.

In this context we have been active developers of the Mmg software. Laetitia Mottet (postdoc) works
on ParMmg, the parallel version of Mmg, where she implemented level-set discretization and is working
on the robustification of the software. Corentin Prigent (engineer) works on the serial code mmg3d for
1) its robustification so that it can deal with the extremely complicated topology of the meshes created
using segmented data provided by partners in the MICROCARD project, and 2) for the purposes of the
MICROCARD project, Mark Potse uses mmg3d for the challenging task of creating artificial models of
cardiac muscle fibers (Figure 1C).

In the MICROCARD project, tetrahedral meshes are created using both segmented data and synthetic
models. Several improvements made this year in mmg now allow us to 1) use these segmented data to
create valid meshes with much less elements than in the initial data, 2) improve the synthetic generation
of cardiac tissue.

CEMPACK

CEMPACK is a collection of software that was previously archived in different places. It includes the
high-performance simulation code Propag and a suite of software to create geometric models, prepare
inputs for Propag, and analyse its outputs. In 2017 the code was collected in an archive on Inria’s GitLab
platform. The main components of CEMPACK are the following.

Propag-5.1 Applied modeling studies performed by the Carmen team in collaboration with IHU Liryc
and foreign partners [7] [52, 41, 40, 38] rely on high-performance computations on the national
supercomputers Irene, Zay, and Adastra. The Propag-5 code is optimized for these systems. It is
the result of a decades-long development first at the Université de Montréal in Canada, then at
Maastricht University in the Netherlands, and finally at the Institute of Computational Science of
the Università della Svizzera italiana in Lugano, Switzerland. Since 2016 most of the development
on Propag has been done by M. Potse at the Carmen team [47]. The code scales excellently to large
core counts [53] and, as it is controlled completely with command-line flags and configuration files,
it can be used by non-programmers. It also features:

• a plugin system for membrane models,

• a completely parallel workflow, including the initial anatomy input and mesh partitioning,

which allows it to work with meshes of more than 109 nodes,

• a flexible output scheme allowing hundreds of different state variables and transient variables

to be output to file, when desired, using any spatial and temporal subsampling,

• a configurable, LUSTRE-aware parallel output system in which groups of processes write

HDF5/netCDF files, and

• CWEB documentation of the entire code base.

The code has been stable and reliable for many years. It can be considered the workhorse for our
HPC work until CEPS takes over.

Gepetto The Gepetto suite transforms a surface mesh of the heart into a set of (semi-)structured meshes
for use by the Propag software or others. It creates the different fiber orientations in the model,
including the transmurally rotating ventricular fibers and the various bundle structures in the
atria (figure 2), and creates layers with possibly different electrophysiological properties across
the wall. A practically important function is that it automatically builds the matching heart and
torso meshes that Propag uses to simulate potentials in the torso (at a resolution of 1 mm) after
projecting simulation results from the heart model (at 0.1 to 0.2 mm) on the coarser torso mesh [50].
Like Propag, the Gepetto software results from a long-term development that started in Montreal,
Canada, around 2002. The code for atrial fiber structure was developed by our team.

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Inria Annual Report 2023

A

B

C

Figure 2: A and B: Complete heart-torso geometries created with CEMPACK tools. C: Bundle structures
and different layers of fiber orientation created by the Gepetto software and visualized using Blender.

Blender plugins Blender is a free software package for the production of 3-D models, renderings, and
animations, comparable to commercial software such as Cinema4D. CEMPACK includes a set
of plugins for Blender that facilitate the production of anatomical models and the visualization
of measured and simulated data. It uses the MMG remeshing library, which is developed by the
CARDAMOM team at Inria Bordeaux. Currently our segmentation work is mostly done with the
MUSICardio software, but we still use Blender for finishing touches and high-quality visualization.

Participants: Mostafa Bendahmane, Yves Coudière, Jacques Henry, Peter Langfield,

Michael Leguèbe, Mark Potse, Lisl Weynans, Nejib Zemzemi.

8 New results

8.1 Numerical analysis and development of numerical methods

• Isochrone computation There has been ongoing development of a numerical continuation-based
method to compute higher-dimensional isochrones. The method had been previously applied
to the Hodgkin-Huxley model. During this year, a region of extremely low sensitivity of phase
response to stimuli was identified, which is a property supportive of synchroniziation between cells.
This region was studied and we have hypothesized an underlying mechanism that gives rise to it.
These results form a manuscript that is currently in preparation, which will be submitted within
the first few months of this year. We also started to use the method to study isochrones in more
cardiac-related models, namely, the Beeler-Reuter model and a model of a sinoatrial node cell.

• Immersed boundary method for cardiac EIT We proposed an immersed boundary scheme for the
numerical resolution of the Complete Electrode Model in Electrical Impedance Tomography, that
we use as a main ingredient in the resolution of inverse problems in medical imaging. Such method
allows to use a Cartesian mesh without accurate discretization of the boundary, which is useful in
situations where the boundary is complicated and/or changing. We proved the convergence of the
method [13].

• Immersed boundary method for some wave equations Besides the issue of cardiac electro-
physiology, we also studied numerical schemes to study waves interacting with partially immersed
objects allowed to move freely in the vertical direction, and in a regime in which the propagation
of the waves is described by the one dimensional Boussinesq-Abbott system [23]. The problem
can be reduced to a transmission problem for this Boussinesq system, in which the transmission
conditions between the components of the domain at the left and at the right of the object are

Project CARMEN

13

determined through the resolution of coupled forced ODEs in time satisfied by the vertical dis-
placement of the object and the average discharge in the portion of the fluid located under the
object. We propose a new extended formulation in which these ODEs are complemented by two
other forced ODEs satisfied by the trace of the surface elevation at the contact points. The interest
of this new extended formulation is that the forcing terms are easy to compute numerically and
that the surface elevation at the contact points is furnished for free. Based on this formulation, we
propose a second order scheme that involves a generalization of the MacCormack scheme with
nonlocal flux and a source term, which is coupled to a second order Heun scheme for the ODEs. In
order to validate this scheme, several explicit solutions for this wave-structure interaction problem
are derived and can serve as benchmark for future codes. As a byproduct, our method provides a
second order scheme for the generation of waves at the entrance of the numerical domain for the
Boussinesq-Abbott system.

8.2 Modeling and inverse problems

• Modeling and in-silico trial for pacemakers We pursued our work within the H2020 SimCardioTest
European project, by using both 0D and 3D models of cardiac stimulation by a pacemaker, which
were derived in collaboration with Microport CRM, manufacturer. The models couple a model
of the pacemaker circuitry with cardiac tissue through boundary conditions which model the
polarization of the electrodes. First results were presented at FIMH 2023 [18]. The implementation
of the 3D model was made following high quality standards in order to match the Verification and
Validation standards of the V&V40 document [32], which gives a list a software requirements for the
Verification aspects. We are currently using data from bench experiments of optical mapping to
comply with the Validation items. In particular, we are calibrating parameters of the ionic models
using measured activation maps. This verification and validation process following the V& V40
guidelines was presented at the RICAM workshop on Cardiovascular Modeling and simulation in
2023 [20]. Finally, we designed a first in-silico clinical trial, that is described in a deliverable of the
European project (still not published). the question of interest for this trial concerns the changes of
the electrical capture properties of a pacemaker bradychardia lead with respect to some design
parameters, in the context where fibrosis develops at the tip lf the lead.

• The patchwork method for ECGi We propose a novel “patchwork method” (PM) [10], which
combines two classical numerical approaches for ECGI: the method of fundamental solutions (MFS)
and the finite-element method (FEM). We assume that the method with the smallest residual in the
predicted torso potentials provides the most accurate solution. These residuals were computed
using the boundaryelement method, and projected onto the heart surface using an orthogonal
projection. The PM then selects for each heart node and each time step the method whose
estimated reconstruction error is smallest. The performance of the PM was compared to both
FEM and MFS alone using simulated ectopic and normal ventricular activation beats. Results:
Cardiac potentials and activation maps obtained with the PM (CC=0.63±0.004 and 0.61±0.05
respectively) were more accurate than MFS (CC=0.61± 0.005 and 0.48±0.05 respectively) or FEM
(CC=0.58±0.009 and 0.51±0.02 respectively). The PM also succeeded in locating all epicardial
activation breakthrough sites, whereas the individual numerical methods usually missed one.
Moreover, the PM outperformed the other methods in the presence of Gaussian measurement
noise added to the torso surface potential distribution, showing its robustness and stability with
respect to noise. Conclusions: The PM overcomes some of the limitations of classical numerical
methods, improving the accuracy of mapping important features of activation during sinus rhythm
and paced beats.

• Electrical Impedance Tomography (EIT) We applied the immersed boundary scheme evocated
hereabove to the resolution of the inverse problem of Electrical Impedance Tomography. We
performed reconstructions of conductivites, contact impedances on electrodes and shape of the
considered domain of interest [13].

• A model for cardiac electroporation In the Dielectric project in collaboration with Inria Team
MONC and IHU Liryc, we derived formally a bidomain model at the tissue scale that takes into

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Inria Annual Report 2023

account the specificity of electroporation, which involves different time scales than the classical
bidomain model. This model was presented at the 2023 RICAM workshop [26].

• Comparison of different formulations for ECG computations We compared and numerically
studied two formulations that map the body surface potential maps from the transmembrane
voltage. Those formulations naturally emerge from the bidomain model. We determined which
formulation is the most relevant to use in an inverse resolution perpective. We developped a 2D
finite volume bidomain code, and compared simplified models with the bidomain [21].

• Impact of cardiac motion on ECGi solutions We conducted an investigation into the impact of
cardiac motion on both inverse and forward simulations, as well as the localization of sources from
ECGI outcomes. This study relied on clinical patient imaging data, generously provided by Simula
Research Laboratory, as part of a research visit conducted during the summer of 2023.

• Numerical Investigation of Methods Used In Commercial Clinical Devices for Solving the ECGI
Inverse Problem In this work, we assess two ECGI algorithms used in commercial ECGI systems
to solve the inverse problem; the Method of Fundamental Solutions (MFS) and the Equivalent
Single Layer (ESL). We quantify the performance of these two methods in conjunction with two
different activation maps to estimate the activation times and earliest activation sites (ADM et
TID). Results for clinical cases, indicate that ESL combined with ADM resulted in better localization
accuracy and, in contrast to simulated data, TID and ADM based earliest activation sites can be very
different. In fact, TID based activation maps is less robust to noisy and clinical data. This is mainly
due to the fact that TID calculates activation times for each cardiac node separately (thepoint of
maximum negative slope) without a spatial coherence. Consequently, in noisy data, it frequently
provides patchy patterns in the obtained maps. However, activation direction mapping provides
better results for clinical data despitethe fact that it tends to over-smooth the spread of activation,
which can bemisleading in the excitation origin localization. The post-processing methods and
in particular the activation times calculation have a significant impact on the computation of the
Activation map and concequently on PVC localization. [24]

• Inter-operator segmentation variability induces high premature ventricular contractions localiz-
ation uncertainty at the heart base Our main purpose is to evaluate the effect of the inter-operator
segmentation variability on the PVC localization. Eight different cardiac segmentations from the
same single subject CT-scans were performed by researchers within the consortium for Electrocardi-
ographic Imaging. For all generated meshes, eight ventricular stimulation protocols were used; left
and right ventricular free walls (LV, RV), apex, left and right ventricular outflow tract (LVOT, RVOT),
septum, and two locations at the left and right heart base (LVB, RVB). BSPs were generated using
computational models. We designed two test cases: with and without segmentation uncertainty.
We found that the high uncertainty is due to the variability of segmentations at the base of the heart.
These findings suggest that uncertainty in cardiac segmentation can have a significant impact on
ECGI and its interpretability in clinical applications; therefore, careful segmentation is strongly
recommended, especially at the base of the heart. [27]

8.3 Clinical applications

• Artificial Intelligence for Detection of Ventricular Oversensing Machine Learning Approaches for
Noise Detection Within Non-Sustained Ventricular Tachycardia Episodes Remotely Transmitted
by Pacemakers and Implantable Cardioverter Defibrillators Pacemakers (PMs) and implantable
cardioverter defibrillators (ICDs) increasingly automatically record and remotely transmit non-
sustained ventricular tachycardia (NSVT) episodes which may reveal ventricular oversensing. We
aimed at developing and validating a machine learning algorithm which accurately classifies NSVT
episodes transmitted by PMs and ICDs in order to lighten healthcare workload burden and improve
patient safety. PMs or ICDs (Boston Scientific) from four French hospitals with ≥ 1 transmitted
NSVT episode were split into three subgroups: training set, validation set, and test set. Each
NSVT episode was labelled as either physiological or non-physiological. Four machine learning
algorithms (2DTF-CNN, 2D-DenseNet, 2DTF-VGG, and 1D-AgResNet) were developed using a

Project CARMEN

15

training and validation dataset. Accuracies of the classifiers were compared with an analysis of the
remote monitoring team of the Bordeaux University Hospital using F2 scores (favoring sensitivity
over predictive positive value) using an independent test set. We used data collected from 807
devices that transmitted 10.471 NSVT recordings (82% ICD, 18% PM), of which 87 devices (10.8%)
transmitted 544 NSVT recordings with non-physiological signals. The classification by the remote
monitoring team resulted in an F2 score of 0,932 (sensitivity of 95%, specificity of 99%). The
four machine learning algorithms showed high and comparable F2 scores (2DTF-CNN: 0,914, 2D-
DenseNet: 0,906, 2DTF-VGG: 0,863, 1D-AgResNet: 0,791) and only 1D-AgResNet had significantly
different labeling as compared with the remote monitoring team. Our conclusion is that Machine
learning algorithms were accurate in detecting non-physiological signals within EGMs transmitted
by pacemaker and ICDs. We think that an artificial intelligence approach may render remote
monitoring less resourceful and improve patient safety. [15]

• Comparison of two segmentation software tools for deep brain stimulation of the subthalamic
and ventro-intermedius nuclei Deep brain stimulation (DBS) relies on precise targeting of key
structures such as the subthalamic nucleus (STN) for Parkinson’s disease (PD) and the ventro-
intermedius nucleus of the thalamus (Vim) for essential tremor (ET). Segmentation software, such
as GuideXT© de Boston Scientific and Suretune©, de Medtronic commercially available for atlas-
based identification of deep brain structures. However, no study has compared the concordance of
the segmentation results between the two software. We retrospectively compared the concordance
of segmentation of GuideXT© and Suretune© software by comparing the position of the segmented
key structures with clinically predicted targets obtained using the newly developed RebrAIn©
software as a reference. We targeted the STN in 44 MRI from PD patients (88 hemispheres) and the
Vim in 31 MRI from ET patients (62 hemispheres) who were elected for DBS. In 22 STN targeting
(25%), the target positioning was not correlating between GuideXT© and Suretune©. Regarding
the Vim, targets were located in the segmented Vim in 37%, the posterior subthalamic area (PSA)
in 60%, and the STN in 3% of the cases using GuideXT©; the proportions were 34%, 60%, and 6%,
respectively, using Suretune©. The mean distance from the centre of the RebrAIn© targeting to the
segmented Vim by Suretune© was closer (0.64 mm) than with GuideXT© (0.96 mm; p = 0.0004).
[12]

8.4 High performance computing and Microscopic models

• A population based study of the effect of ion concentrations on the ECG We have used a population
of models to investigate a problem faced by researchers who are trying to infer blood metabolyte
concentrations from the ECG. There is in most subjects a clear relation between ECG features and
concentrations of sodium and potassium, but these relations differ strongly between subjects. We
have shown that inter-subject differences in the heterogeneity of intrinsic cardiac cell properties
are a possible explanation for these differences [11].

• Computational methods for the microscopic EMI model The MICROCARD project has developed
numerical methods to simulate cardiac electrical activity on cell-by-cell (EMI) models: 1) efficient
higher-order time stepping achieved by combining low-overhead spatial adaptivity on the algeb-
raic level with progressive spectral deferred correction methods, and 2) substructuring domain
decomposition preconditioners tailored to address the complexities of our heterogeneous problem
structures. These methods have been tested using artificial 3D tissue geometries of upto a few
hundreds of cells that we generated [16, 19].

• Mesh of a 1 cubic millimeter of cardiac tissue In addition, thanks to improvements in the Mmg
code and in mesh generation software we were able to build such meshes of cardiac tissue structure
up to 1 cubic millimeter (7 thousand cells, 270 million tetrahedra), a larger volume than can be
simulated yet, without resorting to mesh replication. An HPC-capable version of the simulation
code is being developed which should be able to handle much larger cases.

• Mesh partitions that respect the geometry of cardiac cells We have also started to work on par-
titioning these meshes, which requires not only to balance the partitions in accordance with the

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Inria Annual Report 2023

target machine, but also to keep the cardiac cells intact within each partition. A first prototype was
written using the Metis library, and aims at being transferred to the OpenCARP software platoform.

• Finite volume methods for the microscopic EMI model We pursued our work [17] within the
MICROCARD European project. The Two-point flux approximation (TPFA) finite volume (FV)
scheme was generalized naturally to the extracellular-membrane-intracellular (EMI) model on an
admissibile orhtogonal mesh. Under strong regularity assumptions, an error estimates was derrived
on the electrical potentials and the transmembrne voltages as well in the case of single myocyte.
We believe that extending the proof to the case of many cardiac cells is straightforwad, and the
convergence analysis might be easily deduced from the existence proof in [33], even with minimal
regularity of the data. In fact, the ODEs from the non-standard transimission conditions on the cell
membrane, are coupled with large sets of nonlinear equations that require time-integration specific
to the EMI. Indeed, The FV method simplifies the implementation of this coupling by introducing
the a Dirichlet to Neuman operator to rewrite the problem as an evolution one on the membrane
only. We plan to implement the scheme and compare it to finite elements and a boundary elements
discretizations on simple 2D test cases. Afterwards, we aim to generalize the scheme to a FV-like
method that is more robust with respect to the more general meshes.

9 Bilateral contracts and grants with industry

Participants: Nejib Zemzemi.

9.1 Bilateral Grants with Industry

• RebrAIn and Inria contracted an agreement allowing Nejib Zemzemi to pass half of his time working

at RebrAIn. The startup RebrAIn has been co-founded by N. Zemzemi and E. Cuny.

• Lisl Weynans obtained a grant from Fondation EDF to fund a research project about Electrical

Impedance Tomography.

10 Partnerships and cooperations

10.1 International initiatives

10.1.1 Associate Teams in the framework of an Inria International Lab or in the framework of an

Inria International Program

SPICY

Title: Stochastic forward and inverse Problems In Cardiac electrophysiologY

Duration: 2021 ->

Coordinator: Mourad Bellasoued (mourad.bellassoued@enit.utm.tn)

Partners:

• Université de Tunis El Manar Tunis (Tunisie)

Inria contact: Mostafa Bendahmane

Summary: The electrocardiography imaging inverse problem is frequently solved using the deterministic
quasi-static models. These models don’t take into account the heart dynamic in time, channel
noise and external random perturbations acting in the torso. Recent numerical studies in the direct
problem have shown that such randomness cannot be suppressed. Occasionally deterministic

Project CARMEN

17

equations give qualitatively incorrect results. Therefore, it is important to quantify the nature
of the noise and choose an appropriate model incorporating randomness. In our project, we
study the inverse problem constrained by the stochastic monodomain or bidomain equations in
electrocardiology. The state equations consist in a coupled stochastic reaction-diffusion system
modelling the propagation of the intracelullar and extracellular electrical potentials, and stochastic
ionic currents in the heart. These equations are coupled to the stochastic quasi-static elliptic
equation in the torso. Thus, we will demonstrate that the novel concept of applying the stochastic
model will be useful to improve noninvasive reconstruction of electrical heart activity. We will
perform numerical experiments representing the effect of the stochastic heart dynamic on the
inverse solutions. Moreover, we will study the stability result for the conductivities and numerically
solve the parameters estimations problem in the stochastic model.

10.1.2 Participation in other International Programs

ECOS Nord

Participants:

Jacques Henry, Yves coudière.

Title: Qualitative and numerical analysis of inverse problems in cardiology

Partner Institution(s): Cuerpo Academico de Ecuaciones Diferenciales y Modelacion Matematica, Fac-

ultad de Ciencias Fisico Matematicas

• Benemerita Universidad Autonoma de Puebla, Mexico

Date/Duration: 2021-2025 (prolonged due to Covid)

Additionnal info/keywords:

ECOS Sud

Participants: Mostafa Bendahmane, Yves coudière.

Title: Virtual Element Methods for Different Bidomain Models for Cardiac Electrphysiology

Partner Institution(s): Departamento de Matemática, Facultad de Ciencias

• Universidad del Bio-Bio, Conception, Chile

Date/Duration: 2021-2024

Additionnal info/keywords:

10.2 International research visitors

10.2.1 Visits of international scientists

Other international visits to the team

Narjess Ben Abid

Status Intern

Institution of origin: ENIT TUNIS

Country: Tunisia

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Inria Annual Report 2023

Dates: Nov. 2023

Context of the visit:

Mobility program/type of mobility: Internship

Emna Bouaine

Status Intern

Institution of origin: ENIT TUNIS

Country: Tunisia

Dates: May 2023 to Oct 2023

Context of the visit:

Mobility program/type of mobility: Internship

Hamza Ammar

Status PhD

Institution of origin: University of Tunis El Manar

Country: Tunisia

Dates: May 2023 until Jun 2023

Context of the visit: SPICY associated team

Mobility program/type of mobility: research stay

Moises Soto Bajo

Status Researcher

Institution of origin: Benemerita Universidad Autonoma de Puebla

Country: Mexico

Dates: June 2023 (2 weeks)

Context of the visit: ECOS Nord project

Mobility program/type of mobility: research stay

Andres Fraguela

Status Researcher

Institution of origin: Benemerita Universidad Autonoma de Puebla

Country: Mexico

Dates: September 2023 (1 week)

Context of the visit: ECOS Nord project

Mobility program/type of mobility: research stay

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Project CARMEN

David Mora

Status Researcher

Institution of origin: Universidad del Bio Bio

Country: Chile

Dates: 2023 (1 week)

Context of the visit: ECOS Sud project

Mobility program/type of mobility: research stay

Veronica Anaya

Status Researcher

Institution of origin: Universidad del Bio Bio

Country: Chile

Dates: 2023 (1 week)

Context of the visit: ECOS Sud project

Mobility program/type of mobility: research stay

10.2.2 Visits to international teams

Research stays abroad

EmmaLagracie

Visited institution: Université d’Ottawa

Country: Canada

Dates: From August 11th to December 3rd 2023

Context of the visit: Mitacs exchange

Mobility program/type of mobility: Research stay under surpervision of Prof. Yves Bourgault

persNarimaneGassa

Visited institution: Simula Laboratory

Country: Norway

Dates: June 26th to August 18th, 2023

Context of the visit: PersonalizeAF

Mobility program/type of mobility: Research stay

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Inria Annual Report 2023

10.3 European initiatives

10.3.1 H2020 projects

MICROCARD

Participants:

Yves Coudière, Mark Potse, Zeina Chehade, Wissam Bouymedj, Laeti-
tia Mottet, Corentin Prigent.

MICROCARD project on cordis.europa.eu

Title: Numerical modeling of cardiac electrophysiology at the cellular scale

Duration: From April 1, 2021 to September 30, 2024

Partners:

• The Inria centers in Bordeaux and Nancy (as linked third party)

• Megware GmbH, Germany

• SIMULA Research Laboratory AS, Norway

• Université de Strasbourg (UNISTRA), France

• Zuse Institute Berlin, Germany

• Università della Svizzera italiana (USI), Switzerland

• Karlsruhe Institute of Technology (KIT), Germany

• Université de Bordeaux (UBx), France

• Università degli studi di Pavia (UNIPV), Italy

• Institut Polytechnique de Bordeaux (Bordeaux INP), France

• Numericor GmbH, Austria

• Orobix SRL (OROBIX), Italy

Inria contact: Mark Potse

Coordinator: Mark Potse

Summary: Cardiovascular diseases are the most frequent cause of death worldwide and half of these
deaths are due to cardiac arrhythmia, a disorder of the heart’s electrical synchronization system.
Numerical models of this complex system are highly sophisticated and widely used, but to match
observations in aging and diseased hearts they need to move from a continuum approach to
a representation of individual cells and their interconnections. This implies a different, harder
numerical problem and a 10,000-fold increase in problem size. Exascale computers will be needed
to run such models.

We propose to develop an exascale application platform for cardiac electrophysiology simulations
that is usable for cell-by-cell simulations. The platform will be co-designed by HPC experts, nu-
merical scientists, biomedical engineers, and biomedical scientists, from academia and industry.
We will develop, in concert, numerical schemes suitable for exascale parallelism, problem-tailored
linear-system solvers and preconditioners, and a compiler to translate high-level model descrip-
tions into optimized, energy-efficient system code for heterogeneous computing systems. The
code will be parallelized with a recently developed runtime system that is resilient to hardware
failures and will use an energy-aware task placement strategy.

The platform will be applied in real-life use cases with high impact in the biomedical domain and
will showcase HPC in this area where it is painfully underused. It will be made accessible for a wide
range of users both as code and through a web interface.

Project CARMEN

21

We will further employ our HPC and biomedical expertise to accelerate the development of parallel
segmentation and (re)meshing software, necessary to create the extremely large and complex
meshes needed from available large volumes of microscopy data.

The platform will be adaptable to similar biological systems such as nerves, and components of the
platform will be reusable in a wide range of applications.

SimCardioTest

Participants:

Yves Coudière, Michael Leguèbe, Gwladys Ravon, Valentin Pannetier,
Arthur Jean.

SimCardioTest project on cordis.europa.eu

Title: In silico testing and certification of healthcare products

Duration: From January 1, 2021 to December 30, 2024

Partners:

• Université de Bordeaux, France

• Universidad Pompeu Fabra, Spain

• Universitat Politecnica de Valencia, Spain

• SIMULA Research Laboratory AS, Norway

• INSILICOTRIALS Technologies S.P.A., Italy

• SORIN CRM SAS, France

• EXACTCURE, France

• Boston Scientific SCIMED INC, USA

• Virtual Physiological Human Institute for Integrative Biomedical Research VZW, Belgium

Inria contact: Yves Coudière

Coordinator: Maxime Sermesant

Summary: Computer modelling and simulation have the power to increase speed and reduce costs in
most product development pipelines. The EU-funded SimCardioTest project aims to implement
computer modelling, simulation and artificial intelligence to design and test cardiac drugs and med-
ical devices. Scientists will establish a platform for running in silico trials and obtaining scientific
evidence based on controlled investigations. The simulation of disease conditions and cohort
characteristics has the potential to overcome clinical trial limitations, such as under-representation
of groups. It also reduces the size and duration of human clinical trials as well as animal testing,
and offers robust, personalised information. Leveraging in silico technology in healthcare will
expedite product and drug certification and offer patients the best possible care.

Personalized AF

Participants: Nejib Zemzemi, Yves Coudière, Narimane Gassa.

PersonalizeAF project on cordis.europa.eu

Title: Personalized Therapies for Atrial Fibrillation. A Translational Approach

Duration: From 1st February 2020 to 31st January 2024

Inria Annual Report 2023

22

Partners:

• Karlsruhe Institute of Technology, Germany

• Universiteit Maastricht, Netherlands

• Universitätsklinikum Freiburg, Germany

• Université de Bordeaux, France

• The University of Oxford, United Kingdom

• CONSORCI Institut D’investigacions Biomediques AUGUST PI I SUNYER, Spain

• ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA, Italy

• SIMULA Research Laboratory AS, Norway

• Fundacion para la Investigacion Biomédica del Hospital Gregorio Maranon, Spain

• NCARDIA Services BV, Netherlands

• Fundacion para la Investigacion del Hoispital Universitario La Fe de la Comunidad Valenciana,

Spain

Inria contact: Nejib Zemzemi

Coordinator:

Summary: Atrial Fibrillation (AF) is the most common cardiac arrhythmia affecting more than 6 million

Europeans with a cost exceeding 1

PersonalizeAF addresses this challenge by delivering an innovative multinational, multi-sectorial,
and multidisciplinary research and training programme in new technologies and novel strategies
for individualized characterization of AF substrate to and increase treatments efficiency.

From the research point of view, PersonalizeAF will integrate data and knowledge from in-vitro, in
silico, ex vivo and in vivo animal and human models to: 1) generate an individual description of the
state of the atrial muscle identifying the disease mechanisms and characteristics; 2) understand
the potential effect that different therapies have on different atrial substrates; and 3) combine this
information to generate a specific profile of the patient and the best therapy for each patient.

With this purpose, PersonalizeAF partnership aggregates relevant scientific staff from the academic
and clinical world with highly specialised biomedical companies which will be involved in a
high-level personalised training programme that will train a new generation of highly skilled
professionals and guarantee ESRs and future PhD students outstanding Career Opportunities in
the biomedical engineering, cardiology services and medical devices sectors. PersonalizeAF will
disseminate results to a wide spectrum of stakeholders, create awareness in the general public
about atrial fibrillation and encourage vocational careers among young students.

10.4 National initiatives

ANR MAESTRO The ANR project MAESTRO (Magnetic Signal detection of ventricular arrhythmOgenic
substrates), coordinated by Prof. Michel Haïssaguerre (IHU Liryc), has a computational component for
which we recruited a postdoc from December 2022 to mid-November 2023, directed by Mark Potse.

GENCI GENCI project A0130307379, Interaction between tissue structure and ion-channel function
in cardiac arrhythmia, coordinated by Mark Potse, comprises 2.35 million core-hours on the national
supercomputers Zay and Joliot-Curie. Compared to previous years it is a modest allocation. This is
because most of our computational needs in 2023 are either smaller or larger than the national scale.

Project CARMEN

23

Dielectric project The Dielectric project, co-funded by the Federation Française de Cardiologie and
Inria, started in January 2023, and is co-piloted by Pr. Pierre Jaïs (IHU Liryc) and Clair Poignard (Inria
MONC). It aims at a better understanding of cardiac ablation by electroporation. Both Inria teams MONC
and CARMEN are involved, with the PhD of Simon Bihoreau, co-directed by Annabelle Collin (MONC)
and Michael Leguèbe (CARMEN).

ANR Mire4VTach PI Annabelle Collin (Inria MONC), started late 2023. Michael Leguèbe contributes in
Mire4VTach, another project on cardiac electroporation which is more focused on the application and
confrontation with data than the work in the Dielectric project. Mire4Tach also involves people from
Inria MONC, CARMEN and IHU Liryc.

10.5 Regional initiatives

EITCardio

Participants:

Laura Bear, Yves Coudière, Charles Pierre, Bénédicte Puig, Lisl Weyn-
ans.

Title: EITCardio

Duration: From September 2023 to September 2027

Partners:

• Inria Bordeaux Sud-Ouest

• IHU-liryc

• Université de Pau et des Pays de l’Adour

Inria contact: Lisl Weynans

Coordinator: Lisl Weynans

Summary: The objective of this project is to develop mathematical methods for solving Electrical Im-
pedance Tomography (EIT) to enhance the resolution of the ECGi (Electrocardiographic Imaging)
problem and validate them experimentally. Specifically, the project consists of two parts:

Development of mathematical and numerical methods to solve the inverse problem of EIT in
the torso and identify influential parameters for the propagation of the electric field, such as
conductivities and organ movements.

Experimental validation of the ECGi + EIT coupling. This experimental validation will be conduc-
ted first within the experimental setup, the torso tank, currently available at Liryc, which allows
measurements for ECGi in a controlled environment. Subsequently, it will be conducted as in-vivo
experiments, meaning a context closer to clinical reality.

ATLAS-RVA

Participants:

Peter Langfied, Karim Benali.

Title: Atlas of normal and pathological ventricular Repolarization patterns and correlation with clinical

re-entrant Ventricular Arrhythmias

Duration: From January 2024 to December 2025

Partners:

24

Inria Annual Report 2023

• Inria Bordeaux Sud-Ouest

• IHU-liryc

Inria contact: Peter Langfield

Coordinator: Peter Langfield

Summary: The project aims to study the variability of patterns of ventricular repolarization times in

healty and unhealthy patients, and explore the role of such patterns.

The main objective of the project is to perform a statistical assessment of patterns of ventricular
repolarization time via unipolar electrogram annotations from CARTO datasets, from roughly two
hundred datasets from data centers across France. The cruicial difference between this project and
previous work, is that specific filtering settings were imposed for the data acquisition that make the
annotations reliable. The project will exploit this particular setting and the large volumes of data,
to exlpore and assess alternative methods of repolarization time annotation. Finally, the project
will study cases of ventricular tachycardia with the aim of ellucidating the role of repolarization
time patterns and also the associated resitituion properties of the tissue.

Peter Langfield Nejib Zemzemi Yves Coudière Corentin Prigent Laetitia Mottet Mark Potse Michael Leguebe
Lisl Weynans Mostafa Bendahmane Emma Lagracie Niami Nasr Valentin Pannetier Zeina Chehade

11 Dissemination

11.1 Promoting scientific activities

11.1.1 Scientific events: organisation

General chair, scientific chair

• Yves Coudière: chair of the organisation of the General Assembly of the SimCardioTest project,

March, 20-21, 2023

• Yves Coudière: organisation of the first InnovaHeart day, Bordeaux, March, 22nd, 2023, see video

Member of the organizing committees

• Peter Langfield: Co-organizer of mini-symposium at EQUADIFF 2024 conference.

11.1.2 Scientific events: selection

Member of the conference program committees

• Yves Coudière, Nejib Zemzemi: Program Committee for the FIMH 2023 international conference

• Yves Coudière: program Committe for the first LiryConnect days, November 14-15, 2023

11.1.3 Invited talks

• Yves Coudière, invited talk at RICAM Workshop 2 on Cardiovascular Modeling and Simulation,

2023-11-13 to 2023-11-17, Linz, Austria.

• Yves Coudière, invited talk at the JPVV66 workshop in honor of J.-P. Vila, 2023-04-04 to 2023-04-06,

Banyuls, France.

• Mark Potse. MICROCARD Overview. openCARP User Meeting, Karlsruhe, Germany, May 2023.

• Corentin Prigent and Laetitia Mottet. Meshing with the Mmg platform. openCARP User Meeting,

Karlsruhe, Germany, May 2023.

Project CARMEN

25

• Laetitia Mottet. Challenges in meshing tissue at the micro-scale for cardiac modeling. IHU Liryc

International Scientific Workshop, Pessac, France, November 2023.

• Mark Potse. Large Numerical modeling of cardiac electrophysiology at the cellular scale. EuroHPC
Summit: European Supercomputing Excellence in the Exascale Era, Göteborg, Sweden, March
2023.

• Mark Potse. Digital Twins in Cardiology. Inserm/Inria Digital Twins for Health seminar, Brussels, 28

March 2023.

• Mark Potse. Simulating Cardiac Electrophysiology: The Quest for Detail and Diversity. Keynote talk

at the Measurement Science congress, Smolenice, Chech republic, 29 May 2023.

• Mark Potse. Numerical modeling of cardiac electrophysiology at the cellular scale. IHU Liryc

International Scientific Workshop, November 2023.

• Mark Potse. Numerical modeling of cardiac electrophysiology at the cellular scale. Symposium

“Where computation meets cardiology”, Maastricht, The Netherlands, November 2023.

• Lisl Weynans, seminar of laboratory MIP, Toulouse

• Lisl Weynans, seminar of laboratory LMAP, Pau

11.1.4 Leadership within the scientific community

Mark Potse is leading the H2020-EuroHPC MICROCARD project, strengthening his role as a European
leader in the scientific community.

11.1.5 Scientific expertise

• Peter Langfield: Project reviewer for a proposal at Heart Research UK (HRUK).

• Yves Coudière: diverse expertises, including applications to IHU Liryc internal call, CIFRE applica-

tions, Inserm projects.

• Mark Potse: associate editor for Frontiers in Cardiac Electrophysiology, reviewer for several journals

and congresses.

11.1.6 Research administration

• Comité de direction IHU Liryc: Yves Coudière participates to these bi-monthly commmittees

• Conseil scientifique IHU Liryc: Yves Coudière, Michael Leguèbe, Mark Potse participate to the

scientific committe of IHU Liryc (a few meetings in 2023)

• Mark Potse is a member of the IDRIS user committee

• Lisl Weynans is a member of the BCP of Bordeaux Sud Ouest Inria center.

11.2 Teaching - Supervision - Juries

11.2.1 Teaching

The 2 assistant professors and 1 professor of the team teach at several levels of the Bordeaux University
programs in Mathematics, Neurosciences, and Medicine (respectively, 192, 192 and 96 h/year on average).
The researchers also have a regular teaching activity, contributing to several courses in the Applied
Mathematics at the Bachelor and Master levels (between 16 and 72 h/year).

The PhD students who ask for it are used to teach between 32 and 64 h/year, usually courses of general

mathematics in L1 or mathematics for biologists in L1 or L2.

Typical courses taught by team members (L for Bachelor level, M for Master level):

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Inria Annual Report 2023

• Numerical analysis (L2)

• Programming for scientific computing with C++ (L3) and Modern Fortran (M1)

• Solving sparse linear systems (L3)

• Numerical approximation of PDEs: Finite Differences, Finite Elements, Finite Volumes (M1, M2)

• Supervision of programming projects (L3, M1)

• Linear Algebra, Optimization under constraints (L2 and Essca school)

• Analysis, L2

• Computational Neurosciences, M2

• Neuropsychology and Psychophysiology, L3

• Physics for students in medicine, one lecture on cardiac modelling

11.2.2 Juries

• Yves Coudière: member of the jury for the PhD of N. Nasr (University of Bordeaux), reviewer and

member of the jury for the PhD of L. Gander (Universita della Svizzera Italiana)

• Lisl Weynans: member of the jury for the PhD of N. Nasr

• Mark Potse: co-advisor of Hassaan Bukhari (PhD defense in February 2023)

• Lisl Weynans: member of the jury for the PhD of T. Carlier (Bordeaux), for the PhD of Z.Yang

(Paris-Saclay)

• Lisl Weynans: reviewer of the PhD manuscript of C. Chambon (CNAM Paris), of the PhD manuscript

of L. Salomon (Ensta Bretagne)

11.2.3 Teaching administration

• Yves Coudière: elected member of the conseil du département des Sciences et Technologies of
Bordeaux University. The committe votes on all matters related to teaching at the University in the
domain of sciences and technologies.

• Yves Coudière: elected member of the conseil de l’Unité de Formation Mathématiques et Interac-
tion. This committee discusses and votes on all matters related to teaching in the department of
mathematics, providing helpful decisions to the above committee.

• Lisl Weynans: responsible for the Licence de Mathématique parcours ingénierie mathématique (i.e.

Bachelor on applied mathematics),

• Lisl Weynans: responsible for a course (called mineure Mathématiques du parcours International

de la Licence,

• Mostafa Bendahmane: responsible for international mobility of students from the Licence MIASHS,

which is the Bachelor on mathmatics applied to social and human sciences.

11.3 Popularization

11.3.1 Articles and contents

• Yves Coudière: radio interview for Radio Campus at the Nuit Européenne de Chercheurs 2023.

• Videos on digital twins for cardiology from the InnovaHeart day: main video, Episode 1: Why create
a digital heart twin?, Episode 2 : How are you contributing ?, 3- What motivates your work on the
heart’s digital twin?, 4: What are the remaining challenges?.

Project CARMEN

11.3.2 Education

27

• Whole team: participation to welcoming high school pupils for short internships.

• Laetitia Mottet: CHICHE at Lycée (high school) Jay de Beaufort, Périgueux, December 2023.

• Yves Coudière: CHICHE at 3 Lycées (high school), January, February, November 2023.

• Yves Coudière: small workshop for high school pupils during the Fête de la Science 2023.

11.3.3 Interventions

• Moi Mathématicienne, Moi Informaticienne (MIMM) : organisation (L. Weynans) and participation
(L. Weynans, E. Lagracie) to a week organized during school holidays to welcome young women
high-school students at the University.

• During the GA of SimCardiotest, on March, 21, we organized a small exchange between cardiologists,
representatives of patients’ organizations, and scientists to discuss on in-silico trial and related
issues in science and the society.

12 Scientific production

12.1 Major publications

[1] B. Andreianov, M. Bendahmane, K. H. Karlsen and C. Pierre. ‘Convergence of discrete duality finite
volume schemes for the cardiac bidomain model’. Anglais. In: Networks and Heterogeneous Media
6.2 (2011), pp. 195–240. URL: http://hal.archives-ouvertes.fr/hal-00526047.

[2] A. Azzouzi, Y. Coudière, R. Turpault and N. Zemzemi. ‘A mathematical model of Purkinje-Muscle

Junctions’. In: Mathematical Biosciences and Engineering 8.4 (2011), pp. 915–930.

[3] Y. Coudière and C. Pierre. ‘Stability And Convergence Of A Finite Volume Method For Two Systems
Of Reaction-Diffusion Equations In Electro-Cardiology’. In: Nonlinear Anal. Real World Appl. 7.4
(2006), pp. 916–935. URL: http://hal.archives-ouvertes.fr/hal-00016816/fr.

[4] Y. Coudière, C. Pierre, O. Rousseau and R. Turpault. ‘A 2D/3D Discrete Duality Finite Volume
Scheme. Application to ECG simulation’. In: International Journal on Finite Volumes 6.1 (2009).
URL: http://hal.archives-ouvertes.fr/hal-00328251/fr.

[5] Y. Bourgault, Y. Coudière and C. Pierre. ‘Existence And Uniqueness Of The Solution For The Bido-
main Model Used In Cardiac Electrophysiology’. In: Nonlinear Anal. Real World Appl. 10.1 (2009),
pp. 458–482. URL: http://hal.archives-ouvertes.fr/hal-00101458/fr.

[6] P. W. Macfarlane, C. Antzelevitch, M. Haïssaguerre, H. V. Huikuri, M. Potse, R. Rosso, F. Sacher,
J. T. Tikkanen, H. Wellens and G.-X. Yan. ‘The Early Repolarization Pattern; A Consensus Paper’. In:
Journal of the American College of Cardiology 66 (2015), pp. 470–477. URL: http://dx.doi.org/1
0.1016/j.jacc.2015.05.033.

[7] V. M. F. Meijborg, M. Potse, C. E. Conrath, C. N. W. Belterman, J. M. T. de Bakker and R. Coronel.
‘Reduced Sodium Current in the Lateral Ventricular Wall Induces Inferolateral J-Waves’. In: Front
Physiol 7.365 (Aug. 2016). DOI: 10.3389/fphys.2016.00365. URL: https://hal.inria.fr/hal
-01386905.

[8] C. Pierre. ‘Preconditioning the bidomain model with almost linear complexity’. In: Journal of
Computational Physics 231.1 (Jan. 2012), pp. 82–97. DOI: 10.1016/j.jcp.2011.08.025. URL:
http://www.sciencedirect.com/science/article/pii/S0021999111005122.

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Inria Annual Report 2023

12.2 Publications of the year

International journals

[9] M. Bendahmane, F. Karami, E. Erraji, A. Atlas and A. Afraites. ‘Optimal control for a two-sidedly
degenerate aggregation equation’. In: Nonlinear Analysis: Modelling and Control (4th June 2023).
DOI: 10.15388/namc.2023.28.32395. URL: https://hal.science/hal-04124303.

[10] O. Bouhamama, M. Potse, L. Bear and L. Weynans. ‘A Patchwork Method to Improve the Perform-
ance of Current Methods for Solving the Inverse Problem of Electrocardiography’. In: IEEE Transac-
tions on Biomedical Engineering 70.1 (Jan. 2023), pp. 55–66. DOI: 10.1109/TBME.2022.3184473.
URL: https://inria.hal.science/hal-03913730.

[11] H. A. Bukhari, C. Sánchez, P. Laguna, M. Potse and E. Pueyo. ‘Differences in ventricular wall
composition may explain inter-patient variability in the ECG response to variations in serum
potassium and calcium’. In: Frontiers in Physiology 14 (11th Oct. 2023), p. 1060919. DOI: 10.3389
/fphys.2023.1060919. URL: https://inria.hal.science/hal-04407773.

[12] P.-E. Constanthin, N. Zemzemi, E. Cuny and J. Engelhardt. ‘Comparison of two segmentation
software tools for deep brain stimulation of the subthalamic and ventro-intermedius nuclei’. In:
Acta Neurochirurgica (23rd Oct. 2023). DOI: 10.1007/s00701-023-05819-9. URL: https://inr
ia.hal.science/hal-04241567.

[13]

J. Dardé, N. Nasr and L. Weynans. ‘Immersed Boundary Method for the Complete Electrode
Model in Electrical Impedance Tomography’. In: Journal of Computational Physics 487 (Aug. 2023),
p. 112150. DOI: 10.1016/j.jcp.2023.112150. URL: https://hal.science/hal-03904013.

[14] F. L. P. dos Santos, M. Bendahmane, E. Erraji and F. Karami. ‘A continuous spatial and temporal
mathematical model for assessing the distribution of dengue in Brazil with control’. In: Journal of
Biological Systems 31.02 (13th June 2023), pp. 345–373. DOI: 10.1142/S0218339023300026. URL:
https://hal.science/hal-04127091.

[15] M. Strik, B. Sacristan, P. Bordachar, J. Duchateau, R. Eschalier, P. Mondoly, J. Laborderie, N. Gassa,
N. Zemzemi, M. Laborde, J. Garrido, C. M. Perabla, G. Jimenez-Perez, O. Camara, M. Haïssaguerre,
R. Dubois and S. Ploux. ‘Artificial Intelligence for Detection of Ventricular Oversensing Machine
Learning Approaches for Noise Detection Within Non-Sustained Ventricular Tachycardia Epis-
odes Remotely Transmitted by Pacemakers and Implantable Cardioverter Defibrillators’. In: Heart
Rhythm (July 2023). DOI: 10.1016/j.hrthm.2023.06.019. URL: https://inria.hal.science
/hal-04155080.

International peer-reviewed conferences

[16] F. Chegini, A. Froehly, N. M. M. Huynh, L. F. Pavarino, M. Potse, S. Scacchi and M. Weiser. ‘Efficient
numerical methods for simulating cardiac electrophysiology with cellular resolution’. In: 10th Inter-
national Conference on Computational Methods for Coupled Problems in Science and Engineering.
Chania, Greece, 5th June 2023. URL: https://inria.hal.science/hal-04407791.

[17] Z. Chehade and Y. Coudière. ‘The Two-Point Finite Volume Scheme for the Microscopic Bidomain
Model of Electrocardiology’. In: FVCA 10 - Finite Volume for Complex applications 10. Strasbourg,
France, 30th Oct. 2023. URL: https://inria.hal.science/hal-04403881.

[18] V. Pannetier, M. Leguèbe, Y. Coudière, R. D. Walton, P. Dhiver, D. Feuerstein and D. Amaro. ‘Modeling
Cardiac Stimulation by a Pacemaker, with Accurate Tissue-Electrode Interface’. In: FIMH 2023
- 12th International Conference on Functional Imaging and Modeling of the Heart. Vol. 13958.
Lecture Notes in Computer Science. Villeurbanne (Lyon), France: Springer Nature Switzerland,
16th June 2023, pp. 194–203. DOI: 10.1007/978-3-031-35302-4_20. URL: https://inria.hal
.science/hal-04379089.

[19]

J. Steyer, F. Chegini, M. Potse, A. Loewe and M. Weiser. ‘Continuity of Mircoscopic Cardiac Con-
duction in a Computational Cell-by-Cell Model’. In: 2023 Computing in Cardiology Conference.
Atlanta (GA), United States, 1st Oct. 2023. DOI: 10.22489/CinC.2023.385. URL: https://inria
.hal.science/hal-04407818.

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29

Conferences without proceedings

[20] Y. Coudière, G. Ravon, V. Pannetier and M. Leguèbe. ‘Numerical simulation of cardiac pacing
devices: modeling and validation issues’. In: RICAM 2023 - Workshop on Cardiovascular Modeling
and Simulation. Linz, Austria, 16th Nov. 2023. URL: https://hal.science/hal-04402791.

[21] E. Lagracie, L. Weynans and Y. Coudière. ‘Comparison of Two Formulations for Computing Body
Surface Potential Maps’. In: 2023 Computing in Cardiology Conference. Atlanta, France, 26th Dec.
2023. DOI: 10.22489/CinC.2023.106. URL: https://inria.hal.science/hal-04405814.

Doctoral dissertations and habilitation theses

[22]

S. H. A. Bukhari. ‘Estimation of Serum Potassium and Calcium Concentrations from Electrocardio-
graphic Depolarization and Repolarization Waveforms’. Université de Bordeaux; Universidad de
Zaragoza (Espagne), 2nd Mar. 2023. URL: https://theses.hal.science/tel-04077621.

Reports & preprints

[23] G. Beck, D. Lannes and L. Weynans. A NUMERICAL METHOD FOR WAVE-STRUCTURE INTERAC-

TIONS IN THE BOUSSINESQ REGIME. July 2023. URL: https://hal.science/hal-04151128.

[24] N. Gassa, V. Kalinin and N. Zemzemi. Numerical Investigation of Methods Used In Commercial
Clinical Devices for Solving the ECGI Inverse Problem. 9th June 2023. URL: https://hal.science
/hal-04124322.

[25] C. E. Heaney, J. Tang, J. Yan, D. Guo, J. Ipock, S. Kaluvakollu, Y. Lin, D. Shao, B. Chen, L. Mottet, P.
Kumar and C. C. Pain. Data Assimilation with Machine Learning for Dynamical Systems: Modelling
Indoor Ventilation. 13th Jan. 2023. URL: https://inria.hal.science/hal-03938455.

Other scientific publications

[26] S. Bihoreau, G. Caluori, A. Collin, P. Jaïs, M. Leguèbe and C. Poignard. ‘Mathematical Modeling
of Pulsed Electric Field Cardiac Ablation’. In: RICAM - Workshop 4 "Modeling and simulation of
ablation treatments". Linz, Austria, 28th Nov. 2023. URL: https://hal.science/hal-04389083.

[27] N. Gassa, J. Tate, M. Boonstra, B. Ondrusova, J. Svehlikova, R. Macleod and N. Zemzemi. ‘Inter-
operator segmentation variability induces high premature ventricular contractions localization
uncertainty at the heart base’. In: Heart Rhythm 2023 - The Society’s 44th annual meeting. New
Orleans (LA), United States, May 2023. URL: https://hal.science/hal-04124313.

[28] V. Pannetier, Y. Coudière and M. Leguèbe. ‘Standardized numerical simulations of cardiac electrical
stimulation devices’. In: Journée annuelle de l’EDMI. Bordeaux (France), France, 6th Apr. 2023.
URL: https://inria.hal.science/hal-04384583.

[29] V. Pannetier, M. Leguèbe, Y. Coudière, R. D. Walton, D. Feuerstein, D. Amaro and P. Dhiver. ‘Modeling
Cardiac Stimulation by a Pacemaker, with Accurate Tissue-Electrode Interface’. In: FIMH 2023 -
12th International Conference on Functional Imaging and Modeling of the Heart. Villeurbanne
(Lyon), France, 19th June 2023. URL: https://inria.hal.science/hal-04384661.

[30] V. Pannetier, G. Ravon, M. Leguèbe, Y. Coudière, R. D. Walton, D. Feuerstein, G. Fauré, D. Amaro
and P. Dhiver. ‘From experimental data to 3D realistic simulations: a pacemaker example’. In:
LIRYConnect 2023. Pessac (Bordeaux), France, 2023. URL: https://inria.hal.science/hal-0
4384800.

12.3 Cited publications

[31] A. Arrieula, H. Cochet, P. Jaïs, M. Haïssaguerre and M. Potse. ‘An Improved Iterative Pace-Mapping
Algorithm to Detect the Origin of Premature Ventricular Contractions’. In: Computing in Cardiology.
Vol. 47. Rimini: Computing in Cardiology, 2020, p. 62. DOI: 10.22489/CinC.2020.062.

[32] Assessing the credibility of computational modeling through verification and validation: Application

to medical devices. en. 2018.

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Inria Annual Report 2023

[33] P.-E. Bécue, F. Caro, M. Bendahmane and M. Potse. ‘Modélisation et simulation de l’électrophysiologie

cardiaque à l’échelle microscopique’. In: 43e Congrès National d’Analyse Numérique (CANUM).
SMAI. Obernai, Alsace, France, May 2016. URL: http://smai.emath.fr/canum2016/resumes
PDF/peb/Abstract.pdf.

[34] P.-E. Bécue, F. Caro, M. Potse and Y. Coudière. Theoretical and Numerical Study of Cardiac Electro-
physiology Problems at the Microscopic Scale. SIAM Conference on the Life Sciences (LS16). Poster.
July 2016. URL: https://hal.inria.fr/hal-01405837.

[35] P.-E. Bécue, M. Potse and Y. Coudière. ‘A Three-Dimensional Computational Model of Action
Potential Propagation Through a Network of Individual Cells’. In: Computing in Cardiology 2017.
Rennes, France, Sept. 2017, pp. 1–4. URL: https://hal.inria.fr/hal-01592178.

[36] P.-E. Bécue, M. Potse and Y. Coudière. ‘Microscopic Simulation of the Cardiac Electrophysiology: A
Study of the Influence of Different Gap Junctions Models’. In: Computing in Cardiology. Maastricht,
Netherlands, Sept. 2018. URL: https://hal.inria.fr/hal-01910679.

[37] B. Berte, F. Sacher, S. Mahida, S. Yamashita, H. S. Lim, A. Denis, N. Derval, M. Hocini, M. Haïs-
saguerre, H. Cochet and P. Jaïs. ‘Impact of Septal Radiofrequency Ventricular Tachycardia Ablation;
Insights From Magnetic Resonance Imaging’. In: Circulation 130 (2014), pp. 716–718. URL: https:
//www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.114.010175.

[38]

J. Chamorro Servent, L. Bear, J. Duchateau, M. Potse, R. Dubois and Y. Coudière. ‘Do we need to
enforce the homogeneous Neuman condition on the Torso for solving the inverse electrocardi-
ographic problem by using the method of fundamental solution ?’ In: Computing in Cardiology
2016. Vol. 43. Computing in Cardiology 2016. Vancouver, Canada, Sept. 2016, pp. 425–428. URL:
https://hal.inria.fr/hal-01379236.

[39] Y. Coudière, Y. Bourgault and M. Rioux. ‘Optimal monodomain approximations of the bidomain
equations used in cardiac electrophysiology’. In: Mathematical Models and Methods in Applied
Sciences 24.6 (Feb. 2014), pp. 1115–1140. URL: https://hal.inria.fr/hal-00644257.

[40]

J. Duchateau, M. Potse and R. Dubois. ‘Spatially Coherent Activation Maps for Electrocardiographic
Imaging’. In: IEEE Transactions on Biomedical Engineering 64 (May 2017), pp. 1149–1156. DOI:
10.1109/TBME.2016.2593003. URL: https://hal.inria.fr/hal-01386890.

[41] A. Gharaviri, M. Potse, S. Verheule, R. Krause, A. Auricchio and U. Schotten. ‘Epicardial Fibrosis Ex-
plains Increased Transmural Conduction in a Computer Model of Atrial Fibrillation ’. In: Computing
in Cardiology. Vancouver, Canada, Sept. 2016. URL: https://hal.inria.fr/hal-01386916.

[42] M. Haïssaguerre, P. Jaïs, D. C. Shah, S. Garrigue, A. Takahashi, T. Lavergne, M. Hocini, J. T. Peng, R.
Roudaut and J. Clémenty. ‘Spontaneous initiation of atrial fibrillation by ectopic beats originating
in the pulmonary veins’. In: N. Engl. J. Med. 339 (1998), pp. 659–666. URL: https://www.nejm.or
g/doi/full/10.1056/NEJM199809033391003.

[43] M. Haïssaguerre, N. Derval, F. Sacher, L. Jesel, I. Deisenhofer, L. de Roy, J. L. Pasquié, A. Nogami,
D. Babuty, S. Yli-Mayry, C. De Chillou, P. Scanu, P. Mabo, S. Matsuo, V. Probst, S. Le Scouarnec,
P. Defaye, J. Schlaepfer, T. Rostock, D. Lacroix, D. Lamaison, T. Lavergne, Y. Aizawa, A. Englund,
F. Anselme, M. O’Neill, M. Hocini, K. T. Lim, S. Knecht, G. D. Veenhuyzen, P. Bordachar, M. Chauvin,
P. Jaïs, G. Coureau, G. Chene, G. J. Klein and J. Clémenty. ‘Sudden cardiac arrest associated with
early repolarization’. In: N. Engl. J. Med. 358 (2008), pp. 2016–2023.

[44] M. G. Hoogendijk, M. Potse, A. C. Linnenbank, A. O. Verkerk, H. M. den Ruijter, S. C. M. van
Amersfoorth, E. C. Klaver, L. Beekman, C. R. Bezzina, P. G. Postema, H. L. Tan, A. G. Reimer, A. C.
van der Wal, A. D. J. ten Harkel, M. Dalinghaus, A. Vinet, A. A. M. Wilde, J. M. T. de Bakker and
R. Coronel. ‘Mechanism of Right Precordial ST-Segment Elevation in Structural Heart Disease:
Excitation Failure by Current-to-Load Mismatch’. In: Heart Rhythm 7 (2010), pp. 238–248. URL:
http://dx.doi.org/10.1016/j.hrthm.2009.10.007.

[45] M. L. Hubbard and C. S. Henriquez. ‘A microstructural model of reentry arising from focal break-
through at sites of source-load mismatch in a central region of slow conduction’. In: Am. J. Physiol.
Heart Circ. Physiol. 306 (2014), H1341–1352.

Project CARMEN

31

[46] M. Kania, Y. Coudière, H. Cochet, M. Haissaguerre, P. Jaïs and M. Potse. ‘A new ECG-based method
to guide catheter ablation of ventricular tachycardia’. In: iMAging and eLectrical Technologies.
Uppsala, Sweden, Apr. 2018. URL: https://hal.inria.fr/hal-01910709.

[47] M. Potse. ‘Scalable and Accurate ECG Simulation for Reaction-Diffusion Models of the Human
Heart’. In: Frontiers in Physiology 9 (Apr. 2018), p. 370. DOI: 10.3389/fphys.2018.00370. URL:
https://hal.inria.fr/hal-01910637.

[48] M. Potse, L. Cirrottola and A. Froehly. ‘A practical algorithm to build geometric models of cardiac
muscle structure’. In: ECCOMAS 2022 - The 8th European Congress on Computational Methods in
Applied Sciences and Engineering. Oslo, Norway, June 2022. URL: https://inria.hal.science
/hal-03936963.

[49] M. Potse, B. Dubé, J. Richer, A. Vinet and R. M. Gulrajani. ‘A Comparison of monodomain and
bidomain reaction-diffusion models for action potential propagation in the human heart’. In: IEEE
Transactions on Biomedical Engineering 53.12 (2006), pp. 2425–2435. URL: http://dx.doi.org/1
0.1109/TBME.2006.880875.

[50] M. Potse, B. Dubé and A. Vinet. ‘Cardiac Anisotropy in Boundary-Element Models for the Electro-
cardiogram’. In: Medical and Biological Engineering and Computing 47 (2009), pp. 719–729. URL:
http://dx.doi.org/10.1007/s11517-009-0472-x.

[51] M. Potse, A. Gharaviri, S. Pezzuto, A. Auricchio, R. Krause, S. Verheule and U. Schotten. ‘Anatomically-
induced Fibrillation in a 3D model of the Human Atria’. In: Computing in Cardiology. Maastricht,
Netherlands, Sept. 2018. URL: https://hal.inria.fr/hal-01910674.

[52] M. Potse, V. M. F. Meijborg, C. N. W. Belterman, J. M. T. de Bakker, C. E. Conrath and R. Coronel.
Regional conduction slowing can explain inferolateral J waves and their attenuation by sodium
channel blockers. Annual workshop of Liryc - Electrophysiology and heart modeling institute.
Poster. Sept. 2016. URL: https://hal.inria.fr/hal-01393102.

[53] M. Potse, E. Saillard, D. Barthou and Y. Coudière. ‘Feasibility of Whole-Heart Electrophysiological
Models With Near-Cellular Resolution’. In: CinC 2020 - Computing in Cardiology. Rimini / Virtual,
Italy, Sept. 2020. DOI: 10.22489/CinC.2020.126. URL: https://hal.inria.fr/hal-0294351
3.

[54] A. Tveito, K. H. Jæger, M. Kuchta, K.-A. Mardal and M. E. Rognes. ‘A Cell-Based Framework for

Numerical Modeling of Electrical Conduction in Cardiac Tissue’. In: Front. Phys. 5 (2017), p. 48.
<scratchpad>
- Main topic: Research Centre CARMEN (Inria Centre at the University of Bordeaux)
- Key points:
  - Develops and uses models and numerical methods to simulate cardiac electrophysiology
  - Focuses on understanding normal and pathological cardiac electrophysiology
  - Explores the relation between molecular processes and measurable signals
  - Works on incorporating new biological knowledge into models
  - Collaborates with physiologists and cardiologists
- Structure: The document is organized into sections, including Activity Report, Project-Team CARMEN, Domain, Theme, and so on.
- Potential artifacts to ignore: Links, HTML tags, and other web-related elements
</scratchpad>

<final_summary>
The CARMEN project is a research centre at the University of Bordeaux, focusing on developing and using models and numerical methods to simulate cardiac electrophysiology. The team aims to understand normal and pathological cardiac electrophysiology, exploring the relation between molecular processes and measurable signals. They collaborate with physiologists and cardiologists to incorporate new biological knowledge into their models. The project's research program includes complex models for action potential propagation, simplified models and inverse problems, numerical techniques, and more. The CARMEN team has made significant contributions to the field, including the development of new software and platforms, such as CEPS, OptimDBS, and MUSIC. Their research has the potential to improve our understanding of cardiac arrhythmias and develop more effective treatments.
The CARMEN project is a research centre at the University of Bordeaux, focusing on developing and using models and numerical methods to simulate cardiac electrophysiology. The team aims to understand normal and pathological cardiac electrophysiology, exploring the relation between molecular processes and measurable signals. They collaborate with physiologists and cardiologists to incorporate new biological knowledge into their models. The project's research program includes complex models for action potential propagation, simplified models and inverse problems, numerical techniques, and more. The CARMEN team has made significant contributions to the field, including the development of new software and platforms, such as CEPS, OptimDBS, and MUSIC. Their research has the potential to improve our understanding of cardiac arrhythmias and develop more effective treatments.