YALES2BIO : outil de simulation hmodynamique S. Mendez CNRS et I3M, - - PowerPoint PPT Presentation

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YALES2BIO : outil de simulation hmodynamique S. Mendez CNRS et I3M, - - PowerPoint PPT Presentation

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YALES2BIO : outil de simulation hmodynamique S. Mendez CNRS et I3M, Universit Montpellier II Avec C. Chnafa, E. Gibaud, J. Sigenza, V. Zmijanovic and F. Nicoud Institut de Mathmatiques et de Modlisation de Montpellier Journe de

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Institut de Mathématiques et de Modélisation de Montpellier

YALES2BIO : outil de simulation hémodynamique

Journée de recherche translationnelle sur les systèmes Biomédicaux Cardio-Vasculaires – BioDev. 20/11/14

Avec C. Chnafa, E. Gibaud, J. Sigüenza, V. Zmijanovic and F. Nicoud

  • S. Mendez CNRS et I3M, Université Montpellier II
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Contributors and collaborators

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  • I3M (Montpellier)
  • Christophe Chnafa
  • Etienne Gibaud
  • Marco Martins Afonso
  • Simon Mendez
  • Franck Nicoud
  • Julien Sigüenza
  • Vladeta Zmijanovic
  • CORIA (Rouen)
  • Ghislain Lartigue
  • Vincent Moureau
  • LMGC (Montpellier)
  • Dominique Ambard
  • Frédéric Dubois
  • Franck Jourdan
  • Rémy Mozul
  • L2C (Montpellier)
  • Manouk Abkarian
  • CHU Toulouse
  • Ramiro Moreno
  • Hervé Rousseau
  • CHU Montpellier et IRRAS Technology
  • Vincent Costalat
  • Mathieu Sanchez
  • CHU Nîmes
  • Iris Schüster
  • Lab. Pharm-Ecologie Cardiovasculaire

(Avignon)

  • Claire Maufrais
  • Stéphane Nottin
  • Horiba Medical (Montpellier)
  • Damien Isèbe
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Numerical simulations = Solving the equations by computers

Ex: fluid equations solved by finite elements, finite volumes,…

Numerical simulations of blood flows

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∂Ui ∂xi = 0

ρ dUi dt = ρF

i − ∂P

∂xi + ∂ ∂xj µ ∂Ui ∂xj        

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Why numerical simulations?

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To analyze To predict

Surgical outcome Device design

Sanchez et al. 2014 Torii et al. 2009 Marsden et al. 2009 Van Caneeyt et al. 2009 Chnafa et al. 2014

Data correlation Flow description

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Analyzing with numerical simulations

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Sanchez et al. 2014: infer the aneurysm wall properties => Voir V. Costalat 15h55 Torii et al. 2009: how aneurysm shape influences flow in aneurysms

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Predicting with numerical simulations

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Van Canneyt et al. 2013: Design of arteriovenous graft => Voir P. Verdonck 14h15 Marsden et al. 2009: Design of Fontan graft

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YALES2BIO

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http://www.math.univ-montp2.fr/~yales2bio

  • I3M is developing YALES2BIO
  • From existing solver YALES2 (CORIA)

Method: see - Moureau et al. 2011,

  • Chnafa et al. 2014a & 2014b,
  • Mendez et al. 2014
  • Two applications :

1. Left heart flow from medical images 2. Artificial heart flow

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The heart. In brief

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VG AD AG VD

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Heart flow is extremely interesting

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  • For fundamental fluid mechanics
  • For medical reasons:
  • Wall shear stress
  • High pressure
  • Diagnosis (aortic valve stenosis)
  • For future artificial devices (Carmat, Abiocor, Reinheart,…)

Markl et al. 2013 Kilner et al. 2000

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What should we predict?

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  • Flow related to heart movement
  • Wall movement prediction => errors
  • For flow predictions only, use the

medical images

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Image registration algorithm

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From images (color),

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Image registration algorithm

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From images (color),

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Image registration algorithm

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From images (color), ⇒ 4D mesh of the flow domain ⇒ Flow computation in a domain with prescribed motion

Moreno et al. 2008, Midulla et al. 2012, Chnafa et al. 2014

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Animation of the flow

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  • Grid 3 millions of tetrahedra
  • 70 cycles computed
  • 1 cycle = 4h on 60 processors
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Strong cycle to cycle variations

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Recently : Zajac et al. 2014. Turbulence intensity as a biomarker?

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Modeling the transport in the heart

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For more details: PhD defense of C. Chnafa, tomorrow 14h

0 s 0.5 s 0 s 0.5 s Time spent in the ventricle Time spent in the ventricle

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Total artificial hearts

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Syncardia heart (Slepian et al., J. Biomech. 2013) Abiocar, Carmat hearts,…

Abiocor Carmat

How to compute the flow in these systems?

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Principle of the CARMAT artificial heart

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Schematic from the French newspaper ‘Le Monde’

Left ventricle Right ventricle Secondary fluid Pump

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Accounting for immersed structures

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Flexible membranes and valves

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Fluid-structure interaction

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Coupling with LMGC90 (with Ambard, Dubois, Jourdan, Mozul, Sigüenza)

  • Displacements

Forces

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Example with valves

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Thesis : J. Sigüenza

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Back to the artificial heart

A first attempt in half the system: unstructured LES + flexible membrane

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Configuration

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  • A domain mimicking the left heart flow (only half
  • f the heart is considered).

membrane Top view Side view Secondary fluid Blood To aorta From lungs

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Movie presentation

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Movie (5 cycles from the start)

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Residence times movie (8 cycles)

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The artificial heart case

1. Benefits from the experience on physiological heart 2. Industrial applications for Fluid-Structure coupling 3. Proof of concept case => application on real geometries soon

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Computations for industrial applications

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The use of a high-fidelity solver

Artificial hearts Blood analyzers

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Counting and sizing with the Coulter effect

Region of interest Velocity 6 m/s in a 50µm aperture

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Passage of red blood cells in the orifice

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Method : Relation between the red blood cell dynamics and measured volume Objective : minimize errors by device optimization

Thesis : E. Gibaud

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Thank you for your attention

http://www.math.univ-montp2.fr/~yales2bio

We thank for financial support:

  • I3M (Montpellier)
  • Christophe Chnafa
  • Etienne Gibaud
  • Marco Martins Afonso
  • Simon Mendez
  • Franck Nicoud
  • Julien Sigüenza
  • Vladeta Zmijanovic
  • CORIA (Rouen)
  • Ghislain Lartigue
  • Vincent Moureau
  • LMGC (Montpellier)
  • Dominique Ambard
  • Frédéric Dubois
  • Franck Jourdan
  • Rémy Mozul
  • CHU Nîmes
  • Iris Schüster
  • CHU Montpellier et IRRAS

Technology

  • Vincent Costalat
  • Mathieu Sanchez
  • CHU Toulouse
  • Ramiro Moreno
  • Hervé Rousseau
  • Lab. Pharm-Ecologie

Cardiovasculaire (Avignon)

  • Claire Maufrais
  • Stéphane Nottin
  • L2C (Montpellier)
  • Manouk Abkarian
  • Horiba Medical (Montpellier)
  • Damien Isèbe