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On the importance of the submicrovascular network in a computational model of tumour growth.
Lesart A.-C., Van Der Sanden B., Hamard L., Estève F., Stéphanou A.
Microvascular Research 84, 2 (2012) 188-204 - http://www.hal.inserm.fr/inserm-00738177
(22705361)
On the importance of the submicrovascular network in a computational model of tumour growth.
Anne-Cécile Lesart1, Boudewijn Van Der Sanden2, Lauriane Hamard2, François Estève2, Angélique Stéphanou () 1
1 :  TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble
http://www-timc.imag.fr
CNRS : UMR5525 – Université Joseph Fourier - Grenoble I
Domaine de la Merci - 38706 La Tronche
France
2 :  GIN - U836 - Grenoble Institut des Neurosciences
http://neurosciences.ujf-grenoble.fr/
INSERM : U836 – Université Joseph Fourier - Grenoble I – CHU Grenoble – CEA : DSV/IRTSV
UJF - Site Santé La Tronche - BP 170 - 38042 Grenoble Cedex 9
France
INSERM U836, équipe 7, Nanomédecine et cerveau
INSERM U836, équipe 6, Rayonnement synchrotron et recherche médicale
DyCTiM
A computational model is potentially a powerful tool to apprehend complex phenomena like solid tumour growth and to predict the outcome of therapies. To that end, the confrontation of the model with experiments is essential to validate this tool. In this study, we develop a computational model specifically dedicated to the interpretation of tumour growth as observed in a mouse model with a dorsal skinfold chamber. Observation of the skin vasculature at the dorsal window scale shows a sparse network of a few main vessels of several hundreds micrometers in diameter. However observation at a smaller scale reveals the presence of a dense and regular interconnected network of capillaries about ten times smaller. We conveniently designate this structure as the submicrovascular network (SMVN).(1) The question that we wish to answer concerns the necessity of explicitly taking into account the SMVN in the computational model to describe the tumour evolution observed in the dorsal chamber. For that, simulations of tumour growth realised with and without the SMVN are compared and lead to two distinct scenarios. Parameters that are known to strongly influence the tumour evolution are then tested in the two cases to determine to which extent those parameters can be used to compensate the observed differences between these scenarios. Explicit modelling of the smallest vessels appears mandatory although not necessarily under the form of a regular grid. A compromise between the two investigated cases can thus be reached.
Sciences du Vivant/Neurosciences
Sciences du Vivant/Cancérologie
Anglais
0026-2862

Articles dans des revues avec comité de lecture
10.1016/j.mvr.2012.06.001
Microvascular Research (Microvasc Res)
Publisher Elsevier
ISSN 0026-2862 (eISSN : 1095-9319)
internationale
09/2012
13/06/2012
84
2
188-204

computational model – dorsal skinfold chamber – microvascular network – angiogenesis – tumour growth – multiscale model – hybrid model
Animals – Apoptosis – Capillaries – Cell Hypoxia – Cell Proliferation – Computer Simulation – Glioma – Mice – Nude – Models – Cardiovascular – Necrosis – Neovascularization – Pathologic – Oxygen – Reproducibility of Results – Skin – Time Factors – Tumor Burden – Vascular Endothelial Growth Factor A
CNRS (PEPS-INS2I 2010-2011) Rhˆone-Alpes Institute for Complex Systems (RNCS and IXXI respectively)French National Network
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