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Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

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Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation (EN)
Stamatakos, GS (EN)
May, CP (EN)
Kolokotroni, E (EN)
Buchler, P (EN)
journalArticle (EN)
2014-03-01T01:35:28Z
2011 (EN)
Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. (C) 2011 Elsevier Ltd. All rights reserved. (EN)
Biochemistry & Molecular Biology (EN)
Biophysics (EN)
Mechanical Processes (EN)
In silico oncology (EN)
Pressure effects (EN)
pathology (EN)
nuclear magnetic resonance imaging (EN)
Humans (EN)
Glioblastoma (EN)
Biophysical Processes (EN)
biomechanics (EN)
Finite element methods (EN)
system analysis (EN)
Finite Element Analysis (EN)
biophysics (EN)
human (EN)
Monte Carlo method (EN)
biological model (EN)
Biological system modeling (EN)
Multiscale cancer modeling (EN)
Systems Integration (EN)
Treatment Outcome (EN)
mechanics (EN)
finite element analysis (EN)
treatment outcome (EN)
article (EN)
Biomechanics (EN)
Magnetic Resonance Imaging (EN)
glioblastoma (EN)
Models, Biological (EN)
Monte Carlo Method (EN)
Progress in Biophysics and Molecular Biology (EN)
Αγγλική γλώσσα
PERGAMON-ELSEVIER SCIENCE LTD (EN)
Εθνικό Μετσόβιο Πολυτεχνείο
Ψηφιακό Αποθετήριο της Κεντρικής Βιβλιοθήκης του ΕΜΠ | Dspace@NTUA
Κεντρική Βιβλιοθήκη Ε.Μ.Π.
Ιδρυματικό Αποθετήριο
Δημοσιεύσεις μελών Δ.Ε.Π. σε περιοδικά



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