Modeling Glioma Growth and Mass Effect in 3D MR Images of the Brain View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2007

AUTHORS

Cosmina Hogea , Christos Davatzikos , George Biros

ABSTRACT

In this article, we propose a framework for modeling glioma growth and the subsequent mechanical impact on the surrounding brain tissue (mass-effect) in a medical imaging context. Glioma growth is modeled via nonlinear reaction-advection-diffusion, with a two-way coupling with the underlying tissue elastic deformation. Tumor bulk and infiltration and subsequent mass-effects are not regarded separately, but captured by the model itself in the course of its evolution. Our formulation is fully Eulerian and naturally allows for updating the tumor diffusion coefficient following structural displacements caused by tumor growth/infiltration. We show that model parameters can be estimated via optimization based on imaging data, using efficient solution algorithms on regular grids. We test the model and the automatic optimization framework on real brain tumor data sets, achieving significant improvement in landmark prediction compared to a simplified purely mechanical approach. More... »

PAGES

642-650

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-75757-3_78

DOI

http://dx.doi.org/10.1007/978-3-540-75757-3_78

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1024475997

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/18051113


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