Literature DB >> 10736214

Simulated brain tumor growth dynamics using a three-dimensional cellular automaton.

A R Kansal1, S Torquato, I V Harsh GR, E A Chiocca, T S Deisboeck.   

Abstract

We have developed a novel and versatile three-dimensional cellular automaton model of brain tumor growth. We show that macroscopic tumor behavior can be realistically modeled using microscopic parameters. Using only four parameters, this model simulates Gompertzian growth for a tumor growing over nearly three orders of magnitude in radius. It also predicts the composition and dynamics of the tumor at selected time points in agreement with medical literature. We also demonstrate the flexibility of the model by showing the emergence, and eventual dominance, of a second tumor clone with a different genotype. The model incorporates several important and novel features, both in the rules governing the model and in the underlying structure of the model. Among these are a new definition of how to model proliferative and non-proliferative cells, an isotropic lattice, and an adaptive grid lattice. Copyright 2000 Academic Press.

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Year:  2000        PMID: 10736214     DOI: 10.1006/jtbi.2000.2000

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  76 in total

1.  Cell population dynamics modulate the rates of tissue growth processes.

Authors:  Gang Cheng; Belgacem B Youssef; Pauline Markenscoff; Kyriacos Zygourakis
Journal:  Biophys J       Date:  2005-11-18       Impact factor: 4.033

2.  An evolutionary hybrid cellular automaton model of solid tumour growth.

Authors:  P Gerlee; A R A Anderson
Journal:  J Theor Biol       Date:  2007-02-12       Impact factor: 2.691

Review 3.  Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Authors:  Sandeep Sanga; Hermann B Frieboes; Xiaoming Zheng; Robert Gatenby; Elaine L Bearer; Vittorio Cristini
Journal:  Neuroimage       Date:  2007-06-07       Impact factor: 6.556

Review 4.  Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.

Authors:  Maria Protopapa; Anna Zygogianni; Georgios S Stamatakos; Christos Antypas; Christina Armpilia; Nikolaos K Uzunoglu; Vassilis Kouloulias
Journal:  J Neurooncol       Date:  2017-10-28       Impact factor: 4.130

5.  The role of extracellular matrix in glioma invasion: a cellular Potts model approach.

Authors:  Brenda M Rubenstein; Laura J Kaufman
Journal:  Biophys J       Date:  2008-10-03       Impact factor: 4.033

Review 6.  At the biological modeling and simulation frontier.

Authors:  C Anthony Hunt; Glen E P Ropella; Tai Ning Lam; Jonathan Tang; Sean H J Kim; Jesse A Engelberg; Shahab Sheikh-Bahaei
Journal:  Pharm Res       Date:  2009-09-09       Impact factor: 4.200

Review 7.  Toward an Ising model of cancer and beyond.

Authors:  Salvatore Torquato
Journal:  Phys Biol       Date:  2011-02-07       Impact factor: 2.583

8.  Front instabilities and invasiveness of simulated avascular tumors.

Authors:  Nikodem J Popławski; Ubirajara Agero; J Scott Gens; Maciej Swat; James A Glazier; Alexander R A Anderson
Journal:  Bull Math Biol       Date:  2009-02-21       Impact factor: 1.758

Review 9.  In silico cancer modeling: is it ready for prime time?

Authors:  Thomas S Deisboeck; Le Zhang; Jeongah Yoon; Jose Costa
Journal:  Nat Clin Pract Oncol       Date:  2008-10-14

10.  Introduction of hypermatrix and operator notation into a discrete mathematics simulation model of malignant tumour response to therapeutic schemes in vivo. Some operator properties.

Authors:  Georgios S Stamatakos; Dimitra D Dionysiou
Journal:  Cancer Inform       Date:  2009-10-21
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