Literature DB >> 10220926

Analysis of a mathematical model for the growth of tumors.

A Friedman1, F Reitich.   

Abstract

In this paper we study a recently proposed model for the growth of a nonnecrotic, vascularized tumor. The model is in the form of a free-boundary problem whereby the tumor grows (or shrinks) due to cell proliferation or death according to the level of a diffusing nutrient concentration. The tumor is assumed to be spherically symmetric, and its boundary is an unknown function r = s(t). We concentrate on the case where at the boundary of the tumor the birth rate of cells exceeds their death rate, a necessary condition for the existence of a unique stationary solution with radius r = R0 (which depends on the various parameters of the problem). Denoting by c the quotient of the diffusion time scale to the tumor doubling time scale, so that c is small, we rigorously prove that (i) lim inf s(t) > 0, i.e. once engendered, tumors persist in time. t-->infinity Indeed, we further show that (ii) If c is sufficiently small then s(t)-->R0 exponentially fast as t-->infinity, i.e. the steady state solution is globally asymptotically stable. Further, (iii) If c is not "sufficiently small" but is smaller than some constant gamma determined explicitly by the parameters of the problem, then t-->infinity lim sup s(t) < infinity; if however c is "somewhat" larger than gamma then generally s(t) does not remain bounded and, in fact, s(t)-->infinity exponentially fast as t-->infinity.

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Year:  1999        PMID: 10220926     DOI: 10.1007/s002850050149

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  11 in total

1.  Initial/boundary-value problems of tumor growth within a host tissue.

Authors:  Andrea Tosin
Journal:  J Math Biol       Date:  2013-01       Impact factor: 2.259

2.  Solving inverse problems for biological models using the collage method for differential equations.

Authors:  V Capasso; H E Kunze; D La Torre; E R Vrscay
Journal:  J Math Biol       Date:  2012-02-24       Impact factor: 2.259

3.  An Adaptive Multigrid Algorithm for Simulating Solid Tumor Growth Using Mixture Models.

Authors:  S M Wise; J S Lowengrub; V Cristini
Journal:  Math Comput Model       Date:  2011-01-01

4.  The competitive dynamics between tumor cells, a replication-competent virus and an immune response.

Authors:  Youshan Tao; Qian Guo
Journal:  J Math Biol       Date:  2005-03-15       Impact factor: 2.259

5.  Nonlinear modelling of cancer: bridging the gap between cells and tumours.

Authors:  J S Lowengrub; H B Frieboes; F Jin; Y-L Chuang; X Li; P Macklin; S M Wise; V Cristini
Journal:  Nonlinearity       Date:  2010

6.  Predictions of tumour morphological stability and evaluation against experimental observations.

Authors:  Kara Pham; Hermann B Frieboes; Vittorio Cristini; John Lowengrub
Journal:  J R Soc Interface       Date:  2010-06-02       Impact factor: 4.118

7.  Three-dimensional multispecies nonlinear tumor growth--I Model and numerical method.

Authors:  S M Wise; J S Lowengrub; H B Frieboes; V Cristini
Journal:  J Theor Biol       Date:  2008-03-28       Impact factor: 2.691

8.  Analysis of a model of a virus that replicates selectively in tumor cells.

Authors:  Avner Friedman; Youshan Tao
Journal:  J Math Biol       Date:  2003-06-12       Impact factor: 2.259

9.  Steady-state analysis of necrotic core formation for solid avascular tumors with time delays in regulatory apoptosis.

Authors:  Fangwei Zhang; Shihe Xu
Journal:  Comput Math Methods Med       Date:  2014-10-13       Impact factor: 2.238

10.  Predictive modeling of in vivo response to gemcitabine in pancreatic cancer.

Authors:  James J Lee; Justin Huang; Christopher G England; Lacey R McNally; Hermann B Frieboes
Journal:  PLoS Comput Biol       Date:  2013-09-19       Impact factor: 4.475

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