Literature DB >> 17505103

Mathematical modeling of brain tumors: effects of radiotherapy and chemotherapy.

G Powathil1, M Kohandel, S Sivaloganathan, A Oza, M Milosevic.   

Abstract

Gliomas, the most common primary brain tumors, are diffusive and highly invasive. The standard treatment for brain tumors consists of a combination of surgery, radiation therapy and chemotherapy. Over the past few years, mathematical models have been applied to study untreated and treated brain tumors. In an effort to improve treatment strategies, we consider a simple spatio-temporal mathematical model, based on proliferation and diffusion, that incorporates the effects of radiotherapeutic and chemotherapeutic treatments. We study the effects of different schedules of radiation therapy, including fractionated and hyperfractionated external beam radiotherapy, using a generalized linear quadratic (LQ) model. The results are compared with published clinical data. We also discuss the results for combination therapy (radiotherapy plus temozolomide, a new chemotherapy agent), as proposed in recent clinical trials. We use the model to predict optimal sequencing of the postoperative (combination of radiotherapy and adjuvant, neo-adjuvant or concurrent chemotherapy) treatments for brain tumors.

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Year:  2007        PMID: 17505103     DOI: 10.1088/0031-9155/52/11/023

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  31 in total

1.  Improving the time-machine: estimating date of birth of grade II gliomas.

Authors:  C Gerin; J Pallud; B Grammaticos; E Mandonnet; C Deroulers; P Varlet; L Capelle; L Taillandier; L Bauchet; H Duffau; M Badoual
Journal:  Cell Prolif       Date:  2011-12-14       Impact factor: 6.831

2.  Estimating intratumoral heterogeneity from spatiotemporal data.

Authors:  E M Rutter; H T Banks; K B Flores
Journal:  J Math Biol       Date:  2018-05-08       Impact factor: 2.259

3.  Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.

Authors:  Andreas Mang; Spyridon Bakas; Shashank Subramanian; Christos Davatzikos; George Biros
Journal:  Annu Rev Biomed Eng       Date:  2020-06-04       Impact factor: 9.590

4.  The integration of quantitative multi-modality imaging data into mathematical models of tumors.

Authors:  Nkiruka C Atuegwu; John C Gore; Thomas E Yankeelov
Journal:  Phys Med Biol       Date:  2010-04-06       Impact factor: 3.609

5.  An inverse problem formulation for parameter estimation of a reaction-diffusion model of low grade gliomas.

Authors:  Amir Gholami; Andreas Mang; George Biros
Journal:  J Math Biol       Date:  2015-05-12       Impact factor: 2.259

6.  A mathematical model of pre-diagnostic glioma growth.

Authors:  Marc Sturrock; Wenrui Hao; Judith Schwartzbaum; Grzegorz A Rempala
Journal:  J Theor Biol       Date:  2015-06-11       Impact factor: 2.691

7.  Multispecies model of cell lineages and feedback control in solid tumors.

Authors:  H Youssefpour; X Li; A D Lander; J S Lowengrub
Journal:  J Theor Biol       Date:  2012-03-31       Impact factor: 2.691

Review 8.  An imaging-based tumour growth and treatment response model: investigating the effect of tumour oxygenation on radiation therapy response.

Authors:  Benjamin Titz; Robert Jeraj
Journal:  Phys Med Biol       Date:  2008-08-01       Impact factor: 3.609

Review 9.  The biology and mathematical modelling of glioma invasion: a review.

Authors:  J C L Alfonso; K Talkenberger; M Seifert; B Klink; A Hawkins-Daarud; K R Swanson; H Hatzikirou; A Deutsch
Journal:  J R Soc Interface       Date:  2017-11       Impact factor: 4.118

10.  Prognostic significance of growth kinetics in newly diagnosed glioblastomas revealed by combining serial imaging with a novel biomathematical model.

Authors:  Christina H Wang; Jason K Rockhill; Maciej Mrugala; Danielle L Peacock; Albert Lai; Katy Jusenius; Joanna M Wardlaw; Timothy Cloughesy; Alexander M Spence; Russ Rockne; Ellsworth C Alvord; Kristin R Swanson
Journal:  Cancer Res       Date:  2009-11-24       Impact factor: 12.701

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