Literature DB >> 18815786

A mathematical model for brain tumor response to radiation therapy.

R Rockne1, E C Alvord, J K Rockhill, K R Swanson.   

Abstract

Gliomas are highly invasive primary brain tumors, accounting for nearly 50% of all brain tumors (Alvord and Shaw in The pathology of the aging human nervous system. Lea & Febiger, Philadelphia, pp 210-281, 1991). Their aggressive growth leads to short life expectancies, as well as a fairly algorithmic approach to treatment: diagnostic magnetic resonance image (MRI) followed by biopsy or surgical resection with accompanying second MRI, external beam radiation therapy concurrent with and followed by chemotherapy, with MRIs conducted at various times during treatment as prescribed by the physician. Swanson et al. (Harpold et al. in J Neuropathol Exp Neurol 66:1-9, 2007) have shown that the defining and essential characteristics of gliomas in terms of net rates of proliferation (rho) and invasion (D) can be determined from serial MRIs of individual patients. We present an extension to Swanson's reaction-diffusion model to include the effects of radiation therapy using the classic linear-quadratic radiobiological model (Hall in Radiobiology for the radiologist. Lippincott, Philadelphia, pp 478-480, 1994) for radiation efficacy, along with an investigation of response to various therapy schedules and dose distributions on a virtual tumor (Swanson et al. in AACR annual meeting, Los Angeles, 2007).

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Year:  2008        PMID: 18815786      PMCID: PMC3784027          DOI: 10.1007/s00285-008-0219-6

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


  33 in total

1.  A four-dimensional computer simulation model of the in vivo response to radiotherapy of glioblastoma multiforme: studies on the effect of clonogenic cell density.

Authors:  G S Stamatakos; V P Antipas; N K Uzunoglu; R G Dale
Journal:  Br J Radiol       Date:  2006-05       Impact factor: 3.039

2.  The modified linear-quadratic model of Guerrero and Li can be derived from a mechanistic basis and exhibits linear-quadratic-linear behaviour.

Authors:  Marco Carlone; David Wilkins; Peter Raaphorst
Journal:  Phys Med Biol       Date:  2005-05-05       Impact factor: 3.609

3.  Fitting the linear-quadratic model to detailed data sets for different dose ranges.

Authors:  L M Garcia; J Leblanc; D Wilkins; G P Raaphorst
Journal:  Phys Med Biol       Date:  2006-05-17       Impact factor: 3.609

Review 4.  The evolution of mathematical modeling of glioma proliferation and invasion.

Authors:  Hana L P Harpold; Ellsworth C Alvord; Kristin R Swanson
Journal:  J Neuropathol Exp Neurol       Date:  2007-01       Impact factor: 3.685

5.  Investigation of various growth mechanisms of solid tumour growth within the linear-quadratic model for radiotherapy.

Authors:  H McAneney; S F C O'Rourke
Journal:  Phys Med Biol       Date:  2007-01-23       Impact factor: 3.609

6.  A quantitative model for differential motility of gliomas in grey and white matter.

Authors:  K R Swanson; E C Alvord; J D Murray
Journal:  Cell Prolif       Date:  2000-10       Impact factor: 6.831

7.  Mathematical modelling of radiotherapy strategies for early breast cancer.

Authors:  Heiko Enderling; Alexander R A Anderson; Mark A J Chaplain; Alastair J Munro; Jayant S Vaidya
Journal:  J Theor Biol       Date:  2005-12-28       Impact factor: 2.691

8.  Mathematical models of tumour and normal tissue response.

Authors:  B Jones; R G Dale
Journal:  Acta Oncol       Date:  1999       Impact factor: 4.089

9.  A mathematical model of breast cancer development, local treatment and recurrence.

Authors:  Heiko Enderling; Mark A J Chaplain; Alexander R A Anderson; Jayant S Vaidya
Journal:  J Theor Biol       Date:  2006-12-12       Impact factor: 2.691

10.  A multiscale mathematical model of cancer, and its use in analyzing irradiation therapies.

Authors:  Benjamin Ribba; Thierry Colin; Santiago Schnell
Journal:  Theor Biol Med Model       Date:  2006-02-10       Impact factor: 2.432

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  53 in total

Review 1.  Magnetic resonance imaging characteristics of glioblastoma multiforme: implications for understanding glioma ontogeny.

Authors:  Leif-Erik Bohman; Kristin R Swanson; Julia L Moore; Russ Rockne; Christopher Mandigo; Todd Hankinson; Marcela Assanah; Peter Canoll; Jeffrey N Bruce
Journal:  Neurosurgery       Date:  2010-11       Impact factor: 4.654

Review 2.  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

Review 3.  Dissecting cancer through mathematics: from the cell to the animal model.

Authors:  Helen M Byrne
Journal:  Nat Rev Cancer       Date:  2010-03       Impact factor: 60.716

4.  Applying a patient-specific bio-mathematical model of glioma growth to develop virtual [18F]-FMISO-PET images.

Authors:  Stanley Gu; Gargi Chakraborty; Kyle Champley; Adam M Alessio; Jonathan Claridge; Russell Rockne; Mark Muzi; Kenneth A Krohn; Alexander M Spence; Ellsworth C Alvord; Alexander R A Anderson; Paul E Kinahan; Kristin R Swanson
Journal:  Math Med Biol       Date:  2011-05-11       Impact factor: 1.854

5.  A mathematical model of tumor growth and its response to single irradiation.

Authors:  Yoichi Watanabe; Erik L Dahlman; Kevin Z Leder; Susanta K Hui
Journal:  Theor Biol Med Model       Date:  2016-02-27       Impact factor: 2.432

6.  Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach.

Authors:  R Rockne; J K Rockhill; M Mrugala; A M Spence; I Kalet; K Hendrickson; A Lai; T Cloughesy; E C Alvord; K R Swanson
Journal:  Phys Med Biol       Date:  2010-05-18       Impact factor: 3.609

7.  Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer.

Authors:  David A Hormuth; Jared A Weis; Stephanie L Barnes; Michael I Miga; Vito Quaranta; Thomas E Yankeelov
Journal:  Int J Radiat Oncol Biol Phys       Date:  2017-12-13       Impact factor: 7.038

8.  Selection and Validation of Predictive Models of Radiation Effects on Tumor Growth Based on Noninvasive Imaging Data.

Authors:  E A B F Lima; J T Oden; B Wohlmuth; A Shahmoradi; D A Hormuth; T E Yankeelov; L Scarabosio; T Horger
Journal:  Comput Methods Appl Mech Eng       Date:  2017-08-18       Impact factor: 6.756

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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