A mathematical model for brain tumor response to radiation therapy

J Math Biol. 2009 Apr;58(4-5):561-78. doi: 10.1007/s00285-008-0219-6. Epub 2008 Sep 25.


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).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Brain Neoplasms / pathology
  • Brain Neoplasms / radiotherapy*
  • Glioma / pathology
  • Glioma / radiotherapy
  • Humans
  • Linear Models
  • Magnetic Resonance Imaging
  • Mathematical Concepts
  • Models, Biological*
  • Radiation Tolerance
  • Radiobiology
  • Radiotherapy Dosage
  • Rats