A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Russell C. Rockne, Andrew D. Trister, Joshua Jacobs, Andrea J. Hawkins-Daarud, Maxwell L. Neal, Kristi Hendrickson, Maciej M. Mrugala, Jason K. Rockhill, Paul Kinahan, Kenneth Krohn, Kristin R. Swanson

Research output: Contribution to journalArticle

43 Scopus citations

Abstract

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient's disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [(18)F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model-data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.

Original languageEnglish (US)
JournalJournal of the Royal Society Interface
Volume12
Issue number103
DOIs
StatePublished - Feb 6 2015
Externally publishedYes

Keywords

  • glioblastoma
  • hypoxia
  • mathematical modelling
  • patient-specific
  • radiation resistance

ASJC Scopus subject areas

  • Medicine(all)

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    Rockne, R. C., Trister, A. D., Jacobs, J., Hawkins-Daarud, A. J., Neal, M. L., Hendrickson, K., Mrugala, M. M., Rockhill, J. K., Kinahan, P., Krohn, K., & Swanson, K. R. (2015). A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET. Journal of the Royal Society Interface, 12(103). https://doi.org/10.1098/rsif.2014.1174