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 A. Krohn, Kristin R. Swanson

Research output: Contribution to journalArticle

45 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 threedimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [18F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patientspecific 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 improvementwas 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)
Article number20141174
JournalJournal of the Royal Society Interface
Volume12
Issue number103
DOIs
StatePublished - Feb 6 2015

Keywords

  • Glioblastoma
  • Hypoxia
  • Mathematical modelling
  • Patient-specific
  • Radiation resistance

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biomaterials
  • Biochemistry
  • Biomedical Engineering

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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. A., & 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), [20141174]. https://doi.org/10.1098/rsif.2014.1174