Multimodality imaging and mathematical modelling of drug delivery to glioblastomas

Ahmed Boujelben, Michael Watson, Steven McDougall, Yi Fen Yen, Elizabeth R. Gerstner, Ciprian Catana, Thomas Deisboeck, Tracy T. Batchelor, David Boas, Bruce Rosen, Jayashree Kalpathy-Cramer, Mark A.J. Chaplain

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood–brain barrier (BBB). Although it has been hypothesized that the ‘normalization’ of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated—flow rate, vessel permeability and tissue diffusion coefficient— interact nonlinearly to produce the observed average drug concentration in the microenvironment.

Original languageEnglish (US)
JournalInterface Focus
Issue number5
StatePublished - Oct 6 2016


  • Computational modelling and simulation
  • Drug delivery
  • Glioblastoma
  • Multimodality imaging
  • Perfusion

ASJC Scopus subject areas

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


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