Multimodality imaging and mathematical modelling of drug delivery to glioblastomas

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

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)
1 Downloads (Pure)

Abstract

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. 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 blood brain barrier 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
Article number20160039
Number of pages9
JournalInterface Focus
Volume6
Issue number5
Early online date19 Aug 2016
DOIs
Publication statusPublished - 6 Oct 2016

Keywords

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

Fingerprint

Dive into the research topics of 'Multimodality imaging and mathematical modelling of drug delivery to glioblastomas'. Together they form a unique fingerprint.

Cite this