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dc.contributor.authorBoujelben, Ahmed
dc.contributor.authorWatson, Michael
dc.contributor.authorMcDougall, Steven
dc.contributor.authorYen, Yi-Fen
dc.contributor.authorGerstner, Elizabeth
dc.contributor.authorCatana, Ciprian
dc.contributor.authorDeisboeck, Thomas
dc.contributor.authorBatchelor, Tracy
dc.contributor.authorBoas, David
dc.contributor.authorRosen, Bruce
dc.contributor.authorKalpathy-Cramer, Jayashree
dc.contributor.authorChaplain, Mark Andrew Joseph
dc.date.accessioned2017-08-19T23:32:24Z
dc.date.available2017-08-19T23:32:24Z
dc.date.issued2016-10-06
dc.identifier.citationBoujelben , A , Watson , M , McDougall , S , Yen , Y-F , Gerstner , E , Catana , C , Deisboeck , T , Batchelor , T , Boas , D , Rosen , B , Kalpathy-Cramer , J & Chaplain , M A J 2016 , ' Multimodality imaging and mathematical modelling of drug delivery to glioblastomas ' , Interface Focus , vol. 6 , no. 5 , 20160039 . https://doi.org/10.1098/rsfs.2016.0039en
dc.identifier.issn2042-8898
dc.identifier.otherPURE: 244397885
dc.identifier.otherPURE UUID: 49b008ef-e16d-4cf7-a583-eff59cb85b81
dc.identifier.otherScopus: 84983449497
dc.identifier.otherORCID: /0000-0001-5727-2160/work/55378931
dc.identifier.otherWOS: 000382192900007
dc.identifier.urihttps://hdl.handle.net/10023/11513
dc.descriptionMAJC would like to thank the Isaac Newton Institute for Mathematical Sciences for its hospitality during the programme “Coupling Geometric PDEs with Physics for Cell Morphology, Motility and Pattern Formation” supported by EPSRC Grant Number EP/K032208/1.en
dc.description.abstractPatients 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.
dc.format.extent9
dc.language.isoeng
dc.relation.ispartofInterface Focusen
dc.rights© 2016, the Author(s). This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at rsfs.royalsocietypublishing.org / https://dx.doi.org/10.1098/rsfs.2016.0039en
dc.subjectMultimodality imagingen
dc.subjectGlioblastomaen
dc.subjectDrug deliveryen
dc.subjectPerfusionen
dc.subjectComputational modelling and simulationen
dc.subjectRM Therapeutics. Pharmacologyen
dc.subjectQA Mathematicsen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subject.lccRMen
dc.subject.lccQAen
dc.subject.lccQH301en
dc.titleMultimodality imaging and mathematical modelling of drug delivery to glioblastomasen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. Applied Mathematicsen
dc.identifier.doihttps://doi.org/10.1098/rsfs.2016.0039
dc.description.statusPeer revieweden
dc.date.embargoedUntil2017-08-19


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