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dc.contributor.authorLittle, RA
dc.contributor.authorBarjat, H
dc.contributor.authorHare, JI
dc.contributor.authorJenner, M
dc.contributor.authorWatson, Y
dc.contributor.authorCheung, S
dc.contributor.authorHolliday, K
dc.contributor.authorZhang, W
dc.contributor.authorO'Connor, JPB
dc.contributor.authorBarry, ST
dc.contributor.authorPuri, S
dc.contributor.authorParker, GJM
dc.contributor.authorWaterton, JC
dc.date.accessioned2020-08-12T14:48:32Z
dc.date.issued2018-02-01
dc.identifier.citationMagnetic resonance imaging, 2018, 46 pp. 98 - 105
dc.identifier.issn0730-725X
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3945
dc.identifier.eissn1873-5894
dc.identifier.doi10.1016/j.mri.2017.11.008
dc.description.abstractBACKGROUND: Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients. AIM: To test the hypothesis that different tumour types exhibit systematically different Ktrans. MATERIALS AND METHODS: DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model. RESULTS: 12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability. CONCLUSION: With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment.
dc.formatPrint-Electronic
dc.format.extent98 - 105
dc.languageeng
dc.language.isoeng
dc.publisherELSEVIER SCIENCE INC
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectHumans
dc.subjectGlioma
dc.subjectBrain Neoplasms
dc.subjectContrast Media
dc.subjectMagnetic Resonance Imaging
dc.subjectModels, Statistical
dc.subjectBayes Theorem
dc.subjectRetrospective Studies
dc.subjectReproducibility of Results
dc.subjectPerfusion
dc.subjectPhantoms, Imaging
dc.subjectCapillary Permeability
dc.subjectImage Processing, Computer-Assisted
dc.subjectAdolescent
dc.subjectAdult
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectMiddle Aged
dc.subjectFemale
dc.subjectMale
dc.subjectYoung Adult
dc.subjectSignal-To-Noise Ratio
dc.subjectBiomarkers
dc.titleEvaluation of dynamic contrast-enhanced MRI biomarkers for stratified cancer medicine: How do permeability and perfusion vary between human tumours?
dc.typeJournal Article
dcterms.dateAccepted2017-11-13
rioxxterms.versionofrecord10.1016/j.mri.2017.11.008
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
rioxxterms.licenseref.startdate2018-02
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfMagnetic resonance imaging
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Quantitative Biomedical Imaging
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Quantitative Biomedical Imaging
pubs.publication-statusPublished
pubs.volume46
pubs.embargo.termsNot known
icr.researchteamQuantitative Biomedical Imaging
dc.contributor.icrauthorO'Connor, James Patrick


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