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dc.contributor.authorLi, Chaoen
dc.contributor.authorWang, Shuoen
dc.contributor.authorLiu, Panen
dc.contributor.authorTorheim, Turiden
dc.contributor.authorBoonzaier, Natalie Ren
dc.contributor.authorvan Dijken, Bart Rjen
dc.contributor.authorSchönlieb, Carola-Bibianeen
dc.contributor.authorMarkowetz, Florianen
dc.contributor.authorPrice, Stephen Johnen
dc.date.accessioned2019-03-22T00:30:14Z
dc.date.available2019-03-22T00:30:14Z
dc.date.issued2019-05en
dc.identifier.issn1522-8002
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/290737
dc.description.abstractGlioblastoma is highly heterogeneous in microstructure and vasculature, creating various tumor microenvironment among patients, which may lead to different phenotypes. The purpose was to interrogate the inter-dependence of microstructure and vasculature using perfusion and diffusion imaging and to investigate the utility of this approach in tumor invasiveness assessment. A total of 115 primary glioblastoma patients were prospectively recruited for pre-operative MRI and surgery. Apparent diffusion coefficient (ADC) was calculated from diffusion imaging, and relative cerebral blood volume (rCBV) was calculated from perfusion imaging. The empirical copula transform was applied to ADC and rCBV voxels in the contrast-enhancing tumor region to obtain their joint distribution, which was discretized to extract second-order features for an unsupervised hierarchical clustering. The lactate levels of patient subgroups, measured by MR spectroscopy, were compared. Survivals were analyzed using Kaplan-Meier and multivariate Cox regression analyses. The results showed that three patient subgroups were identified by the unsupervised clustering. These subtypes showed no significant differences in clinical characteristics but were significantly different in lactate level and patient survivals. Specifically, the subtype demonstrating high inter-dependence of ADC and rCBV displayed a higher lactate level than the other two subtypes (P = 0.016 and P = 0.044 respectively). Both subtypes of low and high inter-dependence showed worse progression-free survival than the intermediate (P = 0.046 and P = 0.009 respectively). Our results suggest that the inter-dependence between perfusion and diffusion imaging may be useful in stratifying patients and evaluating tumor invasiveness, providing overall measure of tumor microenvironment using multi-parametric MRI.
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.publisherEdiciones Doyma S.A.
dc.rights
dc.rights.uri
dc.titleDecoding the Interdependence of Multiparametric Magnetic Resonance Imaging to Reveal Patient Subgroups Correlated with Survivals.en
dc.typeArticle
prism.endingPage449
prism.issueIdentifier5en
prism.publicationDate2019en
prism.publicationNameNeoplasia (New York, N.Y.)en
prism.startingPage442
prism.volume21en
dc.identifier.doi10.17863/CAM.37937
dcterms.dateAccepted2019-03-12en
rioxxterms.versionofrecord10.1016/j.neo.2019.03.005en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-05en
dc.contributor.orcidLi, Chao [0000-0002-0734-0011]
dc.contributor.orcidWang, Shuo [0000-0002-2947-8783]
dc.contributor.orcidMarkowetz, Florian [0000-0002-2784-5308]
dc.contributor.orcidPrice, Stephen John [0000-0002-7535-3009]
dc.identifier.eissn1476-5586
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idEPSRC (EP/N014588/1)
rioxxterms.freetoread.startdate2022-03-21


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