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dc.contributor.authorKaggie, Joshuaen
dc.contributor.authorDeen, Surrinen
dc.contributor.authorKessler, Dimitrien
dc.contributor.authorMcLean, Maryen
dc.contributor.authorBuonincontri, Guidoen
dc.contributor.authorSchulte, Rolf Fen
dc.contributor.authorAddley, Helenen
dc.contributor.authorSala, Evisen
dc.contributor.authorBrenton, Jamesen
dc.contributor.authorGraves, Martinen
dc.contributor.authorGallagher, Ferdiaen
dc.date.accessioned2019-03-14T00:30:21Z
dc.date.available2019-03-14T00:30:21Z
dc.date.issued2019-07en
dc.identifier.issn2469-7311
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/290524
dc.description.abstractMulti-parametric magnetic resonance imaging (MRI) can be used to characterise many cancer subtypes, including ovarian cancer. Quantitative mapping of MRI relaxation values, such as T1 and T2 mapping, is promising for improving tumour assessment beyond conventional qualitative T1- and T2-weighted images. However, quantitative MRI relaxation mapping methods often involve long scan times due to sequentially measuring many parameters. Magnetic Resonance Fingerprinting (MRF) is a new method that enables fast quantitative MRI by exploiting the transient signals caused by the variation of pseudorandom sequence parameters. These transient signals are then matched to a simulated dictionary of T1 and T2 values to create quantitative maps. The ability of MRF to simultaneously measure multiple parameters, could represent a new approach to characterising cancer and assessing treatment response. This feasibility study investigates MRF for simultaneous T1, T2 and relative proton density (PD) mapping using ovarian cancer as a model system.
dc.description.sponsorshipThe authors acknowledge research support from the National Institute of Health Research Cambridge Biomedical Research Centre, GlaxoSmithKline.Cancer Research UK (CRUK), the CRUK Cambridge Centre, Medical Research Council, CRUK/Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and Manchester, Addenbrooke's Charitable Trust, and the Cambridge Experimental Cancer Medicine Centre.
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.rights
dc.rights.uri
dc.titleFeasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T<sub>1</sub> and T<sub>2</sub> Mapping in a PET/MR Setting.en
dc.typeArticle
prism.endingPage515
prism.issueIdentifier4en
prism.publicationDate2019en
prism.publicationNameIEEE transactions on radiation and plasma medical sciencesen
prism.startingPage509
prism.volume3en
dc.identifier.doi10.17863/CAM.37754
dcterms.dateAccepted2019-03-11en
rioxxterms.versionofrecord10.1109/trpms.2019.2905366en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-07en
dc.contributor.orcidKaggie, Joshua [0000-0001-6706-3442]
dc.contributor.orcidDeen, Surrin [0000-0002-6206-7337]
dc.contributor.orcidKessler, Dimitri [0000-0002-1813-1039]
dc.contributor.orcidMcLean, Mary [0000-0002-3752-0179]
dc.contributor.orcidBuonincontri, Guido [0000-0002-8386-639X]
dc.contributor.orcidSala, Evis [0000-0002-5518-9360]
dc.contributor.orcidBrenton, James [0000-0002-5738-6683]
dc.contributor.orcidGraves, Martin [0000-0003-4327-3052]
dc.contributor.orcidGallagher, Ferdia [0000-0003-4784-5230]
dc.identifier.eissn2469-7303
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idCancer Research UK (16465)
pubs.funder-project-idCancer Research UK (CB4150)
cam.orpheus.successThu Jan 30 10:48:39 GMT 2020 - Embargo updated*
rioxxterms.freetoread.startdate2019-07-31


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