Show simple item record

dc.contributor.authorFeatherstone, AKen_US
dc.contributor.authorO'Connor, JPBen_US
dc.contributor.authorLittle, RAen_US
dc.contributor.authorWatson, Yen_US
dc.contributor.authorCheung, Sen_US
dc.contributor.authorBabur, Men_US
dc.contributor.authorWilliams, KJen_US
dc.contributor.authorMatthews, JCen_US
dc.contributor.authorParker, GJMen_US
dc.date.accessioned2020-08-12T14:47:54Z
dc.date.issued2018-04en_US
dc.identifier.citationMagnetic resonance in medicine, 2018, 79 (4), pp. 2236 - 2245en_US
dc.identifier.issn0740-3194en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3944
dc.identifier.eissn1522-2594en_US
dc.identifier.doi10.1002/mrm.26860en_US
dc.description.abstract<h4>Purpose</h4>Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data.<h4>Methods</h4>DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach.<h4>Results</h4>The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75).<h4>Conclusion</h4>The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_US
dc.formatPrint-Electronicen_US
dc.format.extent2236 - 2245en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectAnimalsen_US
dc.subjectHumansen_US
dc.subjectMiceen_US
dc.subjectNeoplasmsen_US
dc.subjectGlioblastomaen_US
dc.subjectCarcinoma, Non-Small-Cell Lungen_US
dc.subjectLung Neoplasmsen_US
dc.subjectOxygenen_US
dc.subjectImage Interpretation, Computer-Assisteden_US
dc.subjectMagnetic Resonance Imagingen_US
dc.subjectArea Under Curveen_US
dc.subjectCluster Analysisen_US
dc.subjectNormal Distributionen_US
dc.subjectReproducibility of Resultsen_US
dc.subjectNeoplasm Transplantationen_US
dc.subjectPerfusionen_US
dc.subjectAlgorithmsen_US
dc.subjectPrincipal Component Analysisen_US
dc.subjectImage Processing, Computer-Assisteden_US
dc.subjectSoftwareen_US
dc.subjectTumor Microenvironmenten_US
dc.subjectHypoxiaen_US
dc.subjectTumor Hypoxiaen_US
dc.titleData-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.en_US
dc.typeJournal Article
dcterms.dateAccepted2017-07-13en_US
rioxxterms.versionofrecord10.1002/mrm.26860en_US
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0en_US
rioxxterms.licenseref.startdate2018-04en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfMagnetic resonance in medicineen_US
pubs.issue4en_US
pubs.notesNot knownen_US
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-statusPublisheden_US
pubs.volume79en_US
pubs.embargo.termsNot knownen_US
icr.researchteamQuantitative Biomedical Imagingen_US
dc.contributor.icrauthorO'Connor, James Patricken_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

http://creativecommons.org/licenses/by/4.0/
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/