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dc.contributor.authorArthur, A
dc.contributor.authorJohnston, EW
dc.contributor.authorWinfield, JM
dc.contributor.authorBlackledge, MD
dc.contributor.authorJones, RL
dc.contributor.authorHuang, PH
dc.contributor.authorMessiou, C
dc.coverage.spatialSwitzerland
dc.date.accessioned2022-08-31T14:35:55Z
dc.date.available2022-08-31T14:35:55Z
dc.date.issued2022-07-01
dc.identifierARTN 892620
dc.identifier.citationFrontiers in Oncology, 2022, 12 pp. 892620 -
dc.identifier.issn2234-943X
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/5359
dc.identifier.eissn2234-943X
dc.identifier.eissn2234-943X
dc.identifier.doi10.3389/fonc.2022.892620
dc.description.abstractA shift in radiology to a data-driven specialty has been unlocked by synergistic developments in imaging biomarkers (IB) and computational science. This is advancing the capability to deliver "virtual biopsies" within oncology. The ability to non-invasively probe tumour biology both spatially and temporally would fulfil the potential of imaging to inform management of complex tumours; improving diagnostic accuracy, providing new insights into inter- and intra-tumoral heterogeneity and individualised treatment planning and monitoring. Soft tissue sarcomas (STS) are rare tumours of mesenchymal origin with over 150 histological subtypes and notorious heterogeneity. The combination of inter- and intra-tumoural heterogeneity and the rarity of the disease remain major barriers to effective treatments. We provide an overview of the process of successful IB development, the key imaging and computational advancements in STS including quantitative magnetic resonance imaging, radiomics and artificial intelligence, and the studies to date that have explored the potential biological surrogates to imaging metrics. We discuss the promising future directions of IBs in STS and illustrate how the routine clinical implementation of a virtual biopsy has the potential to revolutionise the management of this group of complex cancers and improve clinical outcomes.
dc.formatElectronic-eCollection
dc.format.extent892620 -
dc.languageeng
dc.language.isoeng
dc.publisherFRONTIERS MEDIA SA
dc.relation.ispartofFrontiers in Oncology
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMRI
dc.subjectimaging biomarker
dc.subjectquantitative MRI (qMRI)
dc.subjectradiology pathology correlation
dc.subjectradiomics
dc.subjectsarcoma
dc.subjectsoft tissue sarcoma (STS)
dc.subjectvirtual biopsy
dc.titleVirtual Biopsy in Soft Tissue Sarcoma. How Close Are We?
dc.typeJournal Article
dcterms.dateAccepted2022-05-31
dc.date.updated2022-08-31T14:35:21Z
rioxxterms.versionVoR
rioxxterms.versionofrecord10.3389/fonc.2022.892620
rioxxterms.licenseref.startdate2022-07-01
rioxxterms.typeJournal Article/Review
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/35847882
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/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Computational Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology
pubs.publication-statusPublished online
pubs.publisher-urlhttp://dx.doi.org/10.3389/fonc.2022.892620
pubs.volume12
icr.researchteamAppl Phys in Clinical MRI
icr.researchteamComputational Imaging
icr.researchteamMol and Systems Oncology
dc.contributor.icrauthorArthur, Amani
dc.contributor.icrauthorJohnston
dc.contributor.icrauthorBlackledge, Matthew
dc.contributor.icrauthorHuang, Paul
icr.provenanceDeposited by Mr Arek Surman on 2022-08-31. Deposit type is initial. No. of files: 1. Files: Virtual Biopsy in Soft Tissue Sarcoma. How Close Are We.pdf


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