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dc.contributor.authordeSouza, NMen_US
dc.contributor.authorAchten, Een_US
dc.contributor.authorAlberich-Bayarri, Aen_US
dc.contributor.authorBamberg, Fen_US
dc.contributor.authorBoellaard, Ren_US
dc.contributor.authorClément, Oen_US
dc.contributor.authorFournier, Len_US
dc.contributor.authorGallagher, Fen_US
dc.contributor.authorGolay, Xen_US
dc.contributor.authorHeussel, CPen_US
dc.contributor.authorJackson, EFen_US
dc.contributor.authorManniesing, Ren_US
dc.contributor.authorMayerhofer, MEen_US
dc.contributor.authorNeri, Een_US
dc.contributor.authorO'Connor, Jen_US
dc.contributor.authorOguz, KKen_US
dc.contributor.authorPersson, Aen_US
dc.contributor.authorSmits, Men_US
dc.contributor.authorvan Beek, EJRen_US
dc.contributor.authorZech, CJen_US
dc.contributor.authorEuropean Society of Radiologyen_US
dc.identifier.citationInsights into imaging, 2019, 10 (1), pp. 87 - ?
dc.description.abstractObserver-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.
dc.format.extent87 - ?
dc.subjectEuropean Society of Radiology
dc.titleValidated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR).
dc.typeJournal Article
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfInsights into imaging
pubs.notesNot known
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/Magnetic Resonance
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Quantitative Biomedical Imaging
pubs.embargo.termsNot known
icr.researchteamMagnetic Resonanceen_US
icr.researchteamQuantitative Biomedical Imagingen_US
dc.contributor.icrauthordeSouza, Nanditaen
dc.contributor.icrauthorO'Connor, James Patricken

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