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dc.contributor.authorKommers, Ivar
dc.contributor.authorBouget, David Nicolas Jean-Marie
dc.contributor.authorPedersen, André
dc.contributor.authorEijgelaar, Roelant
dc.contributor.authorArdon, Hilko
dc.contributor.authorBarkhof, Frederik
dc.contributor.authorBello, Lorenzo
dc.contributor.authorBerger, Mitchel S.
dc.contributor.authorNibali, Marco Conti
dc.contributor.authorFurtner, Julia
dc.contributor.authorFyllingen, Even Hovig
dc.contributor.authorHervey-Jumper, Shawn
dc.contributor.authorIdema, Albert J. S.
dc.contributor.authorKiesel, Barbara
dc.contributor.authorKloet, Alfred
dc.contributor.authorMandonnet, Emmanuel
dc.contributor.authorMüller, Domenique M. J.
dc.contributor.authorRobe, Pierre
dc.contributor.authorRossi, Marco
dc.contributor.authorSagberg, Lisa Millgård
dc.contributor.authorSciortino, Tommaso
dc.contributor.authorvan den Brink, Wimar A.
dc.contributor.authorWagemakers, Michiel
dc.contributor.authorWidhalm, Georg
dc.contributor.authorWitte, Marnix G.
dc.contributor.authorZwinderman, Aeilko H.
dc.contributor.authorReinertsen, Ingerid
dc.contributor.authorSolheim, Ole
dc.contributor.authorDe Witt Hamer, Philip C.
dc.date.accessioned2022-05-10T14:27:50Z
dc.date.available2022-05-10T14:27:50Z
dc.date.created2021-06-25T21:18:27Z
dc.date.issued2021
dc.identifier.citationCancers. 2021, 13 (12), .en_US
dc.identifier.issn2072-6694
dc.identifier.urihttps://hdl.handle.net/11250/2995128
dc.description.abstractTreatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.en_US
dc.description.abstractGlioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentationsen_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectNeurokirurgiske / nevrokirurgiske prosedyreren_US
dc.subjectNeurosurgical Proceduresen_US
dc.subjectKlinisk beslutningsstøtteen_US
dc.subjectClinicial decision supporten_US
dc.subjectKunstig intelligensen_US
dc.subjectArtificial intelligenceen_US
dc.titleGlioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentationsen_US
dc.title.alternativeGlioblastoma Surgery Imaging—Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentationsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.subject.nsiVDP::Radiologi og bildediagnostikk: 763en_US
dc.subject.nsiVDP::Radiology and diagnostic imaging: 763en_US
dc.source.pagenumber23en_US
dc.source.volume13en_US
dc.source.journalCancersen_US
dc.source.issue12en_US
dc.identifier.doi10.3390/cancers13122854
dc.identifier.cristin1918664
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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