Publication:
Inter-Reader Agreement for Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System Major Features and Final Categorization: A Subanalysis From a Prospective Multicenter Study.

cris.virtual.author-orcid0000-0003-4562-9016
cris.virtualsource.author-orcida4094c89-e546-4ec5-8814-a2e707b77691
datacite.rightsopen.access
dc.contributor.authorKuon Yeng Escalante, Cristina M
dc.contributor.authorSiu Xiao, Tania
dc.contributor.authorKono, Yuko
dc.contributor.authorPiscaglia, Fabio
dc.contributor.authorWilson, Stephanie R
dc.contributor.authorMedellin, Alexandra
dc.contributor.authorRodgers, Shuchi K
dc.contributor.authorPlanz, Virginia
dc.contributor.authorKamaya, Aya
dc.contributor.authorFetzer, David T
dc.contributor.authorBerzigotti, Annalisa
dc.contributor.authorSidhu, Paul S
dc.contributor.authorWessner, Corinne E
dc.contributor.authorBradigan, Kristen
dc.contributor.authorEisenbrey, John R
dc.contributor.authorForsberg, Flemming
dc.contributor.authorLyshchik, Andrej
dc.date.accessioned2024-11-11T12:55:42Z
dc.date.available2024-11-11T12:55:42Z
dc.date.issued2025-02
dc.descriptionKollektivautorenschaft Forschungsgruppe "CEUS LI-RADS Trial Group", Autorin: Iuliana-Pompilia Radu (Department of Visceral Surgery and Medicine)
dc.description.abstractObjectives Contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) is used to definitively diagnose hepatocellular carcinoma (HCC) in patients at risk. However, the user variability associated with CEUS LI-RADS has not been validated in North American and European patients. This study aims to evaluate the inter-reader agreements of CEUS LI-RADS features for, and final categorization of, HCC in patients at risk.Methods This retrospective multicenter clinical study used the database of a previous prospective multinational study, evaluating the accuracy of CEUS LI-RADS for HCC diagnosis in patients at risk. All cases were first evaluated by a site physician performing/supervising the CEUS examination. Randomly selected cases were re-evaluated by a blinded central reader. Final diagnosis was confirmed with the reference standard, which was a composite of imaging tests and histology. Cohen's kappa test was used to evaluate inter-reader agreement.Results This study included 150 liver nodules and 58.0% (87/150) were confirmed as HCC, 4.7% (7/150) non-HCC malignancies, 22.7% (34/150) had no confirmed final diagnosis, and 14.7% (22/150) were nonmalignant. Inter-reader agreements were substantial for CEUS LI-RADS categorization (κ = 0.61; 95% confidence interval [CI]: 0.51-0.71) and major features assessment (ranged κ = 0.64-0.78), LR-5 (κ = 0.65; 95% CI: 0.52-0.77), and LR-M (κ = 0.67; 95% CI: 0.44-0.90), while for LR-1 and LR-2 categorization was almost perfect (κ = 0.85; 95% CI: 0.65-1.00).Conclusion Our study reported a substantial inter-reader agreement for overall CEUS LI-RADS categorization, especially for LR-5 and LR-M, and major imaging features of HCC, further confirming CEUS LI-RADS as a valuable and reliable tool for diagnosis of HCC.
dc.description.numberOfPages9
dc.description.sponsorshipClinic of Visceral Surgery and Medicine, Hepatology
dc.identifier.doi10.48620/76139
dc.identifier.pmid39470295
dc.identifier.publisherDOI10.1002/jum.16608
dc.identifier.urihttps://boris-portal.unibe.ch/handle/20.500.12422/188861
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofJournal of Ultrasound in Medicine
dc.relation.issn0278-4297
dc.subjectCEUS
dc.subjectLI‐RADS
dc.subjectagreement
dc.subjectinter‐reader
dc.titleInter-Reader Agreement for Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System Major Features and Final Categorization: A Subanalysis From a Prospective Multicenter Study.
dc.typearticle
dspace.entity.typePublication
dspace.file.typetext
oaire.citation.endPage357
oaire.citation.issue2
oaire.citation.startPage349
oaire.citation.volume44
unibe.additional.sponsorshipClinic of Visceral Surgery and Medicine, Hepatology
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unibe.contributor.rolecorresponding author
unibe.description.ispublishedpub
unibe.refereedtrue
unibe.subtype.articlejournal

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