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Diagnostic Performance of the 2018 EASL vs. LI-RADS for Hepatocellular Carcinoma Using CT and MRI: A Systematic Review and Meta-Analysis of Comparative Studies

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dc.contributor.authorShin, Jaeseung-
dc.contributor.authorLee, Sun young-
dc.contributor.authorYOON, JAKYUNG-
dc.contributor.authorRoh, Yun Ho-
dc.date.accessioned2023-11-28T03:28:57Z-
dc.date.available2023-11-28T03:28:57Z-
dc.date.created2024-01-09-
dc.date.issued2023-12-
dc.identifier.issn1053-1807-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/196822-
dc.description.abstractBackground Hepatocellular carcinoma (HCC) can be diagnosed without pathologic confirmation in high-risk patients. Therefore, it is necessary to compare current imaging criteria for noninvasive-diagnosis of HCC.Purpose To systematically compare performance of 2018 European Association for the Study of the Liver (EASL) criteria and Liver Imaging Reporting and Data System (LI-RADS) for noninvasive-diagnosis of HCC.Study Type Systematic review and meta-analysis.Subjects Eight studies with 2232 observations, including 1617 HCCs.Field Strength/Sequence 1.5 T, 3.0 T/T2-weighted, unenhanced T1-weighted in-/opposed-phases, multiphase T1-weighted imaging.Assessment Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers independently reviewed and extracted data, including patient characteristics, index test, reference standard and outcomes, from studies intraindividually comparing the sensitivities and specificities of 2018 EASL-criteria and LR-5 of LI-RADS for HCC. Risk of bias and concerns regarding applicability were evaluated using QUADAS-2 tool. Subgroup analysis was performed based on observation size (=20 mm, 10-19 mm).Statistical Tests Bivariate random-effects model to calculate pooled per-observation sensitivity and specificity of both imaging criteria, and pooled estimates of intraindividual paired data were compared considering the correlation. Forest and linked-receiver-operating-characteristic plots were drawn, and study heterogeneity was assessed using Q-test and Higgins-index. Publication bias was evaluated by Egger&apos;s test. A P-value <0.05 was considered statistically significant, except for heterogeneity (P < 0.10).Results The sensitivity for HCC did not differ significantly between the imaging-based diagnosis using EASL-criteria (61%; 95% CI, 50%-73%) and LR-5 (64%; 95% CI, 53%-76%; P = 0.165). The specificities were also not significantly different between EASL-criteria (92%; 95% CI, 89%-94%) and LR-5 (94%; 95% CI, 91%-96%; P = 0.257). In subgroup analysis, no statistically significant differences were identified in the pooled performances between the two criteria for observations =20 mm (sensitivity P = 0.065; specificity P = 0.343) or 10-19 mm (sensitivity P > 0.999; specificity P = 0.851). There was no publication bias for EASL (P = 0.396) and LI-RADS (P = 0.526).Data Conclusion In the present meta-analysis of paired comparisons, the pooled sensitivities and specificities were not significantly different between 2018 EASL-criteria and LR-5 of LI-RADS for noninvasive-diagnosis of HCC.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherWiley-Liss-
dc.relation.isPartOfJournal of Magnetic Resonance Imaging-
dc.relation.isPartOfJOURNAL OF MAGNETIC RESONANCE IMAGING-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleDiagnostic Performance of the 2018 EASL vs. LI-RADS for Hepatocellular Carcinoma Using CT and MRI: A Systematic Review and Meta-Analysis of Comparative Studies-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiology (영상의학교실)-
dc.contributor.googleauthorShin, Jaeseung-
dc.contributor.googleauthorLee, Sun young-
dc.contributor.googleauthorYOON, JAKYUNG-
dc.contributor.googleauthorRoh, Yun Ho-
dc.identifier.doi10.1002/jmri.28716-
dc.relation.journalcodeJ01567-
dc.identifier.eissn1522-2586-
dc.identifier.pmid37010244-
dc.subject.keywordliver neoplasms-
dc.subject.keyworddiagnosis-
dc.subject.keywordsensitivity and specificity-
dc.subject.keywordcomputed tomography-
dc.subject.keywordmagnetic resonance imaging-
dc.contributor.alternativeNameYoon, Ja Kyung-
dc.contributor.affiliatedAuthorShin, Jaeseung-
dc.contributor.affiliatedAuthorLee, Sun young-
dc.contributor.affiliatedAuthorYOON, JAKYUNG-
dc.contributor.affiliatedAuthorRoh, Yun Ho-
dc.identifier.scopusid2-s2.0-85151426505-
dc.identifier.wosid000962398400001-
dc.citation.volume58-
dc.citation.number6-
dc.citation.startPage1942-
dc.citation.endPage1950-
dc.identifier.bibliographicCitationJournal of Magnetic Resonance Imaging, Vol.58(6) : 1942-1950, 2023-12-
dc.identifier.rimsid81283-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorliver neoplasms-
dc.subject.keywordAuthordiagnosis-
dc.subject.keywordAuthorsensitivity and specificity-
dc.subject.keywordAuthorcomputed tomography-
dc.subject.keywordAuthormagnetic resonance imaging-
dc.type.docTypeReview; Early Access-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryRadiology, Nuclear Medicine & Medical Imaging-
dc.relation.journalResearchAreaRadiology, Nuclear Medicine & Medical Imaging-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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