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Liver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis

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dc.contributor.authorLee, Sunyoung-
dc.contributor.authorKim, Yeun-Yoon-
dc.contributor.authorShin, Jaeseung-
dc.contributor.authorRoh, Yun Ho-
dc.contributor.authorChoi, Jin-Young-
dc.contributor.authorChernyak, Victoria-
dc.contributor.authorSirlin, Claude B.-
dc.date.accessioned2024-04-11T06:35:22Z-
dc.date.available2024-04-11T06:35:22Z-
dc.date.created2024-04-18-
dc.date.issued2024-03-
dc.identifier.issn0938-7994-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/198823-
dc.description.abstractObjectiveWe performed an updated meta-analysis to determine the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS, LR) 5 category for hepatocellular carcinoma (HCC) using LI-RADS version 2018 (v2018), and to evaluate differences by imaging modalities and type of MRI contrast material.MethodsThe MEDLINE and Embase databases were searched for studies reporting the performance of LR-5 using v2018 for diagnosing HCC. A bivariate random-effects model was used to calculate the pooled per-observation sensitivity and specificity. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material.ResultsForty-eight studies qualified for the meta-analysis, comprising 9031 patients, 10,547 observations, and 7216 HCCs. The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC were 66% (95% CI, 61-70%) and 91% (95% CI, 89-93%), respectively. In the subgroup analysis, MRI with extracellular agent (ECA-MRI) showed significantly higher pooled sensitivity (77% [95% CI, 70-82%]) than CT (66% [95% CI, 58-73%]; p = 0.023) or MRI with gadoxetate (Gx-MRI) (65% [95% CI, 60-70%]; p = 0.001), but there was no significant difference between ECA-MRI and MRI with gadobenate (gadobenate-MRI) (73% [95% CI, 61-82%]; p = 0.495). Pooled specificities were 88% (95% CI, 80-93%) for CT, 92% (95% CI, 86-95%) for ECA-MRI, 93% (95% CI, 91-95%) for Gx-MRI, and 91% (95% CI, 84-95%) for gadobenate-MRI without significant differences (p = 0.084-0.803).ConclusionsLI-RADS v2018 LR-5 provides high specificity for HCC diagnosis regardless of modality or contrast material, while ECA-MRI showed higher sensitivity than CT or Gx-MRI.Clinical relevance statementRefinement of the criteria for improving sensitivity while maintaining high specificity of LR-5 for HCC diagnosis may be an essential future direction.Key Points & BULL; The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively.& BULL; ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001).& BULL; LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.Key Points & BULL; The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively.& BULL; ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001).& BULL; LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.Key Points & BULL; The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively.& BULL; ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001).& BULL; LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.-
dc.description.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherSpringer International-
dc.relation.isPartOfEUROPEAN RADIOLOGY-
dc.relation.isPartOfEUROPEAN RADIOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleLiver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiology (영상의학교실)-
dc.contributor.googleauthorLee, Sunyoung-
dc.contributor.googleauthorKim, Yeun-Yoon-
dc.contributor.googleauthorShin, Jaeseung-
dc.contributor.googleauthorRoh, Yun Ho-
dc.contributor.googleauthorChoi, Jin-Young-
dc.contributor.googleauthorChernyak, Victoria-
dc.contributor.googleauthorSirlin, Claude B.-
dc.identifier.doi10.1007/s00330-023-10134-z-
dc.relation.journalcodeJ00851-
dc.identifier.eissn1432-1084-
dc.identifier.pmid37656177-
dc.subject.keywordLiver neoplasm-
dc.subject.keywordCarcinoma, hepatocellular-
dc.subject.keywordRadiology-
dc.subject.keywordDiagnosis-
dc.subject.keywordContrast media-
dc.contributor.alternativeNameKim, Yeun-Yoon-
dc.contributor.affiliatedAuthorLee, Sunyoung-
dc.contributor.affiliatedAuthorKim, Yeun-Yoon-
dc.contributor.affiliatedAuthorRoh, Yun Ho-
dc.contributor.affiliatedAuthorChoi, Jin-Young-
dc.identifier.scopusid2-s2.0-85169325223-
dc.identifier.wosid001060221100002-
dc.citation.volume34-
dc.citation.number3-
dc.citation.startPage1502-
dc.citation.endPage1514-
dc.identifier.bibliographicCitationEUROPEAN RADIOLOGY, Vol.34(3) : 1502-1514, 2024-03-
dc.identifier.rimsid83312-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorLiver neoplasm-
dc.subject.keywordAuthorCarcinoma, hepatocellular-
dc.subject.keywordAuthorRadiology-
dc.subject.keywordAuthorDiagnosis-
dc.subject.keywordAuthorContrast media-
dc.subject.keywordPlusLI-RADS-
dc.subject.keywordPlusGADOXETIC ACID-
dc.subject.keywordPlusCOMPUTED-TOMOGRAPHY-
dc.subject.keywordPlusHIGH-RISK-
dc.subject.keywordPlusCT-
dc.subject.keywordPlusMRI-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusACCURACY-
dc.subject.keywordPlusCRITERIA-
dc.subject.keywordPlusCEUS-
dc.type.docTypeArticle-
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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