Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018.
Purpose: The Liver Imaging Reporting and Data System (LI-RADS) was created to standardize the diagnostic criteria for hepatocellular carcinoma (HCC) and has undergone multiple revisions including a recent update in 2018 (v2018). The primary aim of this study was to determine the diagnostic performan...
| Publicado en: | Abdominal Radiology Vol. 44; no. 6; pp. 2116 - 2133 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136674608&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136674608 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Jun2019 vid: 44 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136674608 10.1007/s00261-019-01948-x 136674608 ppf: 2116 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018. aug: au: Ludwig, Daniel R. Fraum, Tyler J. Ballard, David H. Tsai, Richard Naeem, Muhammad LeBlanc, Maverick Salter, Amber Shetty, Anup S. Tsung, Allan Borhani, Amir A. Furlan, Alessandro Cannella, Roberto Fowler, Kathryn J. affil: Mallinckrodt Institute of Radiology, Washington University School of Medicine, Campus Box 8131, 510 S. Kingshighway Blvd, 63104, Saint Louis, MO, USA sug: ab: Purpose: The Liver Imaging Reporting and Data System (LI-RADS) was created to standardize the diagnostic criteria for hepatocellular carcinoma (HCC) and has undergone multiple revisions including a recent update in 2018 (v2018). The primary aim of this study was to determine the diagnostic performance and interrater reliability (IRR) of LI-RADS v2018 for distinguishing HCC from non-HCC primary hepatic malignancy in patients 'at-risk' for HCC. A secondary aim was to assess the impact of changes introduced in the v2018 diagnostic algorithm. Methods: This retrospective study combined a 10-year experience of pathologically proven primary liver malignancies from two large liver transplant centers. Two blinded readers independently evaluated each lesion and assigned a LI-RADS diagnostic category, additionally scoring all relevant imaging features. Changes in category based on the reader-provided features and the new v2018 criteria were assessed by a study coordinator. Results: The final study cohort comprised 105 HCCs and 73 non-HCC primarily liver malignancies. LI-RADS had a high specificity for distinguishing HCC from non-HCC (89% and 90% for reader 1 and reader 2, respectively), and IRR was moderate to substantial for final LI-RADS category and most features. Revision of the LI-RADS v2018 diagnostic algorithm resulted in very few changes [5 (2.8%) and 3 (1.7%) for reader 1 and reader 2, respectively] in overall lesion classification. Conclusion: LI-RADS diagnostic categories and features had moderate to substantial IRR and high specificity for distinguishing HCC from non-HCC primary liver malignancy. Revision of LI-RADS v2018 diagnostic algorithm resulted in reclassification of very few lesions. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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