Evidence map›Paper›PMID 30798397›Full record

ArticleAbdominal radiology (New York)2019

Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018.

Daniel R Ludwig, Tyler J Fraum, Roberto Cannella, David H Ballard, Richard Tsai, Muhammad Naeem, Maverick LeBlanc, Amber Salter, Allan Tsung, Anup S Shetty and 3 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Abdominal radiology (New York), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Article
  5. Review
  6. Article
  7. Current State of Evidence for Use of MRI in LI-RADS.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  8. Article
  9. [Hepatobiliary phase image manifestation classification and pathological features of nodules in nodules accompanied by hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024
    Article
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  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
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  18. Article
  19. Diagnosis of Hepatocellular Carcinoma Using Gd-EOB-DTPA MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2022
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Daniel R LudwigMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA. ludwigd@wustl.edu.ORCID 0000-0002-8131-3003
Tyler J FraumMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Roberto CannellaUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
David H BallardMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Richard TsaiMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Muhammad NaeemMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Maverick LeBlancMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Amber SalterMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Allan TsungUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Anup S ShettyMallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, Campus Box 8131, Saint Louis, MO, 63104, USA.
Amir A BorhaniUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Alessandro FurlanUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Kathryn J FowlerUniversity of California San Diego, San Diego, CA, USA.

Funding

Training OPportunities in Translational Imaging Education and Research (TOP-TIER)T32EB021955 · NIBIB · WASHINGTON UNIVERSITY · PI Hongyu An, Joseph Edward Ippolito · 2017 to 2026
$2.4M
NIBIB NIH HHS T32 EB021955
6 · The paper itself

Abstract

purposeThe 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.

methodsThis 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.

resultsThe 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.

conclusionLI-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.

Indexed as

Magnetic Resonance ImagingTomography, X-Ray ComputedAdultAgedAged, 80 and overAlgorithmsCarcinoma, HepatocellularFemaleHumansImage Interpretation, Computer-AssistedLiver NeoplasmsMaleMiddle AgedReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityCirrhosisCombined hepatocellular-cholangiocarcinoma (cHCC-CCA)Interrater reliabilityIntrahepatic cholangiocarcinoma (iCCA)LI-RADS

Identifiers

PMID30798397
PMCPMC6538452

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.