Skip to main navigation Skip to search Skip to main content

LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis

  • Haben Dawit
  • , Eric Lam
  • , Matthew D.F. McInnes
  • , Christian B. van der Pol
  • , Mustafa R. Bashir
  • , Jean Paul Salameh
  • , Brooke Levis
  • , Claude B. Sirlin
  • , Victoria Chernyak
  • , Sang Hyun Choi
  • , So Yeon Kim
  • , Tyler J. Fraum
  • , An Tang
  • , Hanyu Jiang
  • , Bin Song
  • , Jin Wang
  • , Stephanie R. Wilson
  • , Heejin Kwon
  • , Andrea S. Kierans
  • , Ijin Joo
  • Maxime Ronot, Ji Soo Song, Joanna Podgórska, Grzegorz Rosiak, Zhen Kang, Brian C. Allen, Andreu F. Costa*
*Corresponding author for this work
  • University of Toronto
  • University of Ottawa
  • McMaster University
  • Center for Advanced Magnetic Resonance Development
  • Duke University
  • Queen's University Kingston
  • Lady Davis Institute for Medical Research
  • University of California at San Diego
  • Memorial Sloan-Kettering Cancer Center
  • University of Ulsan
  • Washington University St. Louis
  • Centre Hospitalier de L'Universite de Montreal
  • Sichuan University
  • Sun Yat-Sen University
  • University of Calgary
  • Dong-A University
  • New York Presbyterian Hospital
  • Seoul National University
  • Clichy and Université Paris Cité
  • Hôpital Beaujon
  • Medical University of Warsaw
  • Huazhong University of Science and Technology
  • Department of Radiology
  • Dalhousie University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Background: The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose: To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods: Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results: Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion: Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features.

Original languageEnglish
Article number231501
JournalRadiology
Volume310
Issue number2
DOIs
StatePublished - 2024.02

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Quacquarelli Symonds(QS) Subject Topics

  • Medicine

Fingerprint

Dive into the research topics of 'LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis'. Together they form a unique fingerprint.

Cite this