Evidence map›Paper›PMID 41706100›Full record

SynthesisAbdominal radiology (New York)2026

Performance of CEUS LI-RADS v2017 major feature combinations: individual patient data meta-analysis.

Rawan Awad, Haresh Naringrekar, Robert G Adamo, Eric Lam, Mostafa Alabousi, Mohammed Kashif Al-Ghita, Stephanie R Wilson, Jean-Paul Salameh, Mustafa R Bashir, Andreu F Costa and 13 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

23 authors.

Rawan AwadFaculty of Medicine, University of Ottawa, Ottawa, Canada.
Haresh NaringrekarDepartment of Radiology, Thomas Jefferson University, Philadelphia, United States. haresh.naringrekar@jefferson.edu.
Robert G AdamoFaculty of Medicine, University of Ottawa, Ottawa, Canada.
Eric LamOttawa Hospital Research Institute, Ottawa Hospital, Ottawa, Canada.
Mostafa AlabousiWilliam Osler Health System, Brampton, Canada.
Mohammed Kashif Al-GhitaFaculty of Medicine, University of Ottawa, Ottawa, Canada.
Stephanie R WilsonFoothills Medical Centre, University of Calgary, Calgary, Canada.
Jean-Paul SalamehDepartment of Medical Imaging, Ottawa Hospital, Ottawa, Canada.
Mustafa R BashirCenter for Advanced Magnetic Resonance Development, Duke Medical Center, Durham, United States.
Andreu F CostaDepartment of Diagnostic Radiology, Queen Elizabeth II Health Sciences Centre, Halifax, Canada.
Christian B van der PolJuravinski Hospital and Cancer Centre, McMaster University, Hamilton, Canada.
Eleonora TerziDivision of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCSS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy.
Fabio PiscagliaDivision of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCSS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy.
Bernardo StefaniniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Li-Da ChenDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Barbara Meitner-SchellhaasDepartment of Internal Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
Deike StrobelDepartment of Internal Medicine, Universitätsklinikum Erlangen, Erlangen, Germany.
Wei WangDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xiang JingDepartment of Ultrasound, Tianjin Institute of Hepatobiliary Disease, Tianjin Third Central Hospital, Tianjin, China.
Hyo-Jin KangDepartment of Radiology, Seoul National University Hospital, Seoul, Korea, Republic of.
John R EisenbreyDepartment of Radiology, Thomas Jefferson University, Philadelphia, United States.
Adam PolikoffDepartment of Radiology, Thomas Jefferson University, Philadelphia, United States.
Matthew Df McInnesDepartment of Medical Imaging, Ottawa Hospital, Ottawa, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe LI-RADS diagnostic algorithm uses imaging features in contrast-enhanced ultrasound (CEUS) to standardize the diagnosis of hepatocellular carcinoma (HCC) in at-risk patients. However, the diagnostic performance of specific major feature combinations has not been comprehensively evaluated. PURPOSE: To evaluate the diagnostic performance of CEUS LI-RADs version 2017 major feature combinations for (HCC) in at-risk individuals across LI-RADS categories 3-5. MATERIALS AND

methodsA living systematic review and individual participant data (IPD) meta-analysis was conducted, including studies using CEUS LI-RADS v2016 or v2017 in at-risk patients, identified through database searches updated to February 2024. Eligible observations were categorized per LI-RADS guidelines, and PPVs for HCC were calculated for all major feature combinations in LI-RADS categories 3-5 using a random-effects one-step model. Risk of bias was assessed independently using a customized QUADAS-2 tool.

resultsThirteen studies were included, comprising 1575 patients (mean age, 62.8 ± 11.2 years; 79.3% male) with 1594 liver observations (median size, 37.1 mm). Pooled PPVs for HCC increased with higher CEUS LI-RADS v2017 categories: LR-3, 40.4% (95% CI: 27.2-55.1); LR-4, 69.7% (95% CI: 49.7-84.3); and LR-5, 95.1% (95% CI: 90.2-97.6). Major feature combinations did not differ from others within the same category. Most studies were at moderate to high risk of bias, primarily due to retrospective design, but sensitivity analysis restricted to low-risk observations yielded similar findings.

conclusionCEUS LI-RADS demonstrated progressively higher PPVs from LR-3 to LR-5, supporting its ability to stratify risk across HCC categories. Major feature combinations performed similarly within each category, indicating internal consistency of the system. Although only PPVs were assessed, the results align with trends seen in CT/MRI LI-RADS, with wider confidence intervals in CEUS reflecting smaller sample sizes.

Indexed as

Carcinoma, HepatocellularContrast MediaImage EnhancementLiver NeoplasmsAlgorithmsHumansSensitivity and SpecificityUltrasonographyContrast MediaContrast enhanced ultrasound (CEUS)Hepatocellular carcinoma (HCC)Individual participant data (IPD) meta-analysisLI-RADS

Identifiers

PMID41706100
PMCPMC13388517

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.