Evidence map›Paper›PMID 39527256›Full record

ReviewAbdominal radiology (New York)2025

Patient centered HCC surveillance - complementary roles of ultrasound and CT/MRI.

Jason Heald, David T Fetzer, Shuchi Rodgers, Vaibhav Jain, Alice Fung, Xiaoyang Liu, Stephanie Wilson, Aya Kamaya, Robert M Marks

Abstract readReview
In one paragraph

Review in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

9 authors.

Jason HealdLoma Linda University Medical Center, Loma Linda, USA.
David T FetzerThe University of Texas Southwestern Medical Center, Dallas, USA.
Shuchi RodgersThomas Jefferson University Hospital, Philadelphia, USA.
Vaibhav JainUniversity of Massachusetts Chan Medical School, Worcester, USA.
Alice FungOregon Health & Science University, Portland, USA.
Xiaoyang LiuUniversity Medical Imaging Toronto, University Health Network, University of Toronto, Toronto, Canada.
Stephanie WilsonUniversity of Calgary, Calgary, Canada.
Aya KamayaStanford University, Stanford, USA.
Robert M MarksUniversity of California, San Diego, San Diego, USA. rmarks@health.ucsd.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide and is the fastest growing cause of cancer death in the United States (U.S.) In the U.S., current national clinical practice guidelines from the 2023 American Association for the Study of Liver Diseases (AASLD) Practice Guidance and the recently updated Liver Imaging Reporting & Data Systems (LI-RADS) Ultrasound (US) Surveillance v2024 core recommend semi-annual serum α-fetoprotein and US screening of patients deemed to be high risk for developing HCC. In this article, we will explore the transition to a patient-centered approach to HCC surveillance, including the role of the new LI-RADS US Surveillance v2024 core and the use of visualization score for determining ultrasound quality, the known risk factors for poor US image quality, and the potential options for alternative surveillance strategies when US may not be a viable option for certain patients, including multiphasic computed tomography (CT), magnetic resonance imaging (MRI), and several abbreviated MRI protocols.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMagnetic Resonance ImagingTomography, X-Ray ComputedHumansPatient-Centered CareUltrasonographyAbbreviated MRIHepatocellular carcinomaLI-RADSSurveillanceUltrasound

Identifiers

PMID39527256
PMCPMC11991968

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.