Evidence map›Paper›PMID 39718628›Full record

ReviewAbdominal radiology (New York)2025

Common pitfalls and diagnostic challenges in the application of LI-RADS CT/MRI algorithms: a comprehensive review.

Omar Kamal, Alexandra Roudenko, Mahmoud Diab, Anuradha Shenoy-Bhangle, James Lee, Claude B Sirlin, Alice Fung, Khaled M Elsayes

Abstract readReview
PubMed Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Omar KamalOregon Health & Science University, Portland, Oregon, USA. kamal@ohsu.edu.
Alexandra RoudenkoAllegheny Health Network, Pittsburgh, USA.
Mahmoud DiabThe University of Texas MD Anderson Cancer Center, Houston, USA.
Anuradha Shenoy-BhangleMassachusetts General Hospital, Boston, USA.
James LeeUniversity of Kentucky, Lexington, USA.
Claude B SirlinLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, USA.
Alice FungOregon Health & Science University, Portland, Oregon, USA.
Khaled M ElsayesThe University of Texas MD Anderson Cancer Center, Houston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Liver Imaging Reporting and Data System (LI-RADS) was developed to standardize the interpretation and reporting of liver observations in at-risk populations, aiding in the diagnosis of hepatocellular carcinoma (HCC). Despite its advantages, the application of LI-RADS can be challenging due to the complexity of liver pathology and imaging interpretation. This comprehensive review highlights common pitfalls encountered in LI-RADS application and offers practical strategies to enhance diagnostic accuracy and consistency among radiologists. Key areas of difficulty include misapplication in non-high-risk populations, misinterpretation of major imaging features such as arterial phase hyperenhancement and washout, and incorrect application of ancillary features. Additionally, the review addresses challenges related to atypical HCC presentations and HCC mimics. By recognizing and addressing these pitfalls, radiologists can improve diagnostic accuracy and avoid common mistakes in the diagnosis of HCC.

Indexed as

AlgorithmsCarcinoma, HepatocellularLiver NeoplasmsMagnetic Resonance ImagingRadiology Information SystemsTomography, X-Ray ComputedDiagnosis, DifferentialHumansHCCLI-RADSPitfalls

Identifiers

PMID39718628

What OpenQuestion holds

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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 OpenQuestion graph.