Evidence map›Paper›PMID 39433603›Full record

ReviewAbdominal radiology (New York)2025

CT/MRI technical pitfalls for diagnosis and treatment response assessment using LI-RADS and how to optimize.

Omar Kamal, Maryam Haghshomar, Jessica Yang, Tasneem Lalani, Bijan Bijan, Vahid Yaghmai, Mishal Mendiratta-Lala, Cheng William Hong, Kathryn J Fowler, Claude B Sirlin and 4 more

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. 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

14 authors.

Omar KamalOregon Health and Science University, Portland, OR, USA. kamal@ohsu.edu.
Maryam HaghshomarNorthwestern University Feinberg School of Medicine, Chicago, IL, USA.
Jessica YangRoyal Prince Alfred and Concord Hospitals, Sydney, NSW, Australia.
Tasneem LalaniUniversity of Massachusetts Chan Medical School, Worcester, MA, USA.
Bijan BijanUniversity of California Davis Medical Center, Sacramento, CA, USA.
Vahid YaghmaiUniversity of California, Irvine, Irvine, CA, USA.
Mishal Mendiratta-LalaMichigan Medicine, Ann Arbor, MI, USA.
Cheng William HongUniversity of California, San Francisco, San Francisco, CA, USA.
Kathryn J FowlerScripps Medical Group, San Diego, CA, USA.
Claude B SirlinUniversity of California, San Diego, San Diego, CA, USA.
Avinash KambadakoneMassachusetts General Hospital, Boston, MA, USA.
James LeeUniversity of Kentucky, Lexington, KY, USA.
Amir A BorhaniNorthwestern University Feinberg School of Medicine, Chicago, IL, USA.
Alice FungOregon Health and Science University, Portland, OR, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC), the most common primary liver cancer, is a significant global health burden. Accurate imaging is crucial for diagnosis and treatment response assessment, often eliminating the need for biopsy. The Liver Imaging Reporting and Data System (LI-RADS) standardizes the interpretation and reporting of liver imaging for diagnosis and treatment response assessment, categorizing observations using defined categories that are based on the probability of malignancy or post-treatment tumor viability. Optimized imaging protocols are essential for accurate visualization and characterization of liver findings by LI-RADS. Common technical pitfalls, such as suboptimal postcontrast phase timing, and MRI-specific challenges like subtraction misregistration artifacts, can significantly reduce image quality and diagnostic accuracy. The use of hepatobiliary contrast agents introduces additional challenges including arterial phase degradation and suboptimal uptake in advanced cirrhosis. This review provides radiologists with comprehensive insights into the technical aspects of liver imaging for LI-RADS. We discuss common pitfalls encountered in routine clinical practice and offer practical solutions to optimize imaging techniques. We also highlight technical advances in liver imaging, including multi-arterial MR acquisition and compressed sensing. By understanding and addressing these technical aspects, radiologists can improve accuracy and confidence in the diagnosis and treatment response assessment for hepatocellular carcinoma.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMagnetic Resonance ImagingRadiology Information SystemsTomography, X-Ray ComputedContrast MediaHumansContrast MediaHepatocellular carcinomaLI-RADSLiver imagingTechnical optimization

Identifiers

What OpenQuestion holds

Textmetadata
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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.