Evidence map›Paper›PMID 30825108›Full record

ReviewDigestive diseases and sciences2019

Hepatocellular Carcinoma: Current Imaging Modalities for Diagnosis and Prognosis.

Maxime Ronot, Yvonne Purcell, Valérie Vilgrain

Abstract readReview
PubMed Publisher
In one paragraph

Review in Digestive diseases and sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
–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

35 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

3 authors.

Maxime RonotDepartment of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, 100 Boulevard du Général Leclerc, Hauts-de-Seine, 92118, Clichy, France. maxime.ronot@aphp.fr.
Yvonne PurcellDepartment of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, 100 Boulevard du Général Leclerc, Hauts-de-Seine, 92118, Clichy, France.
Valérie VilgrainDepartment of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, 100 Boulevard du Général Leclerc, Hauts-de-Seine, 92118, Clichy, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As opposed to most solid cancers, hepatocellular carcinoma (HCC) does not necessarily require histological confirmation. Noninvasive diagnosis is possible and relies on imaging. In cirrhotic patients, the diagnosis can be obtained in tumors displaying typical features that include non-rim arterial phase hyperenhancement followed by washout during the portal venous and/or delayed phases on CT or MR imaging. This pattern is very specific and, as such, has been endorsed by both Western and Asian diagnostic guidelines and systems. However, its sensitivity is not very high, especially for small lesions. Numerous ancillary features favoring the diagnosis of HCC may be depicted, including appearance after injection of hepatobiliary MR imaging contrast agents. These features increase confidence in diagnosis, but cannot be used as substitutes to liver biopsy. Aside from its diagnostic purpose, imaging also helps to assess tumor biology and patient outcome, by identifying features of local invasiveness. The purpose of this review article is to offer an overview of the role of imaging for the diagnosis and prognostication of HCC.

Indexed as

Carcinoma, HepatocellularContrast MediaHumansLiver NeoplasmsPrognosisContrast MediaComputed tomographyContrast-enhanced ultrasoundHepatobiliaryHepatocellular carcinomaHypervascularityMagnetic resonance imagingWashout

Identifiers

PMID30825108

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.