Evidence map›Paper›PMID 24944999›Full record

ReviewLiver cancer2014

Hypervascular benign and malignant liver tumors that require differentiation from hepatocellular carcinoma: key points of imaging diagnosis.

Takamichi Murakami, Masakatsu Tsurusaki

Open access · goldAbstract readReview
In one paragraph

Review in Liver cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
5.6field-weighted citation impact, top 3% of its field
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

32 citing papers in PubMed, 88 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Focal Lesions of the Liver and Radiomics: What Do We Know?Diagnostics (Basel, Switzerland) · 2023
    Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Observational
  14. Article
  15. Article
  16. Article
  17. Hepatic tumors: pitfall in diagnostic imaging.Acta bio-medica : Atenei Parmensis · 2020
    Review
  18. Article
  19. Application of new ultrasound techniques for focal liver lesions.Journal of medical ultrasonics (2001) · 2020
    Review
  20. 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

2 authors at 1 institution in 1 country.

Takamichi MurakamiDepartment of Radiology, Kinki University Faculty of Medicine, Osaka, Japan.
Masakatsu TsurusakiDepartment of Radiology, Kinki University Faculty of Medicine, Osaka, Japan.
Kindai University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most liver tumors are benign and hypervascular, and it is important to avoid unnecessary interventions for benign lesions. This review describes the typical and atypical imaging features of common hypervascular benign liver tumors and outlines a general approach to distinguishing between benign and malignant hepatic lesions. There are many types of benign liver tumors that need to be differentiated from hepatocellular carcinoma (HCC). Therefore, it is very important to know the imaging characteristics of benign tumors. Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging is helpful in diagnosing hypervascular pseudotumors, focal nodular hyperplasia, and nodular lesions associated with alcohol-induced hepatitis. There are also some hypervascular malignant tumors, such as cholangiocarcinoma, cholangiolocellular carcinoma, mixed type tumors, and metastatic liver tumors, which also required differentiation from HCC.

Indexed as

Benign liver tumorComputed tomographyHepatocellular carcinomaMagnetic resonance imaging

Identifiers

PMID24944999
PMCPMC4057794
OpenAlexW2008714049

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.