Evidence map›Paper›PMID 28204853›Full record

ReviewDer Radiologe2017

[Optimized detection and characterization of liver metastases : The role of current MRI contrast agents].

J M Weinrich, L Well, P Bannas

Erratum issuedAbstract readReview
PubMed Publisher
In one paragraph

Review in Der Radiologe, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

J M WeinrichZentrum für Radiologie und Endoskopie, Klinik und Poliklinik für diagnostische und interventionelle Radiologie und Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Gebäude Ost 26, Martinistr. 52, 20246, Hamburg, Deutschland.
L WellZentrum für Radiologie und Endoskopie, Klinik und Poliklinik für diagnostische und interventionelle Radiologie und Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Gebäude Ost 26, Martinistr. 52, 20246, Hamburg, Deutschland.
P BannasZentrum für Radiologie und Endoskopie, Klinik und Poliklinik für diagnostische und interventionelle Radiologie und Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Gebäude Ost 26, Martinistr. 52, 20246, Hamburg, Deutschland. p.bannas@uke.de.
Klinik und Poliklinik für Nuklearmedizin · DEUniversity Medical Center Hamburg-Eppendorf · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metastases are the most common malignant lesions of the liver. The presence of liver metastases is an important prognostic factor and is decisive for the further management, especially in patients with colorectal cancer. Detection and characterization of liver metastases as well as differentiation from benign lesions are of high importance and a daily challenge in clinical radiology. Contrast-enhanced magnetic resonance imaging (MRI) has the highest sensitivity in detecting liver metastases. The sensitivity of MRI has been further increased due to the development of liver-specific contrast agents. This article describes the role of extracellular and hepatobiliary contrast agents for the detection and characterization of liver metastases. Moreover, the current knowledge on safety, sequence optimization, transient severe dyspnea and the combination of hepatobiliary with intravascular contrast agents for liver imaging is discussed.

Indexed as

Colorectal NeoplasmsContrast MediaHumansLiver NeoplasmsMagnetic Resonance ImagingContrast MediaLiver imagingPrognosisSequence optimizationTreatment protocolsTumor patients

Identifiers

PMID28204853
OpenAlexW2595271211

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.