Evidence map›Paper›PMID 29492326›Full record

ArticleSurgical neurology international2018

Diagnosis of demyelinating brain lesion simulating brain tumors on fast imaging employing steady-state acquisition magnetic resonance imaging.

Takeshi Onishi, Naoki Nitta, Tadateru Fukami, Satoshi Nakasu, Kazuhiko Nozaki

Open access · hybridAbstract read
In one paragraph

Article in Surgical neurology international, 2018. 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, top 93% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

5 authors at 2 institutions in 2 countries.

Takeshi OnishiDepartment of Neurosurgery, Shiga University of Medical Science, Shiga, Japan.
Naoki NittaDepartment of Neurosurgery, Shiga University of Medical Science, Shiga, Japan.
Tadateru FukamiDepartment of Neurosurgery, Shiga University of Medical Science, Shiga, Japan.
Satoshi NakasuDepartment of Neurosurgery, Kusatsu General Hospital, Shiga, Japan.
Kazuhiko NozakiDepartment of Neurosurgery, Shiga University of Medical Science, Shiga, Japan.
Harvard University · USShiga University of Medical Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA single inflammatory demyelinating brain lesion sometimes mimics a brain tumor on conventional magnetic resonance imaging (MRI), and thus poses a considerable diagnostic challenge. We assessed the usefulness of a new MRI technique, fast imaging employing steady-state acquisition (FIESTA), for the diagnosis of inflammatory demyelinating disease (IDD).

methodsThree patients (2 males, 1 female) with a histopathologically proven inflammatory demyelinating brain lesion which mimicked a brain tumor on MRI were evaluated with a post-contrast three-dimensional FIESTA sequence before biopsy and treatment. Those images were compared with the images of intra-axial brain tumors (

resultsPreoperative FIESTA showed an iso- or slightly hyperintense distinct intralesional structure that appeared reticulate or broad-line in patients with IDD. These structures traversed a hyperintense demyelinating lesion in the deep grey matter (DGM) and were connected to the surrounding extralesional area, which appeared to be dense fibers between DGM. Such distinct intralesional structures were not observed in most brain tumors.

conclusionReticulate or broad-line-like intralesional structures on FIESTA may, therefore, be suggestive of IDD rather than indicate a brain tumor.

Indexed as

Brain tumordeep gray matterFIESTAinflammatory demyelinating lesion

Identifiers

PMID29492326
PMCPMC5820830
OpenAlexW2802597206

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.