Evidence map›Paper›PMID 28721306›Full record

ReviewAmerican journal of nuclear medicine and molecular imaging2017

Role of conventional magnetic resonance imaging in the screening of epilepsy with structural abnormalities: a pictorial essay.

Xu Zhao, Zhiqiang Zhou, Wenzhen Zhu, Hongbing Xiang

Open access · greenAbstract readReview
In one paragraph

Review in American journal of nuclear medicine and molecular imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
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

4 authors at 1 institution in 1 country.

Xu ZhaoDepartment of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430030, Hubei, P. R. China.
Zhiqiang ZhouDepartment of Anesthesiology and Pain Medicine, Tongji Hospital of Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430030, Hubei, P. R. China.
Wenzhen ZhuDepartment of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430030, Hubei, P. R. China.
Hongbing XiangDepartment of Anesthesiology and Pain Medicine, Tongji Hospital of Tongji Medical College, Huazhong University of Science and TechnologyWuhan 430030, Hubei, P. R. China.
Tongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epilepsy is a chronic neurological disease with serious impact on patients and society. The causes of epilepsy comprise a heterogeneous group of disorders, rendering epilepsy diagnoses rather difficult and challenging. The primary role of MRI is to locate and define the probable anatomic epileptogenic lesions. In the developing countries, where functional MRI (fMRI) is not popular, conventional MRI (cMRI) becomes especially important in epilepsy diagnoses. Apart from that, an experienced radiologist can increase the diagnostic yield of MRI to epileptogenic lesions. Thus, we present a pictorial review focusing on the role of cMRI in the screening of epilepsy with structural abnormalities and highlighting the key findings on cMRI to help radiologists to be familiar with the characteristic findings. Considering the complexity and diversity of the structural abnormalities, we propse a mnemonic "MAGIC TVs" approach to reduce false negative diagnosis and improve the diagnosis rate.

Indexed as

Epilepsymagnetic resonance imaging

Identifiers

PMID28721306
PMCPMC5511122
OpenAlexW2979684491

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.