Evidence map›Paper›PMID 29545716›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2018

Dynamic contrast-enhanced MRI versus

Feng Feng, Fulin Qiang, Aijun Shen, Donghui Shi, Aiyan Fu, Haiming Li, Mingzhu Zhang, Ganlin Xia, Peng Cao

Abstract read
In one paragraph

Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Diagnosis of spinal lesions using perfusion parameters measured by DCE-MRI and metabolism parameters measured by PET/CT.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2020
    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

9 authors.

Feng FengDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Fulin QiangDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Aijun ShenDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Donghui ShiDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Aiyan FuDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Haiming LiDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Mingzhu ZhangDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Ganlin XiaDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.
Peng CaoDepartment of Radiology, Nantong Tumor Hospital, Nantong University, Nantong 226361, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo prospectively compare the discriminative capacity of dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) with that of

methodsForty-nine patients with SPNs were included in this prospective study. Thirty-two of the patients had malignant SPNs, while the other 17 had benign SPNs. All these patients underwent DCE-MRI and

resultsPositive correlations were found between K

conclusionsDCE-MRI can be used to differentiate between benign and malignant SPNs and has the advantage of being radiation free.

Indexed as

dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)positron emission tomography/computed tomography (PET/CT)Solitary pulmonary nodule

Identifiers

PMID29545716
PMCPMC5842230

What OpenQuestion holds

Textmetadata
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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.