Evidence map›Paper›PMID 32877208›Full record

ArticleThe British journal of radiology2020

Pretreatment structural and arterial spin labeling MRI is predictive for p53 mutation in high-grade gliomas.

Jiaji Mao, Dabiao Deng, Zehong Yang, Wensheng Wang, Minghui Cao, Yun Huang, Jun Shen

Open access · bronzeAbstract read
In one paragraph

Article in The British journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Arterial Spin Labeling: Key Concepts and Progress Towards Use as a Clinical Tool.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
  2. Article
  3. Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.Journal of magnetic resonance imaging : JMRI · 2023
    Review
  4. 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

7 authors at 3 institutions in 1 country.

Jiaji MaoDepartment of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, China.
Dabiao DengDepartment of Medical Imaging, Guangdong 999 Brain Hospital, No. 578 Shatai Road South, Guangzhou, China.
Zehong YangDepartment of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, China.
Wensheng WangDepartment of Medical Imaging, Guangdong 999 Brain Hospital, No. 578 Shatai Road South, Guangzhou, China.
Minghui CaoDepartment of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, China.
Yun HuangDepartment of Medical Statistics, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan II Road, Guangzhou, China.
Jun ShenDepartment of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, China.
Sun Yat-sen University · CNGuangdong 999 Brain Hospital · CNSun Yat-sen Memorial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the performance of pretreatment structural and arterial spin labelling (ASL) MRI in predicting p53 mutation in patients with high-grade gliomas (HGGs).

methodsPre-treatment structural and ASL MRI were performed in 57 patients with histologically confirmed HGGs and information of p53 status. Whole-lesion histogram analysis of cerebral blood flow (CBF) images of the enhancing tumour and the peritumoral oedema in the HGGs were performed. Visually AcceSAble Rembrandt Images features were used as qualitative analysis. The differences of ASL histogram parameters and Visually AcceSAble Rembrandt Images features between HGGs with or without p53 mutation were analyzed with post hoc correction for multiple comparisons. LASSO regression was performed to select the optimal features that could predict p53 mutation, followed by receiver operating characteristic analysis to determine the predictive efficacy.

resultsA total of 33 HGGs with p53 mutation and 24 without p53 mutation were included. HGGs with mutant p53 showed lower CBF

conclusionAn integrated pre-treatment structural and ASL MRI can help to predict p53 mutation in HGGs.

Indexed as

MutationAdultArea Under CurveBrain EdemaBrain NeoplasmsCerebrovascular CirculationEcho-Planar ImagingFemaleGenes, p53GliomaHumansMagnetic Resonance ImagingMaleMiddle AgedNeoplasm GradingPreoperative PeriodSpin LabelsTumor Suppressor Protein p53

Identifiers

PMID32877208
PMCPMC8519656
OpenAlexW3081707634

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.