Evidence map›Paper›PMID 30787618›Full record

ArticleTherapeutics and clinical risk management2019

The features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging with Patlak model in relapsing-remitting multiple sclerosis.

Hua Xiong, Ping Yin, Xiaojiao Li, Chao Yang, Dan Zhang, Xianlong Huang, Zhuoyue Tang

Abstract read
In one paragraph

Article in Therapeutics and clinical risk management, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Extended perfusion protocol for MS lesion quantification.Open medicine (Warsaw, Poland) · 2020
    Article
  5. Article
  6. 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

7 authors.

Hua XiongDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.
Ping YinDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Xiaojiao LiDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.
Chao YangDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.
Dan ZhangDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.
Xianlong HuangDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.
Zhuoyue TangDepartment of Radiology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing 400014, China, zhuoyue_tang@cqmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the features of cerebral permeability and perfusion detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with Patlak model in relapsing-remitting multiple sclerosis (RRMS) and their correlations with Expanded Disability Status Scale (EDSS) scores and disease duration. PATIENTS AND

methodsTwenty-seven RRMS patients underwent conventional MRI and DCE-MRI with 3.0 T magnetic resonance scanner were enrolled in the study. A Patlak model was used to quantitatively measure MRI biomarkers, including volume transfer constant (K

resultsThe MRI biomarkers K

conclusionOur study demonstrated the abnormalities of permeability and perfusion characteristics in multiple sclerosis (MS) lesions and NAWM regions by DCE-MRI with Patlak model. The K

Indexed as

dynamic contrast-enhanced magnetic resonance imaginghistogrammultiple sclerosisPatlak modelperfusionpermeability

Identifiers

PMID30787618
PMCPMC6366346

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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.