Evidence map›Paper›PMID 31289531›Full record

ArticleOncology letters2019

Clinical value of magnetic resonance imaging in identifying multiple cerebral gliomas from primary central nervous system lymphoma.

Yushan Chen, Alai Zhan

Abstract read
In one paragraph

Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Yushan ChenDepartment of Radiology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian 363000, P.R. China.
Alai ZhanDepartment of Radiology, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian 363000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical value of magnetic resonance imaging (MRI) in identifying and diagnosing multiple cerebral glioma (MCG) from primary central nervous system lymphoma (PCNSL) was evaluated. A total of 21 patients with MCG diagnosed clinically and pathologically in Zhangzhou Municipal Hospital from March 2016 to April 2017 were selected as group A, and 30 patients with PCNSL diagnosed in Zhangzhou Affiliated Hospital of Fujian Medical University during the same period as group B. Plain MRI, enhanced MRI and diffusion weighted imaging (DWI) were performed in all patients, the apparent diffusion coefficient (ADC) value of lesions was measured, and the diagnostic efficacy of ADC for MCG and PCNSL was evaluated by receiver operating characteristic (ROC) curve. The incidence of hippocampus lesions, patchy and cystic lesions, and the heterogeneous signal of plain scan in group A was significantly higher than that in group B (P<0.05), and the incidence of basal ganglia lesions was significantly lower than that in group B (P<0.05). Mass lesions in group A were significantly less than those in group B (P<0.05). The ADC value of lesions in group A was significantly higher than that in contralateral normal white matter (P<0.05), the ADC value in group B was significantly lower than that in normal contralateral white matter (P<0.05), so the ADC value in group A was significantly higher than that in group B (P<0.05). The location, lesion shape and signal characteristic of MCG and PCNSL have their own specificity; there are significant differences in DWI signal and ADC color map signal intensity of the lesions; ADC has certain diagnostic value for MCG and PCNSL; the differential diagnosis of MCG from PCNSL by MRI is of great significance.

Indexed as

apparent diffusion coefficientdiagnosismagnetic resonance imagingmultiple cerebral gliomaprimary central nervous system lymphomaweighted imaging

Identifiers

PMID31289531
PMCPMC6540358

What OpenQuestion holds

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Registered trials

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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.