Evidence map›Paper›PMID 39335171›Full record

ReviewCancers2024

Value of 11C-Methionine PET Imaging in High-Grade Gliomas: A Narrative Review.

Zsanett Debreczeni-Máté, Omar Freihat, Imre Törő, Mihály Simon, Árpád Kovács, David Sipos

Abstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. 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

6 authors.

Zsanett Debreczeni-MátéDoctoral School of Health Sciences, Faculty of Health Sciences, University of Pécs, 7621 Pécs, Hungary.
Omar FreihatDepartment of Public Health, College of Health Science, Abu Dhabi University, Abu Dhabi P.O. Box 59911, United Arab Emirates.
Imre TörőDepartment of Oncoradiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
Mihály SimonDepartment of Oncoradiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
Árpád KovácsDoctoral School of Health Sciences, Faculty of Health Sciences, University of Pécs, 7621 Pécs, Hungary.ORCID 0000-0002-8469-5764
David SiposDoctoral School of Health Sciences, Faculty of Health Sciences, University of Pécs, 7621 Pécs, Hungary.ORCID 0000-0001-9615-1740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

11C-Methionine (MET) is a widely utilized amino acid tracer in positron emission tomography (PET) imaging of primary brain tumors. 11C-MET PET offers valuable insights for tumor classification, facilitates treatment planning, and aids in monitoring therapeutic response. Its tracer properties allow better delineation of the active tumor volume, even in regions that show no contrast enhancement on conventional magnetic resonance imaging (MRI). This review focuses on the role of MET-PET in brain glioma imaging. The introduction provides a brief clinical overview of the problems of high-grade and recurrent gliomas. It discusses glioma management, radiotherapy planning, and the difficulties of imaging after chemoradiotherapy (pseudoprogression or radionecrosis). The mechanism of MET-PET is described. Additionally, the review encompasses the application of MET-PET in the context of primary gliomas, addressing its diagnostic precision, utility in tumor classification, prognostic value, and role in guiding biopsy procedures and radiotherapy planning.

Indexed as

11C-METgliomahigh-grade gliomahybrid imagingmultimodal imagingPET/CT

Identifiers

PMID39335171
PMCPMC11429583

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.