Evidence map›Paper›PMID 27250577›Full record

ReviewNeurologia medico-chirurgica2016

Usefulness of positron emission tomographic studies for gliomas.

Keisuke Miyake, Daisuke Ogawa, Masaki Okada, Tetsuhiro Hatakeyama, Takashi Tamiya

Open access · goldAbstract readReview
In one paragraph

Review in Neurologia medico-chirurgica, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Usefulness ofCase reports in oncology
    Article
  5. 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

5 authors at 2 institutions in 2 countries.

Keisuke MiyakeDepartment of Neurological Surgery, Kagawa University Faculty of Medicine.
Daisuke Ogawa
Masaki Okada
Tetsuhiro Hatakeyama
Takashi Tamiya
Kagawa University · JPNeurological Surgery · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-invasive positron emission tomography (PET) enables the measurement of metabolic and molecular processes with high sensitivity. PET plays a significant role in the diagnosis, prognosis, and treatment of brain tumors and predominantly detects brain tumors by detecting their metabolic alterations, including energy metabolism, amino acids, nucleic acids, and hypoxia. Glucose metabolic tracers are related to tumor cell energy and exhibit good sensitivity but poor specificity for malignant tumors. Amino acid metabolic tracers provide a better delineation of tumors and cellular proliferation. Nucleic acid metabolic tracers have a high sensitivity for malignant tumors and cellular proliferation. Hypoxic metabolism tracers are useful for detecting resistance to radiotherapy and chemotherapy. Therefore, PET imaging techniques are useful for detecting biopsy-targeting points, deciding on tumor resection, radiotherapy planning, monitoring therapy, and distinguishing brain tumor recurrence or progression from post-radiotherapy effects. However, it is not possible to use only one PET tracer to make all clinical decisions because each tracer has both advantages and disadvantages. This study focuses on the different kinds of PET tracers and summarizes their recent applications in patients with gliomas. Combinational uses of PET tracers are expected to contribute to differential diagnosis, prognosis, treatment targeting, and monitoring therapy.

Indexed as

Positron-Emission TomographyBrain NeoplasmsGliomaHumans

Identifiers

PMID27250577
PMCPMC4945598
OpenAlexW2469099999

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.