Evidence map›Paper›PMID 29487977›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2018

Biological tumour volumes of gliomas in early and standard 20-40 min

M Unterrainer, I Winkelmann, B Suchorska, A Giese, V Wenter, F W Kreth, J Herms, P Bartenstein, J C Tonn, N L Albert

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

20 citing papers in PubMed, 50 citations in OpenAlex.

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  5. Assessment of Brain Tumour Perfusion Using Early-PhaseMolecular imaging and biology · 2024
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  8. TSPO PET signal using [European journal of nuclear medicine and molecular imaging · 2023
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  9. A Head-to-Head Comparison ofJournal of clinical medicine · 2022
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  10. Review
  11. Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET.Cancer imaging : the official publication of the International Cancer Imaging Society · 2021
    Article
  12. Article
  13. Article
  14. TSPO PET, tumour grading and molecular genetics in histologically verified glioma: a correlativeEuropean journal of nuclear medicine and molecular imaging · 2020
    Article
  15. Comparison of [Molecular imaging and biology · 2020
    Article
  16. Approaches to PET Imaging of Glioblastoma.Molecules (Basel, Switzerland) · 2020
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  17. Comparison ofEuropean journal of nuclear medicine and molecular imaging · 2019
    Article
  18. Article
  19. Article
  20. Voxel-wise analysis of dynamicEJNMMI research · 2018
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

M UnterrainerDepartment of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
I WinkelmannDepartment of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
B SuchorskaDepartment of Neurosurgery, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
A GieseDepartment of Neuropathology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
V WenterDepartment of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
F W KrethDepartment of Neurosurgery, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
J HermsDepartment of Neuropathology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
P BartensteinDepartment of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
J C TonnDepartment of Neurosurgery, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
N L AlbertDepartment of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. nathalie.albert@med.uni-muenchen.de.
LMU Klinikum · DEGerman Cancer Research Center · DELudwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFor the clinical evaluation of O-(2-

methodsThe analysis included 245 patients with newly diagnosed, histologically verified glioma and a positive

resultsIn 52.2% of the patients (128/245), a significant difference in BTV of >20% between early and standard summation images was found. While 44.3% of WHO grade II gliomas (31 of 70) showed a significantly smaller BTV in the early summation images, 35.0% of WHO grade III gliomas (28/80) and 37.9% of WHO grade IV gliomas (36/95) had a significantly larger BTVs. Among IDH-wildtype gliomas, an even higher portion (44.4%, 67/151) showed significantly larger BTVs in the early summation images, which was observed in 5.3% (5/94) of IDH-mutant gliomas only: most of the latter had significantly smaller BTVs in the early summation images, i.e. 51.2% of IDH-mutant gliomas without 1p/19q codeletion (21/41) and 39.6% with 1p/19q codeletion (21/53).

conclusionBTVs delineated in early and standard summation images differed significantly in more than half of gliomas. While the standard summation images seem appropriate for delineation of LGG as well as IDH-mutant gliomas, a remarkably high percentage of HGG and, particularly, IDH-wildtype gliomas were depicted with significantly larger volumes in early summation images. This finding might be of interest for optimization of treatment planning (e.g. radiotherapy) in accordance with the individual IDH mutation status.

Indexed as

Tumor BurdenAdultAgedBrain NeoplasmsFemaleGliomaHumansMaleMiddle AgedMutationPositron-Emission TomographyRetrospective Studies1p/19q codeletionBTVFET PETGliomaIDH

Identifiers

PMID29487977
OpenAlexW2793127683

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.