Evidence map›Paper›PMID 39114182›Full record

ArticleNeuro-oncology advances

Exploring molecular glioblastoma: Insights from advanced imaging for a nuanced understanding of the molecularly defined malignant biology.

Michael Griessmair, Claire Delbridge, Julian Ziegenfeuter, Kirsten Jung, Tobias Mueller, Severin Schramm, Denise Bernhardt, Friederike Schmidt-Graf, Olivia Kertels, Marie Thomas and 6 more

Abstract read
In one paragraph

Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

16 authors.

Michael GriessmairDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.ORCID https://orcid.org/0009-0007-3518-0792
Claire DelbridgeDepartment of Pathology, TU Munich, Munich, Germany.
Julian ZiegenfeuterDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Kirsten JungDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Tobias MuellerDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Severin SchrammDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Denise BernhardtDepartment of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Friederike Schmidt-GrafDepartment of Neurology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Olivia KertelsDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Marie ThomasDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Claus ZimmerDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Bernhard MeyerDepartment of Neurosurgery, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Stephanie E CombsDepartment of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Igor YakushevDepartment of Nuclear Medicine, Klinikum Rechts der Isar, TU Munich, Munich, Germany.
Benedikt WiestlerDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-2963-7772
Marie-Christin MetzDepartment of Neuroradiology, Klinikum Rechts der Isar, TU Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-1459-5741

Funding

Generalizable quantitative imaging and machine learning signatures in glioblastoma, for precision diagnostics and personalized treatment: the ReSPOND consortiumR01CA269948 · NCI · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos · 2022 to 2026
$3.2M
NCI NIH HHS R01 CA269948
6 · The paper itself

Abstract

Background: Molecular glioblastoma (molGB) does not exhibit the histologic hallmarks of a grade 4 glioma but is nevertheless diagnosed as glioblastoma when harboring specific molecular markers. MolGB can easily be mistaken for similar-appearing lower-grade astrocytomas. Here, we investigated how advanced imaging could reflect the underlying tumor biology. Methods: Clinical and imaging data were collected for 7 molGB grade 4, 9 astrocytomas grade 2, and 12 astrocytomas grade 3. Four neuroradiologists performed VASARI-scoring of conventional imaging, and their inter-reader agreement was assessed using Fleiss κ coefficient. To evaluate the potential of advanced imaging, 2-sample Results: While conventional VASARI imaging features did not allow for reliable differentiation between glioma entities, rCBV was significantly higher in molGB compared to astrocytomas for the 5th and 95th percentile, mean, and median values ( Discussion: Quantitative analysis of diffusion and perfusion parameters shows potential in reflecting the malignant tumor biology of molGB. It may increase awareness of molGB in a nonenhancing, "benign" appearing tumor. Our results support the emerging hypothesis that molGB might present glioblastoma captured at an early stage of gliomagenesis.

Indexed as

850k methylation analysisadvanced imaging biomarkersfully automated tumor segmentationstumorigenesis of glioblastoma

Identifiers

PMID39114182
PMCPMC11304596

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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.