Evidence map›Paper›PMID 36632188›Full record

ArticleBrain communications2023

Meta-topologies define distinct anatomical classes of brain tumours linked to histology and survival.

Julius M Kernbach, Daniel Delev, Georg Neuloh, Hans Clusmann, Danilo Bzdok, Simon B Eickhoff, Victor E Staartjes, Flavio Vasella, Michael Weller, Luca Regli and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. The anatomy of neuroepithelial tumours.Brain : a journal of neurology · 2023
    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

13 authors at 4 institutions in 3 countries.

Julius M KernbachNeurosurgical Artificial Intelligence Laboratory Aachen (NAILA), RWTH Aachen University Hospital, Pauwelsstrasse 30, 52074 Aachen, Germany.
Daniel DelevNeurosurgical Artificial Intelligence Laboratory Aachen (NAILA), RWTH Aachen University Hospital, Pauwelsstrasse 30, 52074 Aachen, Germany.
Georg NeulohDepartment of Neurosurgery, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany.
Hans ClusmannDepartment of Neurosurgery, Faculty of Medicine, RWTH Aachen University, Pauwelsstrasse 30, 52074 Aachen, Germany.
Danilo BzdokDepartment of Biomedical Engineering, McConnell Brain Imaging Centre, Montreal Neurological Institute, Faculty of Medicine, School of Computer Science, McGill University, 845 Sherbrooke St W, Montreal, Quebec H3A 0G4, Canada.
Simon B EickhoffInstitute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Wilhelm Johnen Strasse, 52428 Jülich, Germany.ORCID https://orcid.org/0000-0001-6363-2759
Victor E StaartjesDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.
Flavio VasellaDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0002-8953-0862
Michael WellerDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0002-1748-174X
Luca RegliDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0003-4639-4474
Carlo SerraDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0002-7305-550X
Niklaus KrayenbühlDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0002-4973-7527
Kevin AkeretDepartment of Neurosurgery, Clinical Neuroscience Center, University Hospital and University of Zurich, Frauenklinikstrasse 10, 8091 Zurich, Switzerland.ORCID https://orcid.org/0000-0002-5946-4999
University of Zurich · CHRWTH Aachen University · DEForschungszentrum Jülich · DEMontreal Neurological Institute and Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current World Health Organization classification integrates histological and molecular features of brain tumours. The aim of this study was to identify generalizable topological patterns with the potential to add an anatomical dimension to the classification of brain tumours. We applied non-negative matrix factorization as an unsupervised pattern discovery strategy to the fine-grained topographic tumour profiles of 936 patients with neuroepithelial tumours and brain metastases. From the anatomical features alone, this machine learning algorithm enabled the extraction of latent topological tumour patterns, termed

Indexed as

anatomyartificial intelligencegliomamachine learningmetastases

Identifiers

PMID36632188
PMCPMC9830987
OpenAlexW4312191874

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.