Evidence map›Paper›PMID 41894002›Full record

ArticleClinical neuroradiology2026

From Anatomy to Outcome: Linking Glioma Location Patterns to Survival Using Non-Negative Matrix Factorization.

Marianne Schell, Joel Kohler, Martha Folty-Dumitru, Haidar Alzaid, Irada Pflüger, Katharina Schregel, Tim Hilgenfeld, Julius Kernbach, Sandro Krieg, Felix Sahm and 3 more

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Article in Clinical neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Marianne SchellNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Joel KohlerNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Martha Folty-DumitruNeuroradiology, University Hospital Bonn, Bonn, Germany.
Haidar AlzaidNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Irada PflügerNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Katharina SchregelNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Tim HilgenfeldNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Julius KernbachNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Sandro KriegNeurosurgery, University Hospital Heidelberg, Heidelberg, Germany.
Felix SahmNeuropathology, University Hospital Heidelberg, Heidelberg, Germany.
Wolfgang WickNeurology, University Hospital Heidelberg, Heidelberg, Germany.
Martin BendszusNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany.
Jessica JesserNeuroradiology, University Hospital Heidelberg, Heidelberg, Germany. Jessica.Jesser@med.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe anatomical distribution of IDH-wildtype gliomas may encode prognostic information not captured by conventional clinical or molecular markers. The purpose of this study was to determine whether continuous, data-driven spatial patterns of tumor involvement provide prognostic value beyond established clinical and molecular factors.

methodsWe applied non-negative matrix factorization (NMF) to preoperative tumor segmentations from 429 patients with IDH-wildtype gliomas to identify coherent spatial components of tumor involvement. Six reproducible spatial signatures were extracted and integrated into multivariate Cox proportional hazards models. Models additionally included tumor volume, age, sex, O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation status, Eastern Cooperative Oncology Group (ECOG) performance status, and extent of resection.

resultsAll six spatial patterns demonstrated significant association with overall survival (p ≤ 0.005). Notably, involvement of the left parietal-occipital regions was linked to the poorest outcomes, while temporal patterns showed weaker associations with survival. Incorporating spatial patterns into the prognostic model improved its discriminatory power and altered the influence of tumor volume, indicating an interaction between tumor location and tumor burden.

conclusionContinuous spatial phenotyping of IDH-wildtype gliomas using NMF captures prognostically relevant information not reflected by conventional markers. Integration of spatial patterns into prognostic models enhances risk stratification and supports the incorporation of detailed spatial analyses into radiologic workflows.

Indexed as

Brain NeoplasmsGliomaMagnetic Resonance ImagingAdultBiomarkers, TumorFemaleHumansImage Interpretation, Computer-AssistedIsocitrate DehydrogenaseMaleMiddle AgedPrognosisSurvival AnalysisTumor BurdenBiomarkers, TumorIsocitrate DehydrogenaseBrainCox regressionGliomaImaging biomarkersSurvival predictionTumor location

Identifiers

PMID41894002
PMCPMC13521997

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