Evidence map›Paper›PMID 41918714›Full record

ArticleNeuro-oncology advances

Marginal diffusion slope as a prognostic imaging biomarker of infiltrating phenotype in glioblastoma; A cancer imaging biomarker roadmap study.

Antoine Vallatos, Haitham F I Al-Mubarak, Joanna L Birch, Yusuf Icer, Catherine McBain, David J Coope, Konstantina Karabatsou, Samantha J Mills, Geoff J M Parker, William M Holmes and 4 more

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Article in Neuro-oncology advances. 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Antoine VallatosEdinburgh Neuro-Oncology Translational Imaging Research (ENTIRe), Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK.ORCID https://orcid.org/0000-0002-5202-056X
Haitham F I Al-MubarakGlasgow Experimental MRI Centre, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK.
Joanna L BirchCancer Research UK Scotland Institute, Scotland, UK.ORCID https://orcid.org/0000-0001-9522-8435
Yusuf IcerEdinburgh Neuro-Oncology Translational Imaging Research (ENTIRe), Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK.ORCID https://orcid.org/0000-0001-6488-4472
Catherine McBainUniversity of Manchester, Manchester, UK.
David J CoopeUniversity of Manchester, Manchester, UK.
Konstantina KarabatsouUniversity of Manchester, Manchester, UK.
Samantha J MillsWalton Centre for Neurology and Neurosurgery, Liverpool, UK.
Geoff J M ParkerCentre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
William M HolmesGlasgow Experimental MRI Centre, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK.
Anthony J ChalmersCancer Research UK Scotland Institute, Scotland, UK.ORCID https://orcid.org/0000-0002-1746-7278
Alan JacksonUniversity of Manchester, Manchester, UK.
Adam WaldmanEdinburgh Neuro-Oncology Translational Imaging Research (ENTIRe), Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK.ORCID https://orcid.org/0000-0003-4398-6431
Gerard ThompsonEdinburgh Neuro-Oncology Translational Imaging Research (ENTIRe), Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK.ORCID https://orcid.org/0000-0003-1722-2235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Conventional MRI protocols fail to probe marginal tumour infiltration in glioblastoma, hindering surgery and radiotherapy planning. This study aimed to demonstrate development and biological validation of a putative imaging biomarker (IB) for characterising glioblastoma infiltration, following principles outlined in the cancer imaging biomarker roadmap. Methods: This IB is based upon spatial change in apparent diffusion coefficient (ADC) measures across a macroscopic tumour boundary. We systematically assessed whether ADC slope at the tumour margin (marginal diffusion slope-MDS) could (a) describe an underlying infiltrative phenotype based on reported links between ADC and tumour cellularity validated using a preclinical model, and (b) predict clinical outcome in a single-centre exemplar prospective human cohort study. Results: Preclinical results showed a strong, spatially-resolved, negative correlation between marginal ADC and underlying tumour cell density in coregistered MRI-histology datasets from a glioblastoma model. Clinical results ( Conclusions: In alignment with the Imaging Biomarker Roadmap consensus, we biologically validated MDS as a biomarker of infiltrative phenotype in a preclinical model and demonstrated its predictive value for OS in humans as a prelude to larger clinical validation studies.

Indexed as

diffusion MRIglioblastomaimaging biomarker­infiltrationprognosis

Identifiers

PMID41918714
PMCPMC13034536

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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.