Evidence map›Paper›PMID 42483740›Full record

ArticleNeuro-oncology advances

Detection of early alterations in radiologically normal-appearing brain regions before recurrence of high-grade glioma using multiparameter mapping and diffusion tensor imaging.

Philipp Raffler, Severin Schramm, Cornelius Berberich, Daniele Calabro, Ronja Berg, Kirsten Jung, Julian Ziegenfeuter, Tim Herrmann, Claire Delbridge, Stephanie C Combs and 4 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. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers 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.

Philipp RafflerDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0009-0006-7269-4998
Severin SchrammDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Cornelius BerberichDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Daniele CalabroDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Ronja BergDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Kirsten JungDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Julian Ziegenfeuter
Tim HerrmannDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Claire DelbridgeDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Stephanie C CombsDepartment of Radiation Oncology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Bernhard MeyerDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Christine PreibischDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Benedikt WiestlerDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-2963-7772
Marie-Christin MetzDepartment of Neuroradiology, TUM School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-1459-5741

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Quantitative MRI (qMRI) might detect subtle changes in recurrent high-grade glioma earlier than conventional imaging. The purpose of this study was to investigate whether WHO grade 4 glioma patients demonstrate alterations in multiparameter mapping (MPM) and diffusion tensor imaging (DTI)-derived measures within radiologically normal-appearing brain regions that subsequently exhibit tumor recurrence in follow-up scans. Methods: For 16 WHO grade 4 glioma patients with confirmed recurrence at follow-up, qMRI parametric maps [proton density (PD), longitudinal relaxation rate (R1), transverse relaxation rate (R2*)] were generated using an MPM protocol. Additionally, diffusion tensor imaging (DTI)-derived free water (FW) and FW-corrected tissue fractional anisotropy (FAt) were evaluated. We mapped recurrent tumor areas onto baseline scans to identify regions that subsequently progressed to contrast-enhancing tumor (CET) or FLAIR-hyperintense areas. Results: Normal-appearing gray matter (NAGM) that progressed into FLAIR-hyperintense areas in follow-up scans showed significantly lower median PD values, while median FW was significantly elevated across all subregions compared to their reference regions. This potentially reflects an early redistribution of water from bound tissue compartments into the extracellular space, most evident in gray matter. R1 demonstrated significantly lower median values in NAGM progressing to tumor compared to stable NAGM. Variance was significantly increased for PD, R2*, and FW in multiple subregions, consistent with heterogeneous tumor infiltration. Conclusions: MPM and DTI-derived metrics reveal subtle alterations in radiologically normal-appearing brain tissue months before recurrence becomes visible on conventional imaging. This could support earlier identification of subclinical progression and allow for personalized surveillance strategies.

Indexed as

DTI-derived free waterhigh-grade gliomamultiparameter mappingquantitative MRIrecurrence

Identifiers

PMID42483740
PMCPMC13385338

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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.