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Accès ouvert déclaré 2026 preprint

Biologically Informed Radiotherapy in Glioblastoma: A Structured Framework for Imaging-Guided Clinical Decision-Making

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Résumé fourni par la source

Radiotherapy for glioblastoma remains anchored to postoperative structural MRI and anatomy-based target definitions, despite marked spatial heterogeneity and dynamic biological change during chemoradiotherapy. Advanced MRI, amino-acid PET, radiomics, and habitat imaging can characterize tumor biology beyond conventional anatomy, yet their relevance to radiotherapy planning and their evidentiary maturity differ substantially. This narrative review examines the current evidence for biologically informed radiotherapy in glioblastoma and proposes an MRI-centered actionability framework that organizes imaging-derived findings into five levels of evidentiary maturity, from descriptive or associative signals to intervention-ready biomarkers, to guide literature interpretation, multidisciplinary discussion, and prospective protocol design. Standard MRI-based planning remains the clinical backbone, supported by contemporary guidelines and the absence of randomized evidence demonstrating benefit from routine biologically guided target modification. Advanced MRI is discussed as the most practical serial platform for treatment-course reassessment, amino-acid PET as a selective complementary tool for metabolic clarification and recurrence assessment, and radiomics and habitat imaging as promising but not yet intervention-ready research layers. Across modalities, prospective evidence supports feasibility more consistently than clinical benefit. The proposed framework is intended to separate biologically informative findings from those sufficiently validated to justify a defined radiotherapy consequence, and to structure the translational path toward intervention-grade evidence in glioblastoma radiotherapy.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Biologically Informed Radiotherapy in Glioblastoma: A Structured Framework for Imaging-Guided Clinical Decision-Making
Date Crossref
04/06/2026
Éditeur
MDPI AG
Type
posted-content

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Sujets associés

Glioma Diagnosis and TreatmentRadiomics and Machine Learning in Medical ImagingCancer Research and Treatments

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