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MINI REVIEW article

Front. Oncol.
Sec. Neuro-Oncology and Neurosurgical Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1497195
This article is part of the Research Topic Application of Emerging Technologies in the Diagnosis and Treatment of Patients with Brain Tumors: New Frontiers in Imaging for Neuro-oncology View all 7 articles

Early characterization and prediction of glioblastoma and brain metastases treatment efficacy using medical imaging-based radiomics and artificial intelligence algorithms

Provisionally accepted
Aurélien Corroyer-Dulmont Aurélien Corroyer-Dulmont 1*Noémie N Moreau Noémie N Moreau 1SAmuel Valable SAmuel Valable 2Cyril Jaudet Cyril Jaudet 1Loïse Dessoude Loïse Dessoude 3Romain Herault Romain Herault 4Romain Modzelewski Romain Modzelewski 5Dinu Stefan Dinu Stefan 3Juliette Thariat Juliette Thariat 3Alexis Lechervy Alexis Lechervy 4
  • 1 Département de Physique Médicale, Centre François Baclesse, Caen, France
  • 2 Normandie Univ, UNICAEN, CEA, CNRS, ISTCT/CERVOxy group, GIP CYCERON, Caen, Lower Normandy, France
  • 3 Radiation Oncology Department, Centre François Baclesse, 14000 Caen, France, Caen, France
  • 4 UMR6072 Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC), Caen, Lower Normandy, France
  • 5 LITIS - EA4108-Quantif, University of Rouen, France, Rouen, France

The final, formatted version of the article will be published soon.

    In brain tumors, glioblastoma (GBM) is the most common and aggressive's one and brain metastases (BM) are occurring in 20-40% of cancer patients. Even with intensive treatment involving radiotherapy and surgery, which frequently leads to cognitive decline due to doses on healthy brain tissue, the median survival is 15 months for GBM and about six to nine for BM. Despite these treatments, GBM patients respond heterogeneously as do patient with BM.Following standard of care, some patients will respond and have an overall survival of more than 30 months and others will not respond and will die within a few months. Differentiating non-responders from responders as early as possible in order to tailor treatment in a personalized medicine fashion to optimize tumor control and preserve healthy brain tissue is the most pressing unmet therapeutic challenge. Innovative computer solutions recently emerged and could help for this challenge. This review will focus on fifty-two published research between 2013 to 2024 on (1) the early characterization of treatment efficacy with biomarkers imaging and radiomic-based solutions, (2) predictive solutions with radiomic and artificial intelligence-based solutions, (3) interest of other biomarkers and (4) the importance of the prediction of new treatment modalities efficacy.

    Keywords: GBM: Glioblastoma, ML: machine learning, brain tumors, artificial intelligence, treatment efficacy, medical imaging, Radiotherapy

    Received: 16 Sep 2024; Accepted: 07 Jan 2025.

    Copyright: © 2025 Corroyer-Dulmont, Moreau, Valable, Jaudet, Dessoude, Herault, Modzelewski, Stefan, Thariat and Lechervy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Aurélien Corroyer-Dulmont, Département de Physique Médicale, Centre François Baclesse, Caen, France

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.