Bentourkia M, Abdo RA. Updates on glioblastoma multiforme: From epidemiology to imaging and artificial intelligence. Artif Intell Med Imaging 2025; 6(2): 108032 [DOI: 10.35711/aimi.v6.i2.108032]
Corresponding Author of This Article
M'hamed Bentourkia, PhD, Professor, Department of Medical Imaging and Radiation Sciences, University of Sherbrooke, 3001, 12th Avenue North, Sherbrooke J1H5N4, Quebec, Canada. mhamed.bentourkia@usherbrooke.ca
Research Domain of This Article
Oncology
Article-Type of This Article
Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Artif Intell Med Imaging. Sep 8, 2025; 6(2): 108032 Published online Sep 8, 2025. doi: 10.35711/aimi.v6.i2.108032
Updates on glioblastoma multiforme: From epidemiology to imaging and artificial intelligence
M'hamed Bentourkia, Redha-Alla Abdo
M'hamed Bentourkia, Redha-Alla Abdo, Department of Medical Imaging and Radiation Sciences, University of Sherbrooke, Sherbrooke J1H5N4, Quebec, Canada
Author contributions: Bentourkia M designed the study; Abdo RA wrote the first draft, and both authors revised the review manuscript.
Conflict-of-interest statement: All authors state that they have no conflicts of interest to report.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: M'hamed Bentourkia, PhD, Professor, Department of Medical Imaging and Radiation Sciences, University of Sherbrooke, 3001, 12th Avenue North, Sherbrooke J1H5N4, Quebec, Canada. mhamed.bentourkia@usherbrooke.ca
Received: April 3, 2025 Revised: May 12, 2025 Accepted: August 12, 2025 Published online: September 8, 2025 Processing time: 153 Days and 5.7 Hours
Abstract
Glioblastoma multiforme (GBM) are the most aggressive and common tumors in the central nervous system. GBM are classified as grade IV according to the World Health Organization. The incidence of GBM slightly differs among countries. The etiology of GBM has not been entirely clarified. No risk factors such as smoking, chemicals or dietary can be identified for GBM. Only the exposure to high radiation dose such as radiotherapy of head and neck cancers have been reported to increase the risk of glioma tumors. In this review, the authors attempted to cover several aspects of GBM. This review was based on a collection of recent publications from different research fields but all related to GBM in order to shed the light on this disease. We highlighted the current insights of GBM in the aspects of epidemiology, pathogenesis, etiology, molecular genetics, imaging technologies, artificial intelligence and treatment. A literature review was conducted for GBM with relevant keywords. Although GBM was known since several decades, its causes are still confounding, and its early detection is often unpredictable. Since the hereditary aspect of GBM is very low, there remains as the common symptoms the interference with normal brain function, memory loss, unusual behavior, headaches and seizures. The progress in GBM treatment is not satisfactory even with the deployment of huge efforts and financial costs in many domains like gene therapy, surgery and chemoradiotherapy. Despite the rapid developments of the standard treatment for GBM, the trend of survival rate did not change among years.
Core Tip: Glioblastoma remains one of the most lethal brain cancers due to its complexity and resistance to therapy. Artificial intelligence (AI) offers transformative potential in early detection, precision surgery, personalized treatment, and drug discovery. By integrating imaging, genomics, and clinical data, AI paves the way to improved capabilities for faster and more effective glioblastoma care.
