MINI REVIEW article
Front. Oncol.
Sec. Pharmacology of Anti-Cancer Drugs
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1673752
This article is part of the Research TopicData and Precision: AI Leading the Revolution in Immunoradiotherapy for Advanced Malignant TumorsView all articles
Radiotherapy for Glioma in the AI Era: Current Applications and Future Prospects
Provisionally accepted
- 1Department of Pediatric Surgery, Zigong First People’s Hospital, Zigong, China
- 2Zigong First People's Hospital, Zigong, China
- 3Joint Shantou International Eye Center of Shantou University and The Chinese University of Hong Kong, Shantou, China
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Gliomas are primary central nervous system tumors characterized by a high recurrence rate and poor prognosis, especially in high-grade forms such as glioblastoma (GBM). Radiotherapy remains a cornerstone in glioma management, particularly following surgical resection. Recent advancements in technology—including intensity-modulated radiotherapy (IMRT), proton therapy, carbon-ion radiotherapy, intraoperative radiotherapy, and ultra-high dose rate FLASH radiotherapy—have improved treatment precision and tumor control. However, clinical challenges persist due to tumor heterogeneity, imaging limitations, and planning variability. In the era of artificial intelligence (AI), novel tools such as radiomics, deep learning, and predictive modeling are increasingly being integrated into glioma radiotherapy workflows. These AI-driven approaches have shown potential to enhance imaging interpretation, automate contouring, optimize treatment planning, and predict clinical outcomes. This review highlights the evolution of glioma radiotherapy, explores the emerging role of AI across various stages of radiotherapy, and discusses future directions for implementing personalized, adaptive, and data-driven strategies in clinical practice.
Keywords: artificial intelligence, Glioma, Radiotherapy, prospects, clinical practice
Received: 26 Jul 2025; Accepted: 29 Aug 2025.
Copyright: © 2025 Li, Wang, Qi, Zeng and Gu. 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: Tianliang Li, Department of Pediatric Surgery, Zigong First People’s Hospital, Zigong, China
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