James C L Chow, Huan Giap
While AI offers significant potential to improve particle therapy treatment planning, further research is needed to enhance model robustness, clinical validation, and integration into existing workflows.
PURPOSE: This review examines the role of artificial intelligence (AI) in particle therapy treatment planning, highlighting recent advancements, clinical potential, and existing challenges.
METHODS AND MATERIALS: A review was conducted on AI applications in proton and heavy ion therapy, focusing on automated plan generation, dose prediction, treatment adaptation, and quality assurance.
RESULTS: AI-driven methods have shown promise in optimizing treatment planning, enhancing dose prediction, and improving plan adaptation. However, challenges such as data limitations, model interpretability, and regulatory barriers hinder clinical implementation.
CONCLUSION: While AI offers significant potential to improve particle therapy treatment planning, further research is needed to enhance model robustness, clinical validation, and integration into existing workflows.