NRG oncology assessment of artificial intelligence for automatic treatment planning in radiation therapy clinical trials: Present and future Journal Article


Authors: Jia, X.; Rong, Y.; Wu, Q.; Cardenas, C. E.; Court, L. E.; Hrinivich, W. T.; Kang, H.; Kovalchuk, N.; Whitaker, T. J.; Xiao, Y.; Zhang, P.; Chen, Q.
Article Title: NRG oncology assessment of artificial intelligence for automatic treatment planning in radiation therapy clinical trials: Present and future
Abstract: Purpose: Recent advances in artificial intelligence (AI) have showcased the potential of automatic treatment planning for clinical trials involving radiation therapy. This paper offers an overview of the current landscape of AI-based treatment planning, emphasizing its ability to improve plan quality and streamline the planning process. Methods and Materials: Acknowledging the increasing clinical utilization and promise of these technologies, the NRG Oncology Medical Physcis Subcommittee established a working group to assess the status of AI-based automatic treatment planning for clinical trials, along with its challenges and future directions. Results: We describe its critical roles within radiation therapy clinical trials and discuss the challenges of integrating AI into such settings. We further outline short-term actions for enhancing AI-based automatic treatment planning for radiation therapy clinical trials and explore future directions for the field, such as the development of personalized algorithms, the integration of AI into routine clinical practice, and the need for support in this direction. Conclusions: This assessment provides insights into the present state and prospects of AI in radiation therapy clinical trials to facilitate enhanced treatment planning and patient care. © 2025 Elsevier Inc.
Keywords: clinical trial; treatment planning; radiotherapy; oncology; patient care; surgery; drug therapy; diseases; cryotherapy; clinical practices; electrotherapeutics; working groups; methods and materials; plan quality; 'current; automatic treatment; planning process
Journal Title: International Journal of Radiation Oncology, Biology, Physics
Volume: 123
Issue: 1
ISSN: 0360-3016
Publisher: Elsevier Inc.  
Publication status: Published
Date Published: 2025-09-01
Online Publication Date: 2025-03-29
Start Page: 282
End Page: 295
Language: English
DOI: 10.1016/j.ijrobp.2025.03.045
PUBMED: 40164355
PROVIDER: scopus
PMCID: PMC12228557
DOI/URL:
Notes: Article -- Source: Scopus
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  1. Pengpeng Zhang
    181 Zhang