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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
Published on: October 6, 2023
NRG Oncology Assessment of Artificial Intelligence for Automatic Treatment Planning in Radiation Therapy Clinical
Xun Jia1, Yi Rong2, Qingrong Wu3
1Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.
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.
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