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Adaptive radiation therapy (ART) is a form of radiation therapy that uses real-time imaging to adjust the radiation dose and target volume during treatment, improving the accuracy of radiation delivery and minimizing damage to healthy tissue. Artificial Intelligence (AI) has been increasingly used in ART to automate and optimize the treatment planning and delivery process. The application of AI in ART is a hot topic in radiation therapy, given the urgent demand from practitioners for systematically organized references.
This new title aims to provide a comprehensive overview of the use of AI in radiation therapy (RT), with the focus on adaptive radiation therapy (ART). It will cover a range of topics related to AI and ART, including image segmentation, adaptive treatment planning, real-time image guidance, personalized medicine, clinical applications, and regulatory and ethical considerations.
Section I: AI in precision medicine
1 Fundamentals of artificial intelligence (Wei Zhao, Beihang University, Beijing, China)
2 Introduction of AI for radiation therapy (Raymond Mak, Harvard Medical School, Boston, MA, USA)
3 AI for response prediction (Clemens Grassberger, University of Washington, Seattle, WA, USA)
4 Imaging technologies in radiation therapy (RT) (Iori Sumida, Osaka University, Osaka, Japan)
5 AI in Clinical Trial (Ying Xiao, University of Pennsylvania, Philadelphia, PA, USA)
6 Big data and information technologies for AI in RT (Dan Ruan, UCLA, Los Angles, CA, USA) Section II: AI in ART workflow
7 Introduction to adaptive radiation therapy (ART) (X. Allen Li, Medical College of Wisconsin, Milwaukee, WI, USA)
8 Overview of AI-driven ART workflow (Geoffrey Hugo, Washington University in St. Louis, St. Louis, MO, USA)
9 Imaging for ART (Quanzheng Li, Harvard Medical School, Boston, MA, USA)
10 Imaging registration and segmentation for ART (Jinzhong Yang, University of Texas, MD Anderson Cancer Center, Houston, TX, USA)
11 AI-assisted dose prediction and adaptive replanning (Jackie Wu, Duke University, Durham, NC, USA)
12 AI for ART treatment delivery (Paul Keall, University of Sydney, Sydney, Australia)
13 AI for quality assurance in ART (Maria Chan, Memorial Solan Kattering Cancer Center, New York, NY, USA)
14 AI for response prediction and adaption (Issam El Naqa, Moffit Cancer Center, Tampa, FL, USA)
15 Challenges in AI-ART (Steve Jiang, University of Texas Southwestern Medical Center, Dallas, TX, USA) Section III: Clinical implementation of AI-ART
16 Online CT/CBCT-based AI ART (Brian Kristensen, Herlev University Hospital, Copenhagen, Denmark)
17 Online MRI-based ART (Dylan P. O'Connell, UCLA, Los Angles, LA, USA)
18 Functional imaging (CT/PET) guided ART (Bin Cai, University of Texas Southwestern Medical Center, Dallas, Texas)
19 Safety and training considerations in clinical implementation of AI ART (Leigh Conroy, Princess Margaret Cancer Centre, Toronto, ON, Canada)
20 Regulatory and ethical considerations in AI ART (Weijin Chen, US Food and Drug Administration, Silver Spring, MD, USA)
21 Future outlook of AI-driven ART (Lei Xing, Stanford University, Palo Alto, CA, USA)