2022/11/16 by Hao Peng, Chao Wu, Peng, Hao +11
Engineering · Medicine · Physics and Astronomy · #Advanced Radiotherapy Techniques #Advanced X-ray and CT Imaging #FOS: Physical sciences #Medical Physics (physics.med-ph) #Radiation Therapy and Dosimetry
paper · pdf · doi:10.48550/arxiv.2211.09038
openalex publication_date 2022/11/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We are in a golden age of progress in artificial intelligence (AI). Radiotherapy, due to its technology-intensive nature as well as direct human-machine interactions, is perfectly suited for benefitting from AI to enhance accuracy and efficiency. Over the past few years, a vast majority of AI research have already been published in the field of photon therapy, while the applications of AI specifically targeted for particle therapy remain scarcely investigated. There are two distinct differences between photon therapy and particle therapy: beam interaction physics (photons vs. charged particles) and beam delivery mode (e.g. IMRT/VMAT vs. pencil beam scanning). As a result, different strategies of AI deployment are required between these two radiotherapy modalities. In this article, we aim to present a comprehensive survey of recent literatures exclusively focusing on AI-powered particle therapy. Six major aspects are included: treatment planning, dose calculation, range and dose verification, image guidance, quality assurance and adaptive replanning. A number of perspectives as well as potential challenges and common pitfalls, are also discussed.