  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.
