Recent Advancements of Artificial Intelligence in Particle Therapy
Hao Peng, Chao Wu, Dan Nguyen, Jan Schuemann, Andrea Mairani, Yuehu Pu, Steve Jiang
Abstract
We are in a golden age of progress in the field of artificial intelligence (AI). Radiotherapy is perfectly suited to benefit from AI to enhance accuracy and efficiency due to its technology-intensive nature and direct human–machine interactions. While large amount of AI research have recently been published in the field of photon therapy, applications of AI specifically targeted for particle therapy remain scarcely investigated. There are two distinct differences between the photon therapy and particle therapy: 1) beam interaction physics (photons versus charged particles) and 2) beam delivery mode (e.g., IMRT/VMAT versus pencil beam scanning). Consequently, different strategies of AI deployment are required for these two radiotherapy modalities. In this article, we aim to present a comprehensive survey of recent literature exclusively focusing on AI-powered particle therapy. Six major aspects are included: 1) treatment planning; 2) dose calculation; 3) range and dose verification; 4) image guidance; 5) quality assurance; and 6) adaptive replanning. A number of perspectives, as well as potential challenges and common pitfalls, are also discussed.