Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow

Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topic in radiotherapy. Today, the first commercial automated treatment planning solutions are available and implemented in a growing number of clinical radiotherapy departments. It should be noted that these various commercial solutions are based on very different methods, implying a daily practice that varies from one center to another. It is likely that this change in planning practices is still in its infancy. Indeed, the rise of artificial intelligence methods, based inparticular on deep learning, has recently revived research interest in this subject. The numerous articles currently being published announce a lasting and profound transformation of radiotherapy planning practices in the years to come. From this perspective, an evolution of initial training for clinical teams and the drafting of new quality assurance recommendations is desirable. (c) 2021 Societe francaise de radiotherapie oncologique (SFRO). Published by Elsevier Masson SAS. Allrights reserved.

Automated summary

Modern radiotherapy treatment planning has become a key research topic with the automation of planning processes, leading to the implementation of commercial solutions in clinical departments. However, the diverse commercial solutions based on different methods suggest varying practices across different centers. With the emergence of artificial intelligence, particularly deep learning, the future of radiotherapy planning practices is expected to undergo lasting and profound transformation.