Artificial intelligence-powered innovations in radiotherapy: boosting efficiency and efficacy

Cancer remains a substantial global health challenge, with steadily increasing incidence rates. Radiotherapy (RT) is a crucial component in cancer treatment. Nevertheless, due to limited resources, there is an urgent need to enhance both its efficiency and therapeutic efficacy. The integration of Ar...

Full description

Saved in:
Bibliographic Details
Main Authors: Chen Junyi, Zhu Xinlin, Jin Jian-Yue, Kong Feng-Ming (Spring), Yang Gen
Format: Article
Language:English
Published: De Gruyter 2025-02-01
Series:Medical Review
Subjects:
Online Access:https://doi.org/10.1515/mr-2025-0007
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Cancer remains a substantial global health challenge, with steadily increasing incidence rates. Radiotherapy (RT) is a crucial component in cancer treatment. Nevertheless, due to limited resources, there is an urgent need to enhance both its efficiency and therapeutic efficacy. The integration of Artificial Intelligence (AI) into RT has proven to significantly improve treatment efficiency, especially in time-consuming tasks. This perspective demonstrates how AI enhances the efficiency of target delineation and treatment planning, and introduces the concept of All-in-One RT, which may greatly improve RT efficiency. Furthermore, the concept of Radiotherapy Digital Twins (RDTs) is introduced. By integrating patient-specific data with AI, RDTs enable personalized and precise treatment, as well as the evaluation of therapeutic efficacy. This perspective highlights the transformative impact of AI and digital twin technologies in revolutionizing cancer RT, with the aim of making RT more accessible and effective on a global scale.
ISSN:2749-9642