Deep learning-driven intelligent radiotherapy for osteosarcoma: recent advances and challenges
10.13491/j.issn.1004-714X.2025.06.021
- VernacularTitle:深度学习驱动骨肉瘤智能放疗的最新进展与挑战
- Author:
Handong ZHANG
1
;
Xiaohui LI
1
;
Luxu YIN
1
;
Huaqiang SUN
1
;
Peng WANG
1
Author Information
1. Department of Orthopedic Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Jinan 250014, China.
- Publication Type:ReviewArticles
- Keywords:
Deep learning;
Osteosarcoma;
Intelligent radiotherapy;
Image segmentation;
Dose optimization
- From:
Chinese Journal of Radiological Health
2025;34(6):912-917
- CountryChina
- Language:Chinese
-
Abstract:
With the widespread application of deep learning technology in radiotherapy, increasing attention has been directed toward enhancing the precision and personalization of intelligent radiotherapy for osteosarcoma. This review summarizes the recent advances in the application of deep learning to osteosarcoma image preprocessing, automatic target volume delineation, dose prediction and treatment plan optimization, early efficacy assessment, and follow-up monitoring. Bottlenecks such as data sharing, model generalization, and interpretability are analyzed. This review aims to provide a comprehensive reference for technological iteration and clinical implementation in this field, as well as a scientific basis for the determination of future research directions and the development of standardized guidelines.
