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Artificial intelligence applications in adaptive radiotherapy-a narrative review.
Zejia F Chen1, Benjamin Larocque1, Jade Wang1
1School of Medicine, Queen's University, Kingston, ON, Canada.
Translational Cancer Research
|April 13, 2026
Summary
Artificial intelligence (AI) enhances online adaptive radiotherapy (ART) by automating tasks like image registration and auto-contouring. This review explores AI
Area of Science:
- Radiation Oncology
- Medical Imaging
- Artificial Intelligence
Background:
- Online adaptive radiotherapy (ART) adapts treatment plans to interfraction changes.
- Artificial intelligence (AI) offers potential to streamline resource-intensive ART workflows.
- Integrating AI into radiation oncology can improve treatment precision and efficiency.
Purpose of the Study:
- To review current applications of AI in online ART.
- To identify promising future directions for AI in online ART.
- To summarize AI's role in decision support, imaging, and contouring for ART.
Main Methods:
- Comprehensive literature search across multiple databases (2015-2025).
- Included peer-reviewed studies evaluating AI tools for online ART functions.
- Keywords included "artificial intelligence", "adaptive radiotherapy", and "synthetic image generation".
Main Results:
- AI applications span image registration, auto-contouring, and decision support.
- Deep learning enables synthetic CT generation for MRI-guided ART.
- AI-driven auto-segmentation reduces contouring time and approaches expert performance.
- AI aids in dose prediction and plan optimization, reducing organ at risk (OAR) dose.
Conclusions:
- AI has transformative potential for automating ART tasks and improving plan quality.
- Future work requires multi-institutional validation and standardized guidelines.
- Development of transparent, uncertainty-aware AI models is crucial for clinical adoption.
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