A review of artificial intelligence in brachytherapy

Area of Science:

• Medical Physics
• Oncology
• Radiotherapy

Background:

• Brachytherapy is a crucial radiotherapy technique.
• Clinical workflow optimization is essential for effective cancer treatment.
• Artificial intelligence (AI) offers novel solutions for complex medical procedures.

Purpose of the Study:

• To comprehensively review the applications of AI, machine learning, and deep learning in brachytherapy.
• To systematically categorize AI's role across the brachytherapy workflow.
• To analyze the impact of AI on treatment personalization, efficiency, and effectiveness.

Main Methods:

• Systematic literature review of AI applications in brachytherapy.
• Categorization of AI applications into seven key areas: imaging, preplanning, treatment planning, applicator reconstruction, quality assurance, outcome prediction, and real-time monitoring.
• Detailed summary of AI models, data utilized, and reported outcomes for each application.

Main Results:

• AI is being applied across all stages of brachytherapy, from imaging to outcome prediction.
• Specific AI models demonstrate potential for improved accuracy and efficiency in tasks like treatment planning and applicator reconstruction.
• Current AI applications show promise in enhancing personalized treatment delivery and predicting patient outcomes.

Conclusions:

• AI holds significant potential to revolutionize brachytherapy's clinical workflow.
• Further research and development are needed to address limitations, challenges, and ethical considerations.
• Expanding AI's clinical utility in brachytherapy can lead to more personalized, efficient, and effective cancer treatments.