Radiotherapy for primary bone tumors: current techniques and integration of artificial intelligence-a review

Area of Science:

• Radiation Oncology
• Medical Physics
• Oncology

Background:

• Primary bone tumours present significant challenges in radiation oncology due to the need for high-dose radiation with minimal damage to surrounding healthy tissues.
• Historically, achieving curative intent while preserving normal tissues has been a major hurdle in treating these rare cancers.

Purpose of the Study:

• To review recent technical and translational advancements in radiotherapy for primary bone tumours.
• To outline practical considerations, identify evidence gaps, and propose research priorities for individualized, data-intelligent radiotherapy.

Main Methods:

• Review of recent innovations in radiation delivery technologies, including proton and carbon-ion therapy, MR-guided linear accelerators, and ultra-high-dose-rate (FLASH) radiotherapy.
• Exploration of advancements in artificial intelligence for treatment planning and contouring, and the role of federated learning in pooling data for rare tumour research.

Main Results:

• Proton and carbon-ion therapy show promise for durable local control and acceptable toxicity in unresectable sarcomas.
• MR-guided systems allow for adaptive radiotherapy, enabling margin reduction and potentially improved precision.
• Emerging FLASH strategies and AI-driven approaches are poised to further enhance treatment efficacy and reduce normal tissue toxicity.

Conclusions:

• Convergent innovations in hardware, software, and data science are transforming radiotherapy for primary bone tumours.
• These advancements are crucial for optimizing dose escalation, designing adaptive protocols, and developing future biology-driven clinical trials.
• The path forward involves integrating these technologies for truly individualized and data-intelligent treatment strategies.