Optimizing the delivery of radiotherapy with artificial intelligence

Optimizing the delivery of radiotherapy with artificial intelligence. Abstract Artificial intelligence (AI) and machine learning are transformative technologies that have sparked both excitement and concern. In radiation oncology, AI has been successfully applied to automate tasks, such as auto-contouring, geometric adaptation, calculation of radiation dose and quality assurance, and predicting outcomes to provide optimal patient care.

The clinical deployment of AI-driven and machine learning-based tools, however, continues to lag behind their perceived potentials, owing to a range of technical, practical, ethical and legal concerns. The original predictive AI algorithms have been expanded with technologies such as generative AI and foundation models to enable new applications, such as automated treatment planning and synthetic computed tomography generation, as well as improved prediction of individual patient outcomes. The increasing availability of innovations such as agentic AI, digital twins and multimodal AI could further improve the delivery and, thus, the efficacy of radiotherapy.

In this Review, we present examples of successful AI applications in radiation oncology, provide an overview of the current challenges for implementing such tools in this specialty and strategies for addressing them, and discuss the broader implications of these tools in optimizing treatment outcomes and the quality of patient care. Key Points Artificial intelligence (AI) is currently transforming radiation oncology workflows and patient care through a growing number of commercially available and Food and Drug Administration-approved tools. AI is transforming the defined roles of radiation oncology care providers by automating routine tasks and supporting predictive and clinical decision-making, while expert human oversight remains essential across AI-enabled workflows.

OpenAI is working with an independent Advisory Group on Mathematics and Artificial Intelligence to guide the review and communication of emerging AI results. Advisory Group on Mathematics and Artificial Intelligence.

Medical Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always consult with qualified healthcare professionals for medical decisions and treatment options.