The UCSD Knowledge-Based Radiotherapy Initiative is dedicated to the dissemination of the best practices in optimized radiotherapy planning. Though the mathematical methods can be complex, the logic behind knowledge-based planning is extremely simple: use past clinical experience to quantitatively inform and improve the practice of radiotherapy for future patients. 

While this website largely serves at the landing page for Dr. Kevin Moore's research group, we also hope to serve a direct clinical need by educating clinicians in how to understand and safely adopt knowledge-based methods in their radiotherapy practice. As one of the primary advantages of knowledge-based planning is the dissemination of best practices, we will also use this page to share the UC San Diego RapidPlan models with the global radiotherapy community. 



In addition to its growing impact on clinical radiation oncology, knowledge-based radiotherapy is a very active area of research and development.  Catch up on the latest publications and presentations from Dr. Moore's research group.

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This initiative represents a multi-disciplinary collaboration involving post-doctoral research fellows, dosimetrists, physicists, and physicians.  Find out more about the people involved in this effort or, if you are interested in joining the team, we do have an open position for a post-doctoral fellow

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If you are a visual learner, we have recorded tutorials on knowledge-based planning to get you started.  Feel free to check out our archive of lab photos and artistic images, because we don't limit ourselves to simply creating beautiful treatment plans. 

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One of the great things about knowledge-based planning is the ability to share experience and technical knowhow. With the clinically-tested UCSD RapidPlan models, anyone with the Varian RapidPlan system can import and apply the UCSD RapidPlan automated planning routines on his or her own patients.

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Catch up on the latest news from the UCSD Knowledge-Based Radiotherapy Initiative.

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All photography by Kevin Moore