Chapter

Optimization in Medicine

Volume 12 of the series Springer Optimization and Its Applications pp 47-70

Neuro-dynamic programming for fractionated radiotherapy planning

  • Geng DengAffiliated withDepartment of Mathematics, University of Wisconsin at Madison
  • , Michael C. FerrisAffiliated withComputer Sciences Department, University of Wisconsin at Madison

Summary

We investigate an on-line planning strategy for the fractionated radiotherapy planning problem, which incorporates the effects of day-to-day patient motion. On-line planning demonstrates significant improvement over off-line strategies in terms of reducing registration error, but it requires extra work in the replanning procedures, such as in the CT scans and the re-computation of a deliverable dose profile. We formulate the problem in a dynamic programming framework and solve it based on the approximate policy iteration techniques of neuro-dynamic programming. In initial limited testing, the solutions we obtain outperform existing solutions and offer an improved dose profile for each fraction of the treatment.

Keywords

Fractionation adaptive radiation therapy neuro-dynamic programming reinforcement learning