A dynamic programming approach to adaptive fractionation

Physics in Medicine and Biology
Jagdish RamakrishnanJohn N Tsitsiklis

Abstract

We conduct a theoretical study of various solution methods for the adaptive fractionation problem. The two messages of this paper are as follows: (i) dynamic programming (DP) is a useful framework for adaptive radiation therapy, particularly adaptive fractionation, because it allows us to assess how close to optimal different methods are, and (ii) heuristic methods proposed in this paper are near-optimal, and therefore, can be used to evaluate the best possible benefit of using an adaptive fraction size. The essence of adaptive fractionation is to increase the fraction size when the tumor and organ-at-risk (OAR) are far apart (a 'favorable' anatomy) and to decrease the fraction size when they are close together. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to the OAR when compared to that resulting from standard fractionation. We first establish a benchmark by using the DP algorithm to solve the problem exactly. In this case, we characterize the structure of an optimal policy, which provides guidance for our choice of heuristics. We develop two intuitive, numerically near-optimal heuristic policies, which could be used for...Continue Reading

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Citations

Jul 17, 2013·Journal of Radiation Research·T T BöhlenA Mairani
May 6, 2016·Medical Physics·Minsun Kim, Mark H Phillips
Jan 20, 2018·Physics in Medicine and Biology·Daniel O'ConnorKe Sheng

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